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يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

", "aboutText": "يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان. اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens. يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.", "editorialOverlay": { "copy_fields": { "about_html": "

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

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مهمة عملية

مثال تقني باللغة الإنجليزية

Diagnose duplicated webhook effects\n\nReview this flow: receive event; charge wallet; save event_id. If saving fails after charging, redelivery charges again. Propose a corrected transaction boundary using a unique event_id record and the wallet update. State the expected behavior for first delivery, duplicate delivery and failure before commit. Return pseudocode and checks; do not claim to execute them.

النتيجة المتوقعة

Transaction pseudocode and a three-case behavior table for first, duplicate and rolled-back delivery.

التحقق من النتيجة

The deduplication record and wallet effect commit together, and a duplicate produces no second debit.

", "short_text": "Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا." }, "copy_sha256": "62962ed296aec5163e8d45222fe771f9d534c98d5655f24f906281453912c162", "copy_source": { "locale": "ar", "pack_sha256": "0f56d90ba41881e1134accf82e57338f246f8753ca4c0cee929aaffada5d10e7", "record_model_id": "anthropic/claude-sonnet-5", "source_facts_sha256": "66a20ec9312716d3317f404ebeb91e8fc2040a53dd22d7c9ca1c73a268425fc5", "validation_sha256": "a2ac2f28056280fc0b2ea34a501bf156d5ce155406e57e708edf30bfdf6bfdc6" }, "html_sha256": "3e796c5f7eca101590c68175b3c76bc57323107b14caec60d219ca0271809205", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "ar", "methods": [ { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · رسائل Anthropic POST /v1/messages

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-5	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود user, assistant	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_block[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`system`	النوع`string\|content_block[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلبمطلوب	القيم والحدود الحد الأدنى: ⁦1⁩ نطاق تطبيق الحد: الحد الأقصى الدقيق للنموذج/البطاقة المختارة	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop_sequences`	النوع`string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].name`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أداة مقدّمة	القيمة الافتراضية—
الحقل`tools[].description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].input_schema`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`thinking.type`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`thinking.budget_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`output_config.effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`metadata`	النوع`object`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`cache_control`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content أو كتلة type=text

نص + صورة

{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, messages, max_tokens
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot رسائل AnthropicPOST /v1/messages

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · رسائل Anthropic

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-5", "max_tokens": 1024, "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-5", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

import anthropic\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nmsg = client.messages.create(\n    model="claude-sonnet-5",\n    max_tokens=1024,\n    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(msg.to_dict(mode="json"))\n

import Anthropic from "@anthropic-ai/sdk";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n  model: "claude-sonnet-5",\n  max_tokens: 1024,\n  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(msg);\n

import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet-5',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_message()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · رسائل Anthropic

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`model`	النوعstring
الحقل`content[]`	النوعtext\|thinking\|tool_use\|other content block
الحقل`stop_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-5", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "claude-sonnet-5", "route_label": "Core" }, "method_key": "Core|messages|/v1/messages|claude-sonnet-5", "ordinal": 0, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content أو كتلة type=text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "system", "required": false, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "limit_scope": "الحد الأقصى الدقيق للنموذج/البطاقة المختارة", "minimum": 1, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop_sequences", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].name", "required": false, "type": "string", "when": "أداة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].input_schema", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.type", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.budget_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_config.effort", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "metadata", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages", "max_tokens" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/messages" }, "operation_modes": [ "messages" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"max_tokens\": 1024, \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"max_tokens\": 1024, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image\",\"source\":{\"type\":\"base64\",\"media_type\":mime,\"data\":b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "import anthropic\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = anthropic.Anthropic(base_url=\"https://api.ailoot.ai\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nmsg = client.messages.create(\n model=\"claude-sonnet-5\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(msg.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import Anthropic from \"@anthropic-ai/sdk\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new Anthropic({ baseURL: \"https://api.ailoot.ai\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: \"claude-sonnet-5\",\n max_tokens: 1024,\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=anthropic.Anthropic(base_url=\"https://api.ailoot.ai\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet-5',max_tokens=1024,messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · complete final message", "language": "python" } ], "family": "anthropic", "fast_multiplier": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "رسائل Anthropic", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/messages", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-5", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · OpenAI Responses POST /v1/responses

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-5	القيمة الافتراضية—
الحقل`input`	النوع`string\|input_item[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`input[].type`	النوع`string`	المتطلباختياري	القيم والحدود message, reasoning, function_call, function_call_output	القيمة الافتراضية—
الحقل`input[].content`	النوع`string\|content_part[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`input[].call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة	القيمة الافتراضية—
الحقل`input[].output`	النوع`string\|content_part[]`	المتطلباختياري	القيم والحدود ينطبق عندما: function_call_output	القيمة الافتراضية—
الحقل`max_output_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning.effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning.summary`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`text.format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`text.verbosity`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`include`	النوع`string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`store`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`previous_response_id`	النوع`string`	المتطلباختياري	القيم والحدود متطلبات المعرّف ID: معرّف استجابة فعلي فقط من متابعة مدعومة يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_key`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

نص إدخال أو جزء input_text

نص + صورة

{type:input_image,image_url}

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, input
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot OpenAI ResponsesPOST /v1/responses

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · OpenAI Responses

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-5", "input": ""}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["input"]="Summarize this material and quote supporting source passages.\\n\\n"+text\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-5", "input": [{"role": "user", "content": [{"type": "input_text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["input"][0]["content"].append({"type":"input_image","image_url":"data:"+mime+";base64,"+b64})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nresp = client.responses.create(model="claude-sonnet-5", input="Explain the difference between an observation and a hypothesis in three sentences.")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_dict(mode="json"))\n

import OpenAI from "openai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: "claude-sonnet-5", input: "Explain the difference between an observation and a hypothesis in three sentences." });\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(resp);\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nwith client.responses.stream(model="claude-sonnet-5", input="Explain the difference between an observation and a hypothesis in three sentences.") as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_response()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · OpenAI Responses

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`status`	النوعstring
الحقل`output[]`	النوعmessage\|reasoning\|function_call\|other item
الحقل`output[].content[]`	النوعcontent part
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-5", "fmt": "responses", "http": "POST", "path": "/v1/responses", "request_model_id": "claude-sonnet-5", "route_label": "Core" }, "method_key": "Core|responses|/v1/responses|claude-sonnet-5", "ordinal": 1, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every output item and content part, actual function call_id, encrypted reasoning and usage. In streaming retain complete event/item identity.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/responses" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "نص إدخال أو جزء input_text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:input_image,image_url}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "output[]", "type": "message|reasoning|function_call|other item" }, { "description": null, "name": "output[].content[]", "type": "content part" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input", "required": true, "type": "string|input_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "message", "reasoning", "function_call", "function_call_output" ], "enum_known": true, "name": "input[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].content", "required": false, "type": "string|content_part[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].call_id", "required": false, "type": "string", "when": "function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].output", "required": false, "type": "string|content_part[]", "when": "function_call_output" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_output_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.summary", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.verbosity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "include", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "store", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "identity_rule": "معرّف استجابة فعلي فقط من متابعة مدعومة", "name": "previous_response_id", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_key", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "input" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/responses" }, "operation_modes": [ "responses" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"input\": \"\"}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"input\"]=\"Summarize this material and quote supporting source passages.\\n\\n\"+text\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"input\": [{\"role\": \"user\", \"content\": [{\"type\": \"input_text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"input\"][0][\"content\"].append({\"type\":\"input_image\",\"image_url\":\"data:\"+mime+\";base64,\"+b64})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.responses.create(model=\"claude-sonnet-5\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: \"claude-sonnet-5\", input: \"Explain the difference between an observation and a hypothesis in three sentences.\" });\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "Source_stream_contract": "typed parameters.stream=boolean/source_interface/defaultfalse; outputs.format=json or SSE", "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nwith client.responses.stream(model=\"claude-sonnet-5\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\") as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_response()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "creation_argument_parity": "same model/input as existing normal SDK call; SDK sets stream=true", "label": "Python streaming · complete Responses result", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "responses", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "OpenAI Responses", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/responses", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-5", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · محادثة OpenAI POST /v1/chat/completions

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-5	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود أمثلة: system, user, assistant, tool, function الشروط: تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج. يعتمد على النموذج	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_part[]\|null`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_calls`	النوع`tool_call[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: role=tool؛ استخدم المعرّف الفعلي المُرجع	القيمة الافتراضية—
الحقل`messages[].name`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].reasoning_content`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج	القيمة الافتراضية—
الحقل`messages[].reasoning_details`	النوع`object\|array`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_completion_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`stream_options.include_usage`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop`	النوع`string\|string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`function_tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].type`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].function.name`	النوع`string`	المتطلبمطلوب	القيم والحدود ينطبق عندما: أداة دالة مقدّمة	القيمة الافتراضية—
الحقل`tools[].function.description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].function.parameters`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`response_format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning_effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود حقل للتوافق	القيمة الافتراضية—
الحقل`functions`	النوع`function[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`function_call`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content

نص + صورة

{type:image_url,image_url:{url,detail}}

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, messages
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot محادثة OpenAIPOST /v1/chat/completions

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · محادثة OpenAI

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-5", "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-5", "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image_url","image_url":{"url":"data:"+mime+";base64,"+b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nresp = client.chat.completions.create(\n    model="claude-sonnet-5",\n    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_dict(mode="json"))\n

import OpenAI from "openai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n  model: "claude-sonnet-5",\n  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(resp);\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet-5',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · محادثة OpenAI

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`choices[].index`	النوعinteger
الحقل`choices[].message.content`	النوعstring\|null
الحقل`choices[].message.tool_calls`	النوعtool_call[]
الحقل`choices[].message.reasoning_content`	النوعstring
الحقل`choices[].message.reasoning_details`	النوعobject\|array
الحقل`choices[].finish_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-5", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "claude-sonnet-5", "route_label": "Core" }, "method_key": "Core|chat|/v1/chat/completions|claude-sonnet-5", "ordinal": 2, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image_url,image_url:{url,detail}}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/chat/completions" }, "operation_modes": [ "chat_completions" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image_url\",\"image_url\":{\"url\":\"data:\"+mime+\";base64,\"+b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.chat.completions.create(\n model=\"claude-sonnet-5\",\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n model: \"claude-sonnet-5\",\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet-5',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · retain all events", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "محادثة OpenAI", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/chat/completions", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-5", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot Ultra · محادثة OpenAI POST /v1/chat/completions

الإدخال: text
الإخراج: text
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-5	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: محادثة نصية	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`required`	المواصفاتmodel, messages
المعلمة`material_types`	المواصفاتtext
المعلمة`messages`	المواصفاتمصفوفة رسائل ببنية role/content
المعلمة`file_material`	المواصفاتمستند UTF-8 الفعلي مُدرج كنص حرفي؛ لا يُستنتَج معرّف ملف
المعلمة`optional_controls`	المواصفاتstream
المعلمة`control_scope`	المواصفاتمحادثة نصية؛ stream قيمة منطقية، وقيمتها الافتراضية false.
المعلمة`output_modalities`	المواصفاتtext
المعلمة`hosted_operations`	المواصفاتfalse
المعلمة`multimodal_input_binding`	المواصفاتnull

الأسماء البديلة للطريقة: /chat/completions

دورة الحياة: synchronous_or_streamed

أرسل معرّف النموذج الدقيق مع messages.

طول السياق ليس حدًا أقصى للإخراج.

يمكن لملف نصي تقديم نص حرفي؛ وتحتاج مدخلات الصور/الصوت/كائنات الملفات إلى ربط دقيق.

الباقات

مراجع التسعير لا تضيف خيارات للطلب. المعلمات المدعومة مذكورة للطريقة المحددة.

الوضع السريع: التعرفة القياسية عند اختيار الوضع السريع
الوضع المرن: التعرفة القياسية عند اختيار وضع flex
أقصى جهد للاستدلال: التعرفة القياسية عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال
جهد الاستدلال · مرتفع: التعرفة القياسية عندما يكون جهد الاستدلال مرتفعًا
جهد الاستدلال · منخفض: التعرفة القياسية عندما يكون جهد الاستدلال منخفضًا
جهد الاستدلال · الحد الأقصى: التعرفة القياسية عندما يكون جهد الاستدلال عند الحد الأقصى
جهد الاستدلال · متوسط: التعرفة القياسية عندما يكون جهد الاستدلال متوسطًا
جهد الاستدلال · xhigh: التعرفة القياسية عندما يكون جهد الاستدلال xhigh

تعرفات Ailoot

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتالتعرفات الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتالشريحة 1 لطول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

أمثلة للطلبات

Ailoot Ultra · محادثة OpenAI

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model":"claude-sonnet-5","messages":[{"role":"user","content":"hello"}],"stream":false}')\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("result.json").read_text())\nfor x in r.get("choices",[]):\n    if x.get("message",{}).get("content"): print(x["message"]["content"])\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nresult=client.chat.completions.create(model="claude-sonnet-5", messages=[{"role":"user","content":"hello"}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(result.to_dict(mode="json"))\n

استلام النتائج وحفظها

Ailoot Ultra · محادثة OpenAI

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`choices[].index`	النوعinteger
الحقل`choices[].message.content`	النوعstring\|null
الحقل`choices[].message.tool_calls`	النوعtool_call[]
الحقل`choices[].message.reasoning_content`	النوعstring
الحقل`choices[].message.reasoning_details`	النوعobject\|array
الحقل`choices[].finish_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-5", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "claude-sonnet-5", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|claude-sonnet-5", "ordinal": 3, "rawMethod": { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "Send the conversation as text messages. Stream must be a boolean; omitted stream defaults to false." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" } ], "operation_modes": [ "conversation" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string", "when": "محادثة نصية" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Text conversation at the exact model ID and method path.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "أرسل معرّف النموذج الدقيق مع messages.", "طول السياق ليس حدًا أقصى للإخراج.", "يمكن لملف نصي تقديم نص حرفي؛ وتحتاج مدخلات الصور/الصوت/كائنات الملفات إلى ربط دقيق." ], "input": { "content_type": "application/json", "control_scope": "محادثة نصية؛ stream قيمة منطقية، وقيمتها الافتراضية false.", "file_material": "مستند UTF-8 الفعلي مُدرج كنص حرفي؛ لا يُستنتَج معرّف ملف", "hosted_operations": false, "material_types": [ "text" ], "messages": "مصفوفة رسائل ببنية role/content", "multimodal_input_binding": null, "optional_controls": [ "stream" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [ "/chat/completions" ], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\":\"claude-sonnet-5\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}],\"stream\":false}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model=\"claude-sonnet-5\", messages=[{\"role\":\"user\",\"content\":\"hello\"}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" } ], "family": "openai", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "chat", "hints": [ "Send exact model ID with messages.", "Context length is not an output cap.", "A text file may supply literal text; image/audio/file-object inputs need exact binding." ], "http": "POST", "in": 4, "input": [ "text" ], "label": "محادثة OpenAI", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [ "/chat/completions" ], "out": 20, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Fast mode", "value": "Standard rate", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Standard rate", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Standard rate", "when": "When maximum reasoning effort uses the default adjustment" }, { "label": "Reasoning effort · high", "value": "Standard rate", "when": "When reasoning effort is high" }, { "label": "Reasoning effort · low", "value": "Standard rate", "when": "When reasoning effort is low" }, { "label": "Reasoning effort · max", "value": "Standard rate", "when": "When reasoning effort is max" }, { "label": "Reasoning effort · medium", "value": "Standard rate", "when": "When reasoning effort is medium" }, { "label": "Reasoning effort · xhigh", "value": "Standard rate", "when": "When reasoning effort is xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص
النتائج: json · sse

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot Ultra · رسائل Anthropic POST /v1/messages

الإدخال: text
الإخراج: json, sse
صيغة الإخراج: JSON أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-5	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود user, assistant	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse

تركيبات مواد الإدخال

النص · نص UTF-8

سلسلة نصية messages[].content

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`required`	المواصفاتmodel, messages, max_tokens
المعلمة`optional_controls`	المواصفاتstream
المعلمة`material_types`	المواصفاتtext
المعلمة`text_file_material`	المواصفاتاقرأ مستند UTF-8 الفعلي وضع نصه في الإدخال المحدد أو السلسلة النصية لمحتوى الرسالة.

دورة الحياة: synchronous_or_streamed

الباقات

مراجع التسعير لا تضيف خيارات للطلب. المعلمات المدعومة مذكورة للطريقة المحددة.

الوضع السريع: التعرفة القياسية عند اختيار الوضع السريع
الوضع المرن: التعرفة القياسية عند اختيار وضع flex
أقصى جهد للاستدلال: التعرفة القياسية عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال
جهد الاستدلال · مرتفع: التعرفة القياسية عندما يكون جهد الاستدلال مرتفعًا
جهد الاستدلال · منخفض: التعرفة القياسية عندما يكون جهد الاستدلال منخفضًا
جهد الاستدلال · الحد الأقصى: التعرفة القياسية عندما يكون جهد الاستدلال عند الحد الأقصى
جهد الاستدلال · متوسط: التعرفة القياسية عندما يكون جهد الاستدلال متوسطًا
جهد الاستدلال · xhigh: التعرفة القياسية عندما يكون جهد الاستدلال xhigh

تعرفات Ailoot

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتالتعرفات الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتالشريحة 1 لطول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

أمثلة للطلبات

Ailoot Ultra · رسائل Anthropic

{\n  "model": "claude-sonnet-5",\n  "max_tokens": 128,\n  "messages": [\n    {\n      "role": "user",\n      "content": "Summarize the incident report."\n    }\n  ],\n  "stream": false\n}

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n

import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n

استلام النتائج وحفظها

Ailoot Ultra · رسائل Anthropic

JSON أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`model`	النوعstring
الحقل`content[]`	النوعtext\|thinking\|tool_use\|other content block
الحقل`stop_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-5", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "claude-sonnet-5", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|claude-sonnet-5", "ordinal": 4, "rawMethod": { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "claude-sonnet-5", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "سلسلة نصية messages[].content", "required_material": "نص UTF-8" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "claude-sonnet-5" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "claude-sonnet-5", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "اقرأ مستند UTF-8 الفعلي وضع نصه في الإدخال المحدد أو السلسلة النصية لمحتوى الرسالة." }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 4, "input": [ "text" ], "label": "رسائل Anthropic", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 20, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Fast mode", "value": "Standard rate", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Standard rate", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Standard rate", "when": "When maximum reasoning effort uses the default adjustment" }, { "label": "Reasoning effort · high", "value": "Standard rate", "when": "When reasoning effort is high" }, { "label": "Reasoning effort · low", "value": "Standard rate", "when": "When reasoning effort is low" }, { "label": "Reasoning effort · max", "value": "Standard rate", "when": "When reasoning effort is max" }, { "label": "Reasoning effort · medium", "value": "Standard rate", "when": "When reasoning effort is medium" }, { "label": "Reasoning effort · xhigh", "value": "Standard rate", "when": "When reasoning effort is xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · رسائل Anthropic POST /v1/messages

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود user, assistant	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_block[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`system`	النوع`string\|content_block[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلبمطلوب	القيم والحدود الحد الأدنى: ⁦1⁩ نطاق تطبيق الحد: الحد الأقصى الدقيق للنموذج/البطاقة المختارة	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop_sequences`	النوع`string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].name`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أداة مقدّمة	القيمة الافتراضية—
الحقل`tools[].description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].input_schema`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`thinking.type`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`thinking.budget_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`output_config.effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`metadata`	النوع`object`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`cache_control`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content أو كتلة type=text

نص + صورة

{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, messages, max_tokens
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot رسائل AnthropicPOST /v1/messages

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · رسائل Anthropic

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet", "max_tokens": 1024, "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

import anthropic\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nmsg = client.messages.create(\n    model="claude-sonnet",\n    max_tokens=1024,\n    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(msg.to_dict(mode="json"))\n

import Anthropic from "@anthropic-ai/sdk";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n  model: "claude-sonnet",\n  max_tokens: 1024,\n  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(msg);\n

import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_message()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · رسائل Anthropic

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`model`	النوعstring
الحقل`content[]`	النوعtext\|thinking\|tool_use\|other content block
الحقل`stop_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "claude-sonnet", "route_label": "Core" }, "method_key": "Core|messages|/v1/messages|claude-sonnet", "ordinal": 5, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content أو كتلة type=text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "system", "required": false, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "limit_scope": "الحد الأقصى الدقيق للنموذج/البطاقة المختارة", "minimum": 1, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop_sequences", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].name", "required": false, "type": "string", "when": "أداة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].input_schema", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.type", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.budget_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_config.effort", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "metadata", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages", "max_tokens" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/messages" }, "operation_modes": [ "messages" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"max_tokens\": 1024, \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"max_tokens\": 1024, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image\",\"source\":{\"type\":\"base64\",\"media_type\":mime,\"data\":b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "import anthropic\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = anthropic.Anthropic(base_url=\"https://api.ailoot.ai\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nmsg = client.messages.create(\n model=\"claude-sonnet\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(msg.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import Anthropic from \"@anthropic-ai/sdk\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new Anthropic({ baseURL: \"https://api.ailoot.ai\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: \"claude-sonnet\",\n max_tokens: 1024,\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=anthropic.Anthropic(base_url=\"https://api.ailoot.ai\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet',max_tokens=1024,messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · complete final message", "language": "python" } ], "family": "anthropic", "fast_multiplier": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "رسائل Anthropic", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/messages", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · OpenAI Responses POST /v1/responses

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet	القيمة الافتراضية—
الحقل`input`	النوع`string\|input_item[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`input[].type`	النوع`string`	المتطلباختياري	القيم والحدود message, reasoning, function_call, function_call_output	القيمة الافتراضية—
الحقل`input[].content`	النوع`string\|content_part[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`input[].call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة	القيمة الافتراضية—
الحقل`input[].output`	النوع`string\|content_part[]`	المتطلباختياري	القيم والحدود ينطبق عندما: function_call_output	القيمة الافتراضية—
الحقل`max_output_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning.effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning.summary`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`text.format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`text.verbosity`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`include`	النوع`string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`store`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`previous_response_id`	النوع`string`	المتطلباختياري	القيم والحدود متطلبات المعرّف ID: معرّف استجابة فعلي فقط من متابعة مدعومة يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_key`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

نص إدخال أو جزء input_text

نص + صورة

{type:input_image,image_url}

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, input
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot OpenAI ResponsesPOST /v1/responses

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · OpenAI Responses

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet", "input": ""}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["input"]="Summarize this material and quote supporting source passages.\\n\\n"+text\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet", "input": [{"role": "user", "content": [{"type": "input_text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["input"][0]["content"].append({"type":"input_image","image_url":"data:"+mime+";base64,"+b64})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nresp = client.responses.create(model="claude-sonnet", input="Explain the difference between an observation and a hypothesis in three sentences.")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_dict(mode="json"))\n

import OpenAI from "openai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: "claude-sonnet", input: "Explain the difference between an observation and a hypothesis in three sentences." });\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(resp);\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nwith client.responses.stream(model="claude-sonnet", input="Explain the difference between an observation and a hypothesis in three sentences.") as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_response()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · OpenAI Responses

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`status`	النوعstring
الحقل`output[]`	النوعmessage\|reasoning\|function_call\|other item
الحقل`output[].content[]`	النوعcontent part
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet", "fmt": "responses", "http": "POST", "path": "/v1/responses", "request_model_id": "claude-sonnet", "route_label": "Core" }, "method_key": "Core|responses|/v1/responses|claude-sonnet", "ordinal": 6, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every output item and content part, actual function call_id, encrypted reasoning and usage. In streaming retain complete event/item identity.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/responses" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "نص إدخال أو جزء input_text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:input_image,image_url}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "output[]", "type": "message|reasoning|function_call|other item" }, { "description": null, "name": "output[].content[]", "type": "content part" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input", "required": true, "type": "string|input_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "message", "reasoning", "function_call", "function_call_output" ], "enum_known": true, "name": "input[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].content", "required": false, "type": "string|content_part[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].call_id", "required": false, "type": "string", "when": "function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].output", "required": false, "type": "string|content_part[]", "when": "function_call_output" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_output_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.summary", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.verbosity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "include", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "store", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "identity_rule": "معرّف استجابة فعلي فقط من متابعة مدعومة", "name": "previous_response_id", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_key", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "input" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/responses" }, "operation_modes": [ "responses" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"input\": \"\"}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"input\"]=\"Summarize this material and quote supporting source passages.\\n\\n\"+text\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"input\": [{\"role\": \"user\", \"content\": [{\"type\": \"input_text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"input\"][0][\"content\"].append({\"type\":\"input_image\",\"image_url\":\"data:\"+mime+\";base64,\"+b64})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.responses.create(model=\"claude-sonnet\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: \"claude-sonnet\", input: \"Explain the difference between an observation and a hypothesis in three sentences.\" });\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "Source_stream_contract": "typed parameters.stream=boolean/source_interface/defaultfalse; outputs.format=json or SSE", "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nwith client.responses.stream(model=\"claude-sonnet\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\") as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_response()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "creation_argument_parity": "same model/input as existing normal SDK call; SDK sets stream=true", "label": "Python streaming · complete Responses result", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "responses", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "OpenAI Responses", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/responses", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · محادثة OpenAI POST /v1/chat/completions

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود أمثلة: system, user, assistant, tool, function الشروط: تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج. يعتمد على النموذج	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_part[]\|null`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_calls`	النوع`tool_call[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: role=tool؛ استخدم المعرّف الفعلي المُرجع	القيمة الافتراضية—
الحقل`messages[].name`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].reasoning_content`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج	القيمة الافتراضية—
الحقل`messages[].reasoning_details`	النوع`object\|array`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_completion_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`stream_options.include_usage`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop`	النوع`string\|string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`function_tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].type`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].function.name`	النوع`string`	المتطلبمطلوب	القيم والحدود ينطبق عندما: أداة دالة مقدّمة	القيمة الافتراضية—
الحقل`tools[].function.description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].function.parameters`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`response_format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning_effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود حقل للتوافق	القيمة الافتراضية—
الحقل`functions`	النوع`function[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`function_call`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content

نص + صورة

{type:image_url,image_url:{url,detail}}

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, messages
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot محادثة OpenAIPOST /v1/chat/completions

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · محادثة OpenAI

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet", "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet", "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image_url","image_url":{"url":"data:"+mime+";base64,"+b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nresp = client.chat.completions.create(\n    model="claude-sonnet",\n    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_dict(mode="json"))\n

import OpenAI from "openai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n  model: "claude-sonnet",\n  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(resp);\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · محادثة OpenAI

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`choices[].index`	النوعinteger
الحقل`choices[].message.content`	النوعstring\|null
الحقل`choices[].message.tool_calls`	النوعtool_call[]
الحقل`choices[].message.reasoning_content`	النوعstring
الحقل`choices[].message.reasoning_details`	النوعobject\|array
الحقل`choices[].finish_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "claude-sonnet", "route_label": "Core" }, "method_key": "Core|chat|/v1/chat/completions|claude-sonnet", "ordinal": 7, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image_url,image_url:{url,detail}}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/chat/completions" }, "operation_modes": [ "chat_completions" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image_url\",\"image_url\":{\"url\":\"data:\"+mime+\";base64,\"+b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.chat.completions.create(\n model=\"claude-sonnet\",\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n model: \"claude-sonnet\",\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · retain all events", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "محادثة OpenAI", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/chat/completions", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-latest

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · رسائل Anthropic POST /v1/messages

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-latest	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود user, assistant	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_block[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`system`	النوع`string\|content_block[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلبمطلوب	القيم والحدود الحد الأدنى: ⁦1⁩ نطاق تطبيق الحد: الحد الأقصى الدقيق للنموذج/البطاقة المختارة	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop_sequences`	النوع`string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].name`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أداة مقدّمة	القيمة الافتراضية—
الحقل`tools[].description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].input_schema`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`thinking.type`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`thinking.budget_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`output_config.effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`metadata`	النوع`object`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`cache_control`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content أو كتلة type=text

نص + صورة

{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, messages, max_tokens
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot رسائل AnthropicPOST /v1/messages

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · رسائل Anthropic

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-latest", "max_tokens": 1024, "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-latest", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

import anthropic\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nmsg = client.messages.create(\n    model="claude-sonnet-latest",\n    max_tokens=1024,\n    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(msg.to_dict(mode="json"))\n

import Anthropic from "@anthropic-ai/sdk";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n  model: "claude-sonnet-latest",\n  max_tokens: 1024,\n  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(msg);\n

import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet-latest',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_message()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · رسائل Anthropic

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`model`	النوعstring
الحقل`content[]`	النوعtext\|thinking\|tool_use\|other content block
الحقل`stop_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-latest", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "claude-sonnet-latest", "route_label": "Core" }, "method_key": "Core|messages|/v1/messages|claude-sonnet-latest", "ordinal": 8, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content أو كتلة type=text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-latest" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "system", "required": false, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "limit_scope": "الحد الأقصى الدقيق للنموذج/البطاقة المختارة", "minimum": 1, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop_sequences", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].name", "required": false, "type": "string", "when": "أداة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].input_schema", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.type", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.budget_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_config.effort", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "metadata", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages", "max_tokens" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/messages" }, "operation_modes": [ "messages" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"max_tokens\": 1024, \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"max_tokens\": 1024, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image\",\"source\":{\"type\":\"base64\",\"media_type\":mime,\"data\":b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "import anthropic\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = anthropic.Anthropic(base_url=\"https://api.ailoot.ai\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nmsg = client.messages.create(\n model=\"claude-sonnet-latest\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(msg.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import Anthropic from \"@anthropic-ai/sdk\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new Anthropic({ baseURL: \"https://api.ailoot.ai\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: \"claude-sonnet-latest\",\n max_tokens: 1024,\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=anthropic.Anthropic(base_url=\"https://api.ailoot.ai\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet-latest',max_tokens=1024,messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · complete final message", "language": "python" } ], "family": "anthropic", "fast_multiplier": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "رسائل Anthropic", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/messages", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-latest", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-latest

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · OpenAI Responses POST /v1/responses

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-latest	القيمة الافتراضية—
الحقل`input`	النوع`string\|input_item[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`input[].type`	النوع`string`	المتطلباختياري	القيم والحدود message, reasoning, function_call, function_call_output	القيمة الافتراضية—
الحقل`input[].content`	النوع`string\|content_part[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`input[].call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة	القيمة الافتراضية—
الحقل`input[].output`	النوع`string\|content_part[]`	المتطلباختياري	القيم والحدود ينطبق عندما: function_call_output	القيمة الافتراضية—
الحقل`max_output_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning.effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning.summary`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`text.format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`text.verbosity`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`include`	النوع`string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`store`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`previous_response_id`	النوع`string`	المتطلباختياري	القيم والحدود متطلبات المعرّف ID: معرّف استجابة فعلي فقط من متابعة مدعومة يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_key`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

نص إدخال أو جزء input_text

نص + صورة

{type:input_image,image_url}

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, input
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot OpenAI ResponsesPOST /v1/responses

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · OpenAI Responses

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-latest", "input": ""}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["input"]="Summarize this material and quote supporting source passages.\\n\\n"+text\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-latest", "input": [{"role": "user", "content": [{"type": "input_text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["input"][0]["content"].append({"type":"input_image","image_url":"data:"+mime+";base64,"+b64})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nresp = client.responses.create(model="claude-sonnet-latest", input="Explain the difference between an observation and a hypothesis in three sentences.")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_dict(mode="json"))\n

import OpenAI from "openai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: "claude-sonnet-latest", input: "Explain the difference between an observation and a hypothesis in three sentences." });\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(resp);\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nwith client.responses.stream(model="claude-sonnet-latest", input="Explain the difference between an observation and a hypothesis in three sentences.") as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_response()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · OpenAI Responses

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`status`	النوعstring
الحقل`output[]`	النوعmessage\|reasoning\|function_call\|other item
الحقل`output[].content[]`	النوعcontent part
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-latest", "fmt": "responses", "http": "POST", "path": "/v1/responses", "request_model_id": "claude-sonnet-latest", "route_label": "Core" }, "method_key": "Core|responses|/v1/responses|claude-sonnet-latest", "ordinal": 9, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every output item and content part, actual function call_id, encrypted reasoning and usage. In streaming retain complete event/item identity.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/responses" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "نص إدخال أو جزء input_text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:input_image,image_url}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "output[]", "type": "message|reasoning|function_call|other item" }, { "description": null, "name": "output[].content[]", "type": "content part" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-latest" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input", "required": true, "type": "string|input_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "message", "reasoning", "function_call", "function_call_output" ], "enum_known": true, "name": "input[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].content", "required": false, "type": "string|content_part[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].call_id", "required": false, "type": "string", "when": "function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].output", "required": false, "type": "string|content_part[]", "when": "function_call_output" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_output_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.summary", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.verbosity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "include", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "store", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "identity_rule": "معرّف استجابة فعلي فقط من متابعة مدعومة", "name": "previous_response_id", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_key", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "input" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/responses" }, "operation_modes": [ "responses" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"input\": \"\"}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"input\"]=\"Summarize this material and quote supporting source passages.\\n\\n\"+text\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"input\": [{\"role\": \"user\", \"content\": [{\"type\": \"input_text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"input\"][0][\"content\"].append({\"type\":\"input_image\",\"image_url\":\"data:\"+mime+\";base64,\"+b64})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.responses.create(model=\"claude-sonnet-latest\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: \"claude-sonnet-latest\", input: \"Explain the difference between an observation and a hypothesis in three sentences.\" });\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "Source_stream_contract": "typed parameters.stream=boolean/source_interface/defaultfalse; outputs.format=json or SSE", "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nwith client.responses.stream(model=\"claude-sonnet-latest\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\") as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_response()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "creation_argument_parity": "same model/input as existing normal SDK call; SDK sets stream=true", "label": "Python streaming · complete Responses result", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "responses", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "OpenAI Responses", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/responses", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-latest", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /claude-sonnet-latest

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص · الصور
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot · محادثة OpenAI POST /v1/chat/completions

الإدخال: text, image
الإخراج: text
السياق: ⁦1,000,000⁩ tokens
الحد الأقصى للإخراج: ⁦131,072⁩ tokens
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود claude-sonnet-latest	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود أمثلة: system, user, assistant, tool, function الشروط: تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج. يعتمد على النموذج	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_part[]\|null`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_calls`	النوع`tool_call[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: role=tool؛ استخدم المعرّف الفعلي المُرجع	القيمة الافتراضية—
الحقل`messages[].name`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].reasoning_content`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج	القيمة الافتراضية—
الحقل`messages[].reasoning_details`	النوع`object\|array`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_completion_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`stream_options.include_usage`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop`	النوع`string\|string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`function_tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].type`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].function.name`	النوع`string`	المتطلبمطلوب	القيم والحدود ينطبق عندما: أداة دالة مقدّمة	القيمة الافتراضية—
الحقل`tools[].function.description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].function.parameters`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`response_format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning_effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود حقل للتوافق	القيمة الافتراضية—
الحقل`functions`	النوع`function[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`function_call`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content

نص + صورة

{type:image_url,image_url:{url,detail}}

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`material_types`	المواصفاتtext, image
المعلمة`required`	المواصفاتmodel, messages
المعلمة`optional_controls`	المواصفاتnull
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`text_file_material`	المواصفاتمحتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل

دورة الحياة: exact retained published method

بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب.

الباقات

تعرفات طرائق Ailoot

Ailoot محادثة OpenAIPOST /v1/chat/completions

الإدخال: ⁦‏0.002 US$⁩ / 1K
الإخراج: ⁦‏0.01 US$⁩ / 1K
قراءة ذاكرة التخزين المؤقت: ⁦‏0.0002 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت: ⁦‏0.0025 US$⁩ / 1K
الكتابة إلى ذاكرة التخزين المؤقت، 5 دقائق: ⁦‏0.0025 US$⁩ / 1K tokens
الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة: ⁦‏0.004 US$⁩ / 1K tokens
web_search_call: ⁦‏0.01 US$⁩ لكل استدعاء
أقصى عدد للاستدعاءات web_search_call: ⁦8⁩

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

تفاصيل التعرفة المرجعية

لا تغيّر جداول التعرفة المرجعية على مستوى النموذج اختيار الطريقة أو عروض الأسعار أو الرسوم. وتستخدم الرسوم الفعلية تعرفات طريقة Ailoot المحددة.

جداول التعرفة المرجعية للنموذج

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتOpenAI Chat · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتOpenAI Chat · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الأسعار الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتAnthropic Messages · الشريحة 1 حسب طول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

أمثلة للطلبات

Ailoot · محادثة OpenAI

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-latest", "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "claude-sonnet-latest", "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image_url","image_url":{"url":"data:"+mime+";base64,"+b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nresp = client.chat.completions.create(\n    model="claude-sonnet-latest",\n    messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_dict(mode="json"))\n

import OpenAI from "openai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n  model: "claude-sonnet-latest",\n  messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n  writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n  console.log(JSON.stringify(data, null, 2));\n  const saveBlob = (encoded, suffix, label) => {\n    const raw = Buffer.from(encoded, "base64");\n    const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n    const file = `${stem}-${label}.${ext}`;\n    writeFileSync(file, raw); console.log("Saved", file);\n  };\n  for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n  for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n  for (const [i, item] of (data.output || []).entries()) {\n    console.log("Output", i, JSON.stringify(item));\n    if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n  }\n  for (const [ci, candidate] of (data.candidates || []).entries()) {\n    for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n      console.log("Candidate/part", ci, pi, JSON.stringify(part));\n      const blob = part.inlineData || part.inline_data;\n      if (blob?.data) {\n        const mime = blob.mimeType || blob.mime_type;\n        const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n        saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n      }\n    }\n  }\n}\n\nsaveResult(resp);\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet-latest',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot · محادثة OpenAI

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`choices[].index`	النوعinteger
الحقل`choices[].message.content`	النوعstring\|null
الحقل`choices[].message.tool_calls`	النوعtool_call[]
الحقل`choices[].message.reasoning_content`	النوعstring
الحقل`choices[].message.reasoning_details`	النوعobject\|array
الحقل`choices[].finish_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "claude-sonnet-latest", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "claude-sonnet-latest", "route_label": "Core" }, "method_key": "Core|chat|/v1/chat/completions|claude-sonnet-latest", "ordinal": 10, "rawMethod": { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image_url,image_url:{url,detail}}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-latest" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/chat/completions" }, "operation_modes": [ "chat_completions" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image_url\",\"image_url\":{\"url\":\"data:\"+mime+\";base64,\"+b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.chat.completions.create(\n model=\"claude-sonnet-latest\",\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n model: \"claude-sonnet-latest\",\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet-latest',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · retain all events", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "محادثة OpenAI", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/chat/completions", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-latest", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /anthropic/claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص
النتائج: النص

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot Ultra · محادثة OpenAI POST /v1/chat/completions

الإدخال: text
الإخراج: text
صيغة الإخراج: json أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود anthropic/claude-sonnet-5	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود الحد الأدنى للعناصر: ⁦1⁩	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود أمثلة: system, user, assistant, tool, function الشروط: تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج. يعتمد على النموذج	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string\|content_part[]\|null`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_calls`	النوع`tool_call[]`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].tool_call_id`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: role=tool؛ استخدم المعرّف الفعلي المُرجع	القيمة الافتراضية—
الحقل`messages[].name`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].reasoning_content`	النوع`string`	المتطلباختياري	القيم والحدود ينطبق عندما: أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج	القيمة الافتراضية—
الحقل`messages[].reasoning_details`	النوع`object\|array`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`max_completion_tokens`	النوع`integer`	المتطلباختياري	القيم والحدود الحد الأدنى: ⁦1⁩ يعتمد على النموذج	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse
الحقل`stream_options.include_usage`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`temperature`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`top_p`	النوع`number`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`stop`	النوع`string\|string[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools`	النوع`function_tool[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].type`	النوع`string`	المتطلباختياري	القيم والحدود function يعتمد على النموذج	القيمة الافتراضية—
الحقل`tools[].function.name`	النوع`string`	المتطلبمطلوب	القيم والحدود ينطبق عندما: أداة دالة مقدّمة	القيمة الافتراضية—
الحقل`tools[].function.description`	النوع`string`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tools[].function.parameters`	النوع`JSON_schema`	المتطلباختياري	القيم والحدود	القيمة الافتراضية—
الحقل`tool_choice`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`parallel_tool_calls`	النوع`boolean`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`response_format`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning_effort`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`reasoning`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`service_tier`	النوع`string`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`instructions`	النوع`string`	المتطلباختياري	القيم والحدود حقل للتوافق	القيمة الافتراضية—
الحقل`functions`	النوع`function[]`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`function_call`	النوع`string\|object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`prompt_cache_options`	النوع`object`	المتطلباختياري	القيم والحدود يعتمد على النموذج	القيمة الافتراضية—
الحقل`modalities`	النوع`string[]`	المتطلباختياري	القيم والحدود text	القيمة الافتراضية—
الحقل`provider`	النوع`object`	المتطلباختياري	القيم والحدود الشروط: يُرفَض provider.options في مسار Ultra النصي هذا	القيمة الافتراضية—
الحقل`cache_control.ttl`	النوع`string`	المتطلباختياري	القيم والحدود الشروط: تُرفَض 1h في المواضع الفعلية للتخزين المؤقت للموجّه	القيمة الافتراضية—

تركيبات مواد الإدخال

النص · نص UTF8

messages[].content

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`required`	المواصفاتmodel, messages
المعلمة`material_types`	المواصفاتtext
المعلمة`messages`	المواصفاتمصفوفة رسائل ببنية role/content
المعلمة`file_material`	المواصفاتمستند UTF-8 الفعلي مُدرج كنص حرفي؛ لا يُستنتَج معرّف ملف
المعلمة`optional_controls`	المواصفاتstream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice
المعلمة`control_scope`	المواصفاتخاص بالنموذج؛ أدوات الدوال التي يقدّمها المستخدم تختلف عن الأدوات المستضافة
المعلمة`output_modalities`	المواصفاتtext
المعلمة`hosted_operations`	المواصفاتfalse
المعلمة`multimodal_input_binding`	المواصفاتnull

دورة الحياة: synchronous_or_streamed

أرسل معرّف النموذج الدقيق مع messages.

طول السياق ليس حدًا أقصى للإخراج.

يمكن لملف نصي تقديم نص حرفي؛ وتحتاج مدخلات الصور/الصوت/كائنات الملفات إلى ربط دقيق.

الباقات

مراجع التسعير لا تضيف خيارات للطلب. المعلمات المدعومة مذكورة للطريقة المحددة.

الوضع السريع: التعرفة القياسية عند اختيار الوضع السريع
الوضع المرن: التعرفة القياسية عند اختيار وضع flex
أقصى جهد للاستدلال: التعرفة القياسية عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال
جهد الاستدلال · مرتفع: التعرفة القياسية عندما يكون جهد الاستدلال مرتفعًا
جهد الاستدلال · منخفض: التعرفة القياسية عندما يكون جهد الاستدلال منخفضًا
جهد الاستدلال · الحد الأقصى: التعرفة القياسية عندما يكون جهد الاستدلال عند الحد الأقصى
جهد الاستدلال · متوسط: التعرفة القياسية عندما يكون جهد الاستدلال متوسطًا
جهد الاستدلال · xhigh: التعرفة القياسية عندما يكون جهد الاستدلال xhigh

تعرفات Ailoot

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتالتعرفات الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتالشريحة 1 لطول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

أمثلة للطلبات

Ailoot Ultra · محادثة OpenAI

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "anthropic/claude-sonnet-5", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}')\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("result.json").read_text())\nfor x in r.get("choices",[]):\n    if x.get("message",{}).get("content"): print(x["message"]["content"])\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nresult=client.chat.completions.create(model='anthropic/claude-sonnet-5',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(result.to_dict(mode="json"))\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.chat.completions.stream(model='anthropic/claude-sonnet-5',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

استلام النتائج وحفظها

Ailoot Ultra · محادثة OpenAI

json أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`choices[].index`	النوعinteger
الحقل`choices[].message.content`	النوعstring\|null
الحقل`choices[].message.tool_calls`	النوعtool_call[]
الحقل`choices[].message.reasoning_content`	النوعstring
الحقل`choices[].message.reasoning_details`	النوعobject\|array
الحقل`choices[].finish_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "anthropic/claude-sonnet-5", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|anthropic%2Fclaude-sonnet-5", "ordinal": 11, "rawMethod": { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID.", "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "anthropic/claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": [ "function" ], "enum_known": true, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "text" ], "enum_known": true, "name": "modalities", "required": false, "type": "string[]" }, { "availability": "source_interface", "conditions": "يُرفَض provider.options في مسار Ultra النصي هذا", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "تُرفَض 1h في المواضع الفعلية للتخزين المؤقت للموجّه", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "أرسل معرّف النموذج الدقيق مع messages.", "طول السياق ليس حدًا أقصى للإخراج.", "يمكن لملف نصي تقديم نص حرفي؛ وتحتاج مدخلات الصور/الصوت/كائنات الملفات إلى ربط دقيق." ], "input": { "content_type": "application/json", "control_scope": "خاص بالنموذج؛ أدوات الدوال التي يقدّمها المستخدم تختلف عن الأدوات المستضافة", "file_material": "مستند UTF-8 الفعلي مُدرج كنص حرفي؛ لا يُستنتَج معرّف ملف", "hosted_operations": false, "material_types": [ "text" ], "messages": "مصفوفة رسائل ببنية role/content", "multimodal_input_binding": null, "optional_controls": [ "stream", "temperature", "top_p", "stop", "max_tokens", "max_completion_tokens", "reasoning", "response_format", "tools", "tool_choice" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "الشريحة 1 لطول الطلب", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"anthropic/claude-sonnet-5\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='anthropic/claude-sonnet-5',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='anthropic/claude-sonnet-5',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python SDK streaming · all events", "language": "python" } ], "family": "openai", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "chat", "hints": [ "Send exact model ID with messages.", "Context length is not an output cap.", "A text file may supply literal text; image/audio/file-object inputs need exact binding." ], "http": "POST", "in": 4, "input": [ "text" ], "label": "محادثة OpenAI", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 20, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "الوضع السريع", "value": "التعرفة القياسية", "when": "عند اختيار الوضع السريع" }, { "label": "الوضع المرن", "value": "التعرفة القياسية", "when": "عند اختيار وضع flex" }, { "label": "أقصى جهد للاستدلال", "value": "التعرفة القياسية", "when": "عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال" }, { "label": "جهد الاستدلال · مرتفع", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال مرتفعًا" }, { "label": "جهد الاستدلال · منخفض", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال منخفضًا" }, { "label": "جهد الاستدلال · الحد الأقصى", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال عند الحد الأقصى" }, { "label": "جهد الاستدلال · متوسط", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال متوسطًا" }, { "label": "جهد الاستدلال · xhigh", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "interval_boundary": "min_exclusive_max_inclusive", "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "null_rate_policy": "unknown or inherited; never zero", "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } }, { "html": "

A

Anthropic: Claude Sonnet 5

Anthropic /anthropic/claude-sonnet-5

معرّف النموذج ID

البداية

Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.

المدخلات المقبولة: النص
النتائج: json · sse

عن النموذج

يغطي هذا الوصف قدرات النموذج. وترد أدناه المدخلات والمخرجات والخيارات المتاحة في Ailoot للطريقة المحددة.

يدعم anthropic/claude-sonnet-5 محادثات متزامنة أو متدفقة لعمل يتطور من أدلة مقدمة. مهمة برمجية ملموسة هي مراجعة الشيفرة مع لقطة، واقتراح إصلاح مركز وشرح التحقق من الخلل الأصلي. تقبل طرائق Core النص والصور، بسياق مدرج 1,000,000 رمز وسقف إخراج 131,072 رمزًا. حد السياق وحد الإجابة مستقلان.

اختر الطريقة المطابقة لعميلك: Messages أو Responses أو Chat Completions. تطلب نسخ Core ‏claude-sonnet-5, claude-sonnet أو claude-sonnet-latest؛ وتستخدم Ultra معرّفاتها المعلنة وتدرج النص فقط. اختر طريقة Core معلنة للصور عندما تهم اللقطة، بدل نقل دعمها إلى Ultra من بيانات العائلة. تتطلب Messages الحقل max_tokens.

يقدم وصف النموذج المقبول استدلالًا تكيفيًا للتحليل الأعمق. يعتمد حقل API على الواجهة: output_config.effort وreasoning.effort وreasoning_effort حقول طرائق مختلفة بدعم يعتمد على النموذج. تنفذ أدوات التطبيق الأفعال المقترحة وتعيد الملاحظات الفعلية؛ فلا يطبق نص النموذج وحده تعديلًا أو يشغل متصفحًا. احفظ كل كتل الرد وفروق التدفق عند جمع النتيجة. يتبع هذا الإدخال العادي دورة المحادثة؛ وتخص المهام الجماعية المستقلة المؤجلة إدخال :batch المعرّف بصورة منفصلة.

متاح في Ailoot · المدخلات والطرائق

Ailoot Ultra · رسائل Anthropic POST /v1/messages

الإدخال: text
الإخراج: json, sse
صيغة الإخراج: JSON أو SSE

الحقل	النوع	المتطلب	القيم والحدود	القيمة الافتراضية
الحقل`model`	النوع`string`	المتطلبمطلوب	القيم والحدود anthropic/claude-sonnet-5	القيمة الافتراضية—
الحقل`messages`	النوع`message[]`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`messages[].role`	النوع`string`	المتطلبمطلوب	القيم والحدود user, assistant	القيمة الافتراضية—
الحقل`messages[].content`	النوع`string`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`max_tokens`	النوع`integer`	المتطلبمطلوب	القيم والحدود	القيمة الافتراضية—
الحقل`stream`	النوع`boolean`	المتطلباختياري	القيم والحدود	القيمة الافتراضيةfalse

تركيبات مواد الإدخال

النص · نص UTF-8

سلسلة نصية messages[].content

معلمات الطريقة ودورة حياتها

المعلمة	المواصفات
المعلمة`content_type`	المواصفاتapplication/json
المعلمة`required`	المواصفاتmodel, messages, max_tokens
المعلمة`optional_controls`	المواصفاتstream
المعلمة`material_types`	المواصفاتtext
المعلمة`text_file_material`	المواصفاتاقرأ مستند UTF-8 الفعلي وضع نصه في الإدخال المحدد أو السلسلة النصية لمحتوى الرسالة.

دورة الحياة: synchronous_or_streamed

الباقات

مراجع التسعير لا تضيف خيارات للطلب. المعلمات المدعومة مذكورة للطريقة المحددة.

الوضع السريع: التعرفة القياسية عند اختيار الوضع السريع
الوضع المرن: التعرفة القياسية عند اختيار وضع flex
أقصى جهد للاستدلال: التعرفة القياسية عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال
جهد الاستدلال · مرتفع: التعرفة القياسية عندما يكون جهد الاستدلال مرتفعًا
جهد الاستدلال · منخفض: التعرفة القياسية عندما يكون جهد الاستدلال منخفضًا
جهد الاستدلال · الحد الأقصى: التعرفة القياسية عندما يكون جهد الاستدلال عند الحد الأقصى
جهد الاستدلال · متوسط: التعرفة القياسية عندما يكون جهد الاستدلال متوسطًا
جهد الاستدلال · xhigh: التعرفة القياسية عندما يكون جهد الاستدلال xhigh

تعرفات Ailoot

الأسعار حسب الإعدادات

طابق كل رسم مع الشروط المعروضة. طبّق تعرفة واحدة لكل مجموعة من الإعدادات البديلة.

الإعدادات	جدول التعرفة	رموز السياق، أكثر من	رموز السياق، حتى القيمة شاملةً	الرسوم
الإعداداتالتعرفات الأساسية للرموز	جدول التعرفةالتعرفة الأساسية	رموز السياق، أكثر من—	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز
الإعداداتالشريحة 1 لطول الطلب	جدول التعرفة—	رموز السياق، أكثر من⁦0⁩	رموز السياق، حتى القيمة شاملةًلا يوجد حد أقصى	الرسوم الإدخال · رموز الإدخال $0.004 / 1K من الرموز الإخراج · رموز الإخراج $0.02 / 1K من الرموز الإدخال · قراءة ذاكرة التخزين المؤقت $0.0004 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت $0.005 / 1K من الرموز الإدخال · الكتابة إلى ذاكرة التخزين المؤقت، 1 ساعة $0.008 / 1K من الرموز

تحجز Ailoot مبلغًا تقديريًا قبل الطلب. وبعد ظهور النتيجة، تُسوّي الرسوم النهائية بناءً على الاستخدام المقاس. وتستخدم تسوية البث سجل الاستخدام النهائي. كيفية عمل حجز المبلغ وتسوية الرسوم →

أمثلة للطلبات

Ailoot Ultra · رسائل Anthropic

{\n  "model": "anthropic/claude-sonnet-5",\n  "max_tokens": 128,\n  "messages": [\n    {\n      "role": "user",\n      "content": "Summarize the incident report."\n    }\n  ],\n  "stream": false\n}

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'anthropic/claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n

import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'anthropic/claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n

استلام النتائج وحفظها

Ailoot Ultra · رسائل Anthropic

JSON أو SSE

الاحتفاظ بكل النتائج المكتملة

احتفظ بكل استجابة كاملة وكل ملف وجزء محتوى تم إرجاعه.

احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.

عند الحاجة إلى التحقق من الاستجابة الأصلية

احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية.

حقول الاستجابة

الحقل	النوع
الحقل`id`	النوعstring
الحقل`model`	النوعstring
الحقل`content[]`	النوعtext\|thinking\|tool_use\|other content block
الحقل`stop_reason`	النوعstring\|null
الحقل`usage`	النوعobject

الأخطاء والخطوات التالية

الاستجابة	الشرط	الخطوة التالية
الاستجابة⁦400⁩ · `invalid_request_error`	الشرطحقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة	الخطوة التاليةصحّح الحقول المحددة قبل طلب إنشاء جديد.

الأسماء البديلة

الأسماء البديلة للنموذج

Ailoot claude-sonnet-5, claude-sonnet, claude-sonnet-latest
Ailoot Ultra claude-sonnet-5, anthropic/claude-sonnet-5

الأسماء البديلة لمسارات الطرائق

/chat/completions

معرّفات النماذج ذات الصلة IDs

anthropic/claude-sonnet-5, claude-sonnet, claude-sonnet-latest, claude-sonnet-5, claude-sonnet-5

", "method_identity": { "effective_request_model_id": "anthropic/claude-sonnet-5", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|anthropic%2Fclaude-sonnet-5", "ordinal": 12, "rawMethod": { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "anthropic/claude-sonnet-5", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "سلسلة نصية messages[].content", "required_material": "نص UTF-8" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "anthropic/claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "anthropic/claude-sonnet-5" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "anthropic/claude-sonnet-5", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "اقرأ مستند UTF-8 الفعلي وضع نصه في الإدخال المحدد أو السلسلة النصية لمحتوى الرسالة." }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "الشريحة 1 لطول الطلب", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "{\n \"model\": \"anthropic/claude-sonnet-5\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'anthropic/claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'anthropic/claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 4, "input": [ "text" ], "label": "رسائل Anthropic", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 20, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "الوضع السريع", "value": "التعرفة القياسية", "when": "عند اختيار الوضع السريع" }, { "label": "الوضع المرن", "value": "التعرفة القياسية", "when": "عند اختيار وضع flex" }, { "label": "أقصى جهد للاستدلال", "value": "التعرفة القياسية", "when": "عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال" }, { "label": "جهد الاستدلال · مرتفع", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال مرتفعًا" }, { "label": "جهد الاستدلال · منخفض", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال منخفضًا" }, { "label": "جهد الاستدلال · الحد الأقصى", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال عند الحد الأقصى" }, { "label": "جهد الاستدلال · متوسط", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال متوسطًا" }, { "label": "جهد الاستدلال · xhigh", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } } ], "model_id": "anthropic/claude-sonnet-5", "nativeProvenance": { "input_facts_canonical_sha256": "3886f6437cd66463896558eb7f84baa04a563e89bb25ac5e380c8806bfd39f77", "input_html_sha256": "ebe29a9dcb5b1ba0488e2016b11daf3e375137aa47c769bb20696a082476ba7f", "private_audit_sha256": "76586269f3965a89ee9b6f3532d440758a11777d840be3675543e4d966423bae", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/ar/claude-sonnet-5/", "description": "Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.", "locale": "ar", "md_url": "https://ailoot.ai/models/ar/claude-sonnet-5/index.md", "title": "Anthropic: Claude Sonnet 5 — Ailoot", "url": "https://ailoot.ai/models/ar/claude-sonnet-5/" }, "practicalHtml": "

مهمة عملية

مثال تقني باللغة الإنجليزية

Diagnose duplicated webhook effects\n\nReview this flow: receive event; charge wallet; save event_id. If saving fails after charging, redelivery charges again. Propose a corrected transaction boundary using a unique event_id record and the wallet update. State the expected behavior for first delivery, duplicate delivery and failure before commit. Return pseudocode and checks; do not claim to execute them.

النتيجة المتوقعة

Transaction pseudocode and a three-case behavior table for first, duplicate and rolled-back delivery.

التحقق من النتيجة

The deduplication record and wallet effect commit together, and a duplicate produces no second debit.

", "practicalText": "مهمة عملية مثال تقني باللغة الإنجليزية Diagnose duplicated webhook effects Review this flow: receive event; charge wallet; save event_id. If saving fails after charging, redelivery charges again. Propose a corrected transaction boundary using a unique event_id record and the wallet update. State the expected behavior for first delivery, duplicate delivery and failure before commit. Return pseudocode and checks; do not claim to execute them. النتيجة المتوقعة Transaction pseudocode and a three-case behavior table for first, duplicate and rolled-back delivery. التحقق من النتيجة The deduplication record and wallet effect commit together, and a duplicate produces no second debit.", "rawModel": { "about": "### وضع خطة وتنفيذها بالتتابع\n\nيركز Claude Sonnet 5 على العمل الوكيلي: يحلل النموذج المهمة ويبني تسلسل إجراءات ويستخدم الوسائل المتاحة لمتابعة التنفيذ. تبرز Anthropic التطوير والتصحيح والعمل المهني بالمعلومات والمهام البحثية. قد تغير نتيجة كل خطوة الخطة اللاحقة في هذا العمل.\n\nالسيناريو الهندسي الأساسي هو إتمام دورة من المشكلة إلى إصلاح متحقق منه. عند وجود بيئة يستطيع النموذج دراسة السبب وكتابة فحص يعيد إنتاج الخطأ وتعديل الكود ورؤية ما إذا حُلّت المشكلة الأصلية. يؤكد المصنّع الفحص الذاتي والحفاظ على الخطة خلال مهمة معقدة. هذا مجال استخدام، وليس ضمانًا لإصلاح أي خطأ بصورة صحيحة.\n\n### وسائل العمل والمعلومات\n\nيستطيع Sonnet 5 استخدام المتصفح والطرفية والأدوات الأخرى التي يوفرها التطبيق. يقدم المتصفح مادة للبحث، وتتيح الطرفية تنفيذ الأوامر وفحص النتيجة التقنية. يحتاج العمل بالملفات وتشغيل الكود والتعديلات الفعلية الوسائل والصلاحيات المناسبة من البيئة.\n\nقد تجمع المهمة المهنية البحث والتحليل وإعداد النص النهائي. يقبل النموذج **النص والصور**، لذا قد يتضمن الطلب مواد موضوعية وعينة بصرية. مخرجاته الخاصة **نص**: يختلف محتوى المستند أو كود الواجهة عن ملف جاهز وتطبيق قابل للتنفيذ، يُنشآن عبر الأدوات.\n\nصيغ الإدخال البصري العادي لدى المصنّع هي JPEG/PNG/GIF/WebP، ويُستخدم الإطار الأول من الصور المتحركة. في التحليل الأصلي: طول الجانب الكبير 2576 بكسل و4784 توكنًا بصريًا؛ وتُصغَّر الصور الكبيرة قبل التحليل. يتحدد دعم الملفات والمعلمات وفق طريقة التطبيق.\n\n### الاستدلال وحجم المهمة\n\nالاستدلال التكيفي مفعّل افتراضيًا. يضبط `effort` عمق العمل: تتوفر `low` و`medium` و`high` و`xhigh` و`max`، والقيمة القياسية `high`. بحسب بيانات Anthropic، تستهدف المستويات الأقل المهام الحساسة للتأخير والمحدودة، والمعالجة العميقة العمل الهندسي الصعب ومتعدد الخطوات. لا يدعم هذا الإصدار extended thinking اليدوي بميزانية منفصلة.\n\nيبلغ السياق **1 مليون توكن**، والحد الأقصى لطول الإجابة في الوضع العادي **128 ألف توكن**. تُستخدم هذه المساحة لمواد المهمة وتنفيذها؛ ويحتاج العمل المعقد بالاستدلال إلى ترك مجال كافٍ للنتيجة النهائية. الحد الموثوق للمعرفة المدمجة هو **يناير 2026**.\n\n### خصائص الإصدار\n\nيستخدم Sonnet 5 طريقة محدثة لتقسيم النص إلى توكنات. يعتمد العدد على المحتوى، لذا لا يعطي الحجم المعتاد للنص بالحروف حجمًا دقيقًا للطلب. كما لا يقبل الإصدار القيم غير القياسية لـ`temperature` و`top_p` و`top_k`؛ ويجب تحديد صيغة الإجابة وطبيعتها في التعليمات.\n\nقد تقيد آليات الحماية المدمجة الطلبات الخطرة في الأمن السيبراني. تحتاج الأبحاث الحديثة مواد جديدة أو بحث التطبيق، ويجب التحقق من تغييرات الكود والاستنتاجات من البيانات وفق نتيجة استخدامها الفعلي.", "alias_of": null, "aliases": [ "claude-sonnet", "claude-sonnet-latest", "claude-sonnet-5" ], "author": "Anthropic", "available": null, "canonical_model": "anthropic/claude-sonnet-5", "capabilities": { "context_length": 1000000, "manufacturer_input": [ "text", "image", "file" ], "manufacturer_output": [ "text" ] }, "card_routes": [ { "label": "Core", "rates": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" } ], "summary": "التسعير الكامل للتكوين في التفاصيل." }, { "label": "Ultra", "rates": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" } ], "summary": "التسعير الكامل للتكوين في التفاصيل." }, { "label": "Ultra", "rates": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" } ], "summary": "التسعير الكامل للتكوين في التفاصيل." } ], "ctx": null, "entity_type": "model", "formats": [ "messages", "responses", "chat" ], "id": "anthropic/claude-sonnet-5", "input": [ "text", "image" ], "kind": "text", "max_out": null, "methods": [ { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content أو كتلة type=text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "system", "required": false, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "limit_scope": "الحد الأقصى الدقيق للنموذج/البطاقة المختارة", "minimum": 1, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop_sequences", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].name", "required": false, "type": "string", "when": "أداة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].input_schema", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.type", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.budget_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_config.effort", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "metadata", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages", "max_tokens" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/messages" }, "operation_modes": [ "messages" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"max_tokens\": 1024, \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"max_tokens\": 1024, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image\",\"source\":{\"type\":\"base64\",\"media_type\":mime,\"data\":b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "import anthropic\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = anthropic.Anthropic(base_url=\"https://api.ailoot.ai\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nmsg = client.messages.create(\n model=\"claude-sonnet-5\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(msg.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import Anthropic from \"@anthropic-ai/sdk\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new Anthropic({ baseURL: \"https://api.ailoot.ai\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: \"claude-sonnet-5\",\n max_tokens: 1024,\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=anthropic.Anthropic(base_url=\"https://api.ailoot.ai\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet-5',max_tokens=1024,messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · complete final message", "language": "python" } ], "family": "anthropic", "fast_multiplier": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "رسائل Anthropic", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/messages", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-5", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every output item and content part, actual function call_id, encrypted reasoning and usage. In streaming retain complete event/item identity.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/responses" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "نص إدخال أو جزء input_text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:input_image,image_url}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "output[]", "type": "message|reasoning|function_call|other item" }, { "description": null, "name": "output[].content[]", "type": "content part" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input", "required": true, "type": "string|input_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "message", "reasoning", "function_call", "function_call_output" ], "enum_known": true, "name": "input[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].content", "required": false, "type": "string|content_part[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].call_id", "required": false, "type": "string", "when": "function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].output", "required": false, "type": "string|content_part[]", "when": "function_call_output" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_output_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.summary", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.verbosity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "include", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "store", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "identity_rule": "معرّف استجابة فعلي فقط من متابعة مدعومة", "name": "previous_response_id", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_key", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "input" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/responses" }, "operation_modes": [ "responses" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"input\": \"\"}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"input\"]=\"Summarize this material and quote supporting source passages.\\n\\n\"+text\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"input\": [{\"role\": \"user\", \"content\": [{\"type\": \"input_text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"input\"][0][\"content\"].append({\"type\":\"input_image\",\"image_url\":\"data:\"+mime+\";base64,\"+b64})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.responses.create(model=\"claude-sonnet-5\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: \"claude-sonnet-5\", input: \"Explain the difference between an observation and a hypothesis in three sentences.\" });\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "Source_stream_contract": "typed parameters.stream=boolean/source_interface/defaultfalse; outputs.format=json or SSE", "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nwith client.responses.stream(model=\"claude-sonnet-5\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\") as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_response()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "creation_argument_parity": "same model/input as existing normal SDK call; SDK sets stream=true", "label": "Python streaming · complete Responses result", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "responses", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "OpenAI Responses", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/responses", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-5", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image_url,image_url:{url,detail}}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/chat/completions" }, "operation_modes": [ "chat_completions" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-5\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image_url\",\"image_url\":{\"url\":\"data:\"+mime+\";base64,\"+b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.chat.completions.create(\n model=\"claude-sonnet-5\",\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n model: \"claude-sonnet-5\",\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet-5',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · retain all events", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "محادثة OpenAI", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/chat/completions", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-5", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "Send the conversation as text messages. Stream must be a boolean; omitted stream defaults to false." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" } ], "operation_modes": [ "conversation" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string", "when": "محادثة نصية" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Text conversation at the exact model ID and method path.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "أرسل معرّف النموذج الدقيق مع messages.", "طول السياق ليس حدًا أقصى للإخراج.", "يمكن لملف نصي تقديم نص حرفي؛ وتحتاج مدخلات الصور/الصوت/كائنات الملفات إلى ربط دقيق." ], "input": { "content_type": "application/json", "control_scope": "محادثة نصية؛ stream قيمة منطقية، وقيمتها الافتراضية false.", "file_material": "مستند UTF-8 الفعلي مُدرج كنص حرفي؛ لا يُستنتَج معرّف ملف", "hosted_operations": false, "material_types": [ "text" ], "messages": "مصفوفة رسائل ببنية role/content", "multimodal_input_binding": null, "optional_controls": [ "stream" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [ "/chat/completions" ], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\":\"claude-sonnet-5\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}],\"stream\":false}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model=\"claude-sonnet-5\", messages=[{\"role\":\"user\",\"content\":\"hello\"}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" } ], "family": "openai", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "chat", "hints": [ "Send exact model ID with messages.", "Context length is not an output cap.", "A text file may supply literal text; image/audio/file-object inputs need exact binding." ], "http": "POST", "in": 4, "input": [ "text" ], "label": "محادثة OpenAI", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [ "/chat/completions" ], "out": 20, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Fast mode", "value": "Standard rate", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Standard rate", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Standard rate", "when": "When maximum reasoning effort uses the default adjustment" }, { "label": "Reasoning effort · high", "value": "Standard rate", "when": "When reasoning effort is high" }, { "label": "Reasoning effort · low", "value": "Standard rate", "when": "When reasoning effort is low" }, { "label": "Reasoning effort · max", "value": "Standard rate", "when": "When reasoning effort is max" }, { "label": "Reasoning effort · medium", "value": "Standard rate", "when": "When reasoning effort is medium" }, { "label": "Reasoning effort · xhigh", "value": "Standard rate", "when": "When reasoning effort is xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "claude-sonnet-5", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "سلسلة نصية messages[].content", "required_material": "نص UTF-8" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "claude-sonnet-5" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "claude-sonnet-5", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "اقرأ مستند UTF-8 الفعلي وضع نصه في الإدخال المحدد أو السلسلة النصية لمحتوى الرسالة." }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "{\n \"model\": \"claude-sonnet-5\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 4, "input": [ "text" ], "label": "رسائل Anthropic", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 20, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Fast mode", "value": "Standard rate", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Standard rate", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Standard rate", "when": "When maximum reasoning effort uses the default adjustment" }, { "label": "Reasoning effort · high", "value": "Standard rate", "when": "When reasoning effort is high" }, { "label": "Reasoning effort · low", "value": "Standard rate", "when": "When reasoning effort is low" }, { "label": "Reasoning effort · max", "value": "Standard rate", "when": "When reasoning effort is max" }, { "label": "Reasoning effort · medium", "value": "Standard rate", "when": "When reasoning effort is medium" }, { "label": "Reasoning effort · xhigh", "value": "Standard rate", "when": "When reasoning effort is xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content أو كتلة type=text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "system", "required": false, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "limit_scope": "الحد الأقصى الدقيق للنموذج/البطاقة المختارة", "minimum": 1, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop_sequences", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].name", "required": false, "type": "string", "when": "أداة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].input_schema", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.type", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.budget_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_config.effort", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "metadata", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages", "max_tokens" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/messages" }, "operation_modes": [ "messages" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"max_tokens\": 1024, \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"max_tokens\": 1024, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image\",\"source\":{\"type\":\"base64\",\"media_type\":mime,\"data\":b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "import anthropic\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = anthropic.Anthropic(base_url=\"https://api.ailoot.ai\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nmsg = client.messages.create(\n model=\"claude-sonnet\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(msg.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import Anthropic from \"@anthropic-ai/sdk\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new Anthropic({ baseURL: \"https://api.ailoot.ai\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: \"claude-sonnet\",\n max_tokens: 1024,\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=anthropic.Anthropic(base_url=\"https://api.ailoot.ai\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet',max_tokens=1024,messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · complete final message", "language": "python" } ], "family": "anthropic", "fast_multiplier": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "رسائل Anthropic", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/messages", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every output item and content part, actual function call_id, encrypted reasoning and usage. In streaming retain complete event/item identity.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/responses" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "نص إدخال أو جزء input_text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:input_image,image_url}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "output[]", "type": "message|reasoning|function_call|other item" }, { "description": null, "name": "output[].content[]", "type": "content part" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input", "required": true, "type": "string|input_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "message", "reasoning", "function_call", "function_call_output" ], "enum_known": true, "name": "input[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].content", "required": false, "type": "string|content_part[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].call_id", "required": false, "type": "string", "when": "function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].output", "required": false, "type": "string|content_part[]", "when": "function_call_output" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_output_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.summary", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.verbosity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "include", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "store", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "identity_rule": "معرّف استجابة فعلي فقط من متابعة مدعومة", "name": "previous_response_id", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_key", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "input" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/responses" }, "operation_modes": [ "responses" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"input\": \"\"}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"input\"]=\"Summarize this material and quote supporting source passages.\\n\\n\"+text\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"input\": [{\"role\": \"user\", \"content\": [{\"type\": \"input_text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"input\"][0][\"content\"].append({\"type\":\"input_image\",\"image_url\":\"data:\"+mime+\";base64,\"+b64})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.responses.create(model=\"claude-sonnet\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: \"claude-sonnet\", input: \"Explain the difference between an observation and a hypothesis in three sentences.\" });\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "Source_stream_contract": "typed parameters.stream=boolean/source_interface/defaultfalse; outputs.format=json or SSE", "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nwith client.responses.stream(model=\"claude-sonnet\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\") as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_response()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "creation_argument_parity": "same model/input as existing normal SDK call; SDK sets stream=true", "label": "Python streaming · complete Responses result", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "responses", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "OpenAI Responses", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/responses", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image_url,image_url:{url,detail}}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/chat/completions" }, "operation_modes": [ "chat_completions" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image_url\",\"image_url\":{\"url\":\"data:\"+mime+\";base64,\"+b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.chat.completions.create(\n model=\"claude-sonnet\",\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n model: \"claude-sonnet\",\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · retain all events", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "محادثة OpenAI", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/chat/completions", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content أو كتلة type=text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image,source:{type:base64,media_type,data}} أو مصدر من النوع type=url" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-latest" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "system", "required": false, "type": "string|content_block[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "limit_scope": "الحد الأقصى الدقيق للنموذج/البطاقة المختارة", "minimum": 1, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop_sequences", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].name", "required": false, "type": "string", "when": "أداة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].input_schema", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.type", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "thinking.budget_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "output_config.effort", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "metadata", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages", "max_tokens" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/messages" }, "operation_modes": [ "messages" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"max_tokens\": 1024, \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"max_tokens\": 1024, \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image\",\"source\":{\"type\":\"base64\",\"media_type\":mime,\"data\":b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "import anthropic\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = anthropic.Anthropic(base_url=\"https://api.ailoot.ai\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nmsg = client.messages.create(\n model=\"claude-sonnet-latest\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(msg.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import Anthropic from \"@anthropic-ai/sdk\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new Anthropic({ baseURL: \"https://api.ailoot.ai\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: \"claude-sonnet-latest\",\n max_tokens: 1024,\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "import anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=anthropic.Anthropic(base_url=\"https://api.ailoot.ai\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.messages.stream(model='claude-sonnet-latest',max_tokens=1024,messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · complete final message", "language": "python" } ], "family": "anthropic", "fast_multiplier": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "رسائل Anthropic", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/messages", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-latest", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every output item and content part, actual function call_id, encrypted reasoning and usage. In streaming retain complete event/item identity.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/responses" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "نص إدخال أو جزء input_text", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:input_image,image_url}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل عنصر إخراج وجزء محتوى وقيمة call_id الفعلية للدالة والاستدلال المشفّر والاستخدام. وفي البث، احتفظ بهوية الحدث/العنصر كاملة.", "family": "text", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "status", "type": "string" }, { "description": null, "name": "output[]", "type": "message|reasoning|function_call|other item" }, { "description": null, "name": "output[].content[]", "type": "content part" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-latest" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input", "required": true, "type": "string|input_item[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "message", "reasoning", "function_call", "function_call_output" ], "enum_known": true, "name": "input[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].content", "required": false, "type": "string|content_part[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].call_id", "required": false, "type": "string", "when": "function_call_output؛ احتفظ بقيمة call_id الفعلية المُرجعة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "input[].output", "required": false, "type": "string|content_part[]", "when": "function_call_output" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_output_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning.summary", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "text.verbosity", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "include", "required": false, "type": "string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "store", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "identity_rule": "معرّف استجابة فعلي فقط من متابعة مدعومة", "name": "previous_response_id", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_key", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "input" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/responses" }, "operation_modes": [ "responses" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"input\": \"\"}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"input\"]=\"Summarize this material and quote supporting source passages.\\n\\n\"+text\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"input\": [{\"role\": \"user\", \"content\": [{\"type\": \"input_text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"input\"][0][\"content\"].append({\"type\":\"input_image\",\"image_url\":\"data:\"+mime+\";base64,\"+b64})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(json.loads(Path(\"result.json\").read_text(encoding=\"utf-8\")))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.responses.create(model=\"claude-sonnet-latest\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.responses.create({ model: \"claude-sonnet-latest\", input: \"Explain the difference between an observation and a hypothesis in three sentences.\" });\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "Source_stream_contract": "typed parameters.stream=boolean/source_interface/defaultfalse; outputs.format=json or SSE", "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nwith client.responses.stream(model=\"claude-sonnet-latest\", input=\"Explain the difference between an observation and a hypothesis in three sentences.\") as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_response()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "creation_argument_parity": "same model/input as existing normal SDK call; SDK sets stream=true", "label": "Python streaming · complete Responses result", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "responses", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "OpenAI Responses", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/responses", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-latest", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "cache_read": 0.2, "cache_write": 2.5, "cache_write_1h": 4, "cache_write_5m": 2.5, "conditional_meter": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" }, { "availability": "Exact model input declaration and selected Source bridge required", "file_id_workflow": "No Ailoot upload/file-ID endpoint is introduced by this feed.", "mode": "text_plus_image", "representation": "{type:image_url,image_url:{url,detail}}" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "claude-sonnet-latest" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [] }, "hints": [ "بُنى الطرق ومعرّفاتها دقيقة؛ قدرة المورد منفصلة عن السماح بالطلب." ], "input": { "content_type": "application/json", "material_types": [ "text", "image" ], "optional_controls": null, "required": [ "model", "messages" ], "text_file_material": "محتوى UTF-8 الفعلي مُدرج كنص؛ وتحتاج معرّفات الملفات/URLs إلى دعم دقيق منفصل" }, "lifecycle": { "mode": "exact retained published method" }, "method": { "http": "POST", "path": "/v1/chat/completions" }, "operation_modes": [ "chat_completions" ], "output": { "family": [ "text" ], "format": "JSON or supported SSE", "multioutputs": "retain every actual response output" } }, "ctx": 1000000, "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"messages\": []}')\nf=Path(os.environ[\"AILOOT_TEXT_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose your actual UTF-8 source material\")\ntext=f.read_text(encoding=\"utf-8\")\nif not text.strip():raise SystemExit(\"Source material must contain text\")\np[\"messages\"]=[{\"role\":\"user\",\"content\":\"Summarize this material and quote supporting source passages.\\n\\n\"+text}]\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use actual text material", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}\"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"claude-sonnet-latest\", \"messages\": [{\"role\": \"user\", \"content\": [{\"type\": \"text\", \"text\": \"Read labels and numbers in this image; flag unreadable text.\"}]}]}')\nimport base64\nf=Path(os.environ[\"AILOOT_IMAGE_FILE\"])\nif not f.is_file():raise SystemExit(\"Choose an actual PNG JPEG or WebP image\")\nraw=f.read_bytes()\nmime=\"image/png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"image/jpeg\" if raw.startswith(b\"\\xff\\xd8\") else \"image/webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else None\nif not mime:raise SystemExit(\"Use PNG JPEG or WebP\")\nb64=base64.b64encode(raw).decode()\np[\"messages\"][0][\"content\"].append({\"type\":\"image_url\",\"image_url\":{\"url\":\"data:\"+mime+\";base64,\"+b64}})\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(\"result.json\").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n", "label": "Use your actual image", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient = OpenAI(base_url=\"https://api.ailoot.ai/v1\", api_key=os.environ[\"AILOOT_API_KEY\"], max_retries=0)\nresp = client.chat.completions.create(\n model=\"claude-sonnet-latest\",\n messages=[{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(resp.to_dict(mode=\"json\"))\n", "label": "Python · retained SDK call", "language": "python" }, { "SDK_retry_proof": { "field": "maxRetries", "scope": "normalclient options; no provider/account/proxy switches", "source_urls": [ "https://raw.githubusercontent.com/openai/openai-node/master/src/client.ts", "https://raw.githubusercontent.com/anthropics/anthropic-sdk-typescript/main/src/client.ts" ], "value": 0 }, "code": "import OpenAI from \"openai\";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error(\"Set AILOOT_API_KEY before making a request\");\nconst client = new OpenAI({ baseURL: \"https://api.ailoot.ai/v1\", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst resp = await client.chat.completions.create({\n model: \"claude-sonnet-latest\",\n messages: [{ role: \"user\", content: \"Explain the difference between an observation and a hypothesis in three sentences.\" }],\n});\nimport { writeFileSync } from \"node:fs\";\n\nfunction saveResult(data, stem = \"result\") {\n writeFileSync(stem + \".json\", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, \"base64\");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? \"png\" : raw[0]===255 && raw[1]===216 ? \"jpg\" : raw.subarray(0,4).toString()===\"RIFF\" && raw.subarray(8,12).toString()===\"WEBP\" ? \"webp\" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log(\"Saved\", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log(\"Content\", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log(\"Choice\", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log(\"Output\", i, JSON.stringify(item));\n if (item.type === \"image_generation_call\" && item.result) saveBlob(item.result, item.output_format || \"bin\", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log(\"Candidate/part\", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"})[mime] || \"bin\";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\n", "label": "Node.js · retained SDK call", "language": "js" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='claude-sonnet-latest',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python streaming · retain all events", "language": "python" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "http": "POST", "img_in": null, "img_out": null, "in": 2, "input": [ "text", "image" ], "label": "محادثة OpenAI", "max_out": 131072, "max_tool_calls": { "web_search_call": 8 }, "out": 10, "output": [ "text" ], "path": "/v1/chat/completions", "pricing_profiles": [ { "dimensions": {}, "label": "Core", "units": [ { "amount": 2, "amount_unit": "usd_per_million_tokens", "key": "in", "label": "Input", "side": "in" }, { "amount": 10, "amount_unit": "usd_per_million_tokens", "key": "out", "label": "Output", "side": "out" }, { "amount": 0.2, "amount_unit": "usd_per_million_tokens", "key": "cache_read", "label": "Cache read", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write", "label": "Cache write", "side": "in" }, { "amount": 2.5, "amount_unit": "usd_per_million_tokens", "key": "cache_write_5m", "label": "Cache write 5m", "side": "in" }, { "amount": 4, "amount_unit": "usd_per_million_tokens", "key": "cache_write_1h", "label": "Cache write 1h", "side": "in" } ] } ], "request_model_id": "claude-sonnet-latest", "route_label": "Core", "status_reads": [], "tiers": [], "tool_prices": { "web_search_call": 0.01 }, "unit": "token", "units": [] }, { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID.", "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "نص UTF8" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "احتفظ بكل اختيار ومحتواه واستدعاءات أدواته واستدلاله. في SSE، جمّع التحديثات بحسب فهرس الاختيار/الأداة، واحتفظ بسبب الإنهاء النهائي والاستخدام.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "anthropic/claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "تُمثَّل هذه الأدوار صراحةً بأنواع التوافق في الشيفرة المصدرية؛ وتظل مجموعة الأدوار الدقيقة خاصة بكل نموذج.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool؛ استخدم المعرّف الفعلي المُرجع" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "أعِد تمرير الاستدلال الفعلي المُرجع حيث يستخدمه هذا النموذج" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": [ "function" ], "enum_known": true, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "أداة دالة مقدّمة" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "text" ], "enum_known": true, "name": "modalities", "required": false, "type": "string[]" }, { "availability": "source_interface", "conditions": "يُرفَض provider.options في مسار Ultra النصي هذا", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "تُرفَض 1h في المواضع الفعلية للتخزين المؤقت للموجّه", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "أرسل معرّف النموذج الدقيق مع messages.", "طول السياق ليس حدًا أقصى للإخراج.", "يمكن لملف نصي تقديم نص حرفي؛ وتحتاج مدخلات الصور/الصوت/كائنات الملفات إلى ربط دقيق." ], "input": { "content_type": "application/json", "control_scope": "خاص بالنموذج؛ أدوات الدوال التي يقدّمها المستخدم تختلف عن الأدوات المستضافة", "file_material": "مستند UTF-8 الفعلي مُدرج كنص حرفي؛ لا يُستنتَج معرّف ملف", "hosted_operations": false, "material_types": [ "text" ], "messages": "مصفوفة رسائل ببنية role/content", "multimodal_input_binding": null, "optional_controls": [ "stream", "temperature", "top_p", "stop", "max_tokens", "max_completion_tokens", "reasoning", "response_format", "tools", "tool_choice" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "الشريحة 1 لطول الطلب", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"anthropic/claude-sonnet-5\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='anthropic/claude-sonnet-5',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='anthropic/claude-sonnet-5',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python SDK streaming · all events", "language": "python" } ], "family": "openai", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "chat", "hints": [ "Send exact model ID with messages.", "Context length is not an output cap.", "A text file may supply literal text; image/audio/file-object inputs need exact binding." ], "http": "POST", "in": 4, "input": [ "text" ], "label": "محادثة OpenAI", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 20, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "الوضع السريع", "value": "التعرفة القياسية", "when": "عند اختيار الوضع السريع" }, { "label": "الوضع المرن", "value": "التعرفة القياسية", "when": "عند اختيار وضع flex" }, { "label": "أقصى جهد للاستدلال", "value": "التعرفة القياسية", "when": "عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال" }, { "label": "جهد الاستدلال · مرتفع", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال مرتفعًا" }, { "label": "جهد الاستدلال · منخفض", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال منخفضًا" }, { "label": "جهد الاستدلال · الحد الأقصى", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال عند الحد الأقصى" }, { "label": "جهد الاستدلال · متوسط", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال متوسطًا" }, { "label": "جهد الاستدلال · xhigh", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "interval_boundary": "min_exclusive_max_inclusive", "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "null_rate_policy": "unknown or inherited; never zero", "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "available": null, "cache_read": 0.4, "cache_write": 5, "cache_write_1h": 8, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "حقول مطلوبة أو تمثيل مادة أو قيمة معلمة غير صحيحة", "http_status": 400, "recovery": "صحّح الحقول المحددة قبل طلب إنشاء جديد.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "anthropic/claude-sonnet-5", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "احتفظ بمعرّفات الطلبات/الاستجابات والترويسات. لا يُقدَّم URL عام لاسترجاع مهمة نصية." }, "material_combinations": [ { "mode": "text", "representation": "سلسلة نصية messages[].content", "required_material": "نص UTF-8" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "احتفظ بكل كتل المحتوى وتوقيعات التفكير ومعرّفات استخدام الأدوات الفعلية. جمّع جميع تحديثات كتل SSE؛ فأول كتلة نصية ليست الإخراج الكامل.", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON أو SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "anthropic/claude-sonnet-5" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "anthropic/claude-sonnet-5" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "anthropic/claude-sonnet-5", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "اقرأ مستند UTF-8 الفعلي وضع نصه في الإدخال المحدد أو السلسلة النصية لمحتوى الرسالة." }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "التعرفات الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "الشريحة 1 لطول الطلب", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "{\n \"model\": \"anthropic/claude-sonnet-5\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'anthropic/claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'anthropic/claude-sonnet-5', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 4, "input": [ "text" ], "label": "رسائل Anthropic", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 20, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "الوضع السريع", "value": "التعرفة القياسية", "when": "عند اختيار الوضع السريع" }, { "label": "الوضع المرن", "value": "التعرفة القياسية", "when": "عند اختيار وضع flex" }, { "label": "أقصى جهد للاستدلال", "value": "التعرفة القياسية", "when": "عندما يُطبَّق الضبط الافتراضي default مع أقصى جهد للاستدلال" }, { "label": "جهد الاستدلال · مرتفع", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال مرتفعًا" }, { "label": "جهد الاستدلال · منخفض", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال منخفضًا" }, { "label": "جهد الاستدلال · الحد الأقصى", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال عند الحد الأقصى" }, { "label": "جهد الاستدلال · متوسط", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال متوسطًا" }, { "label": "جهد الاستدلال · xhigh", "value": "التعرفة القياسية", "when": "عندما يكون جهد الاستدلال xhigh" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "max": 1, "medium": 1, "xhigh": 1 }, "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.4, "cache_read_multiplier": null, "cache_write": 5, "cache_write_1h": 8, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 20, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "model_aliases": [ { "canonical_model_id": "anthropic/claude-sonnet-5", "request_model_id": "claude-sonnet-5", "route_label": "Core" }, { "canonical_model_id": "anthropic/claude-sonnet-5", "request_model_id": "claude-sonnet-5", "route_label": "Ultra" }, { "canonical_model_id": "anthropic/claude-sonnet-5", "request_model_id": "claude-sonnet", "route_label": "Core" }, { "canonical_model_id": "anthropic/claude-sonnet-5", "request_model_id": "claude-sonnet-latest", "route_label": "Core" }, { "canonical_model_id": "anthropic/claude-sonnet-5", "request_model_id": "anthropic/claude-sonnet-5", "route_label": "Ultra" } ], "name": "Anthropic: Claude Sonnet 5", "price": { "in": 4, "in_label": null, "out": 20, "out_label": null, "scope_label": "Token rates", "sort_in": 4, "sort_out": 20, "varies": true }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "OpenAI Chat · الأسعار الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "OpenAI Chat · الشريحة 1 حسب طول الطلب", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "regime": "base" }, "label": "Anthropic Messages · الأسعار الأساسية للرموز", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Anthropic Messages · الشريحة 1 حسب طول الطلب", "units": [ { "amount": "0.004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00002", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": "0.008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": "0.000008", "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "public_id": "anthropic/claude-sonnet-5", "short": "صُمم Claude Sonnet 5 للتخطيط والعمل المتتابع على الكود والأبحاث والمواد المهنية. يدعم الاستدلال التكيفي وأدوات التطبيق." }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 }, { "contract_json_pointer": "/methods/1/rawMethod/contract", "html_json_pointer": "/methods/1/html", "method_ordinal": 1 }, { "contract_json_pointer": "/methods/2/rawMethod/contract", "html_json_pointer": "/methods/2/html", "method_ordinal": 2 }, { "contract_json_pointer": "/methods/3/rawMethod/contract", "html_json_pointer": "/methods/3/html", "method_ordinal": 3 }, { "contract_json_pointer": "/methods/4/rawMethod/contract", "html_json_pointer": "/methods/4/html", "method_ordinal": 4 }, { "contract_json_pointer": "/methods/5/rawMethod/contract", "html_json_pointer": "/methods/5/html", "method_ordinal": 5 }, { "contract_json_pointer": "/methods/6/rawMethod/contract", "html_json_pointer": "/methods/6/html", "method_ordinal": 6 }, { "contract_json_pointer": "/methods/7/rawMethod/contract", "html_json_pointer": "/methods/7/html", "method_ordinal": 7 }, { "contract_json_pointer": "/methods/8/rawMethod/contract", "html_json_pointer": "/methods/8/html", "method_ordinal": 8 }, { "contract_json_pointer": "/methods/9/rawMethod/contract", "html_json_pointer": "/methods/9/html", "method_ordinal": 9 }, { "contract_json_pointer": "/methods/10/rawMethod/contract", "html_json_pointer": "/methods/10/html", "method_ordinal": 10 }, { "contract_json_pointer": "/methods/11/rawMethod/contract", "html_json_pointer": "/methods/11/html", "method_ordinal": 11 }, { "contract_json_pointer": "/methods/12/rawMethod/contract", "html_json_pointer": "/methods/12/html", "method_ordinal": 12 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod", "/methods/1/rawMethod", "/methods/2/rawMethod", "/methods/3/rawMethod", "/methods/4/rawMethod", "/methods/5/rawMethod", "/methods/6/rawMethod", "/methods/7/rawMethod", "/methods/8/rawMethod", "/methods/9/rawMethod", "/methods/10/rawMethod", "/methods/11/rawMethod", "/methods/12/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "Claude Sonnet 5 للتحليل النصي والمرئي المتواصل؛ تدرج طرائق محادثة Core سياق 1,000,000 رمز وسقف إخراج 131,072 رمزًا.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "5217b791414c27f8257850e47539ef5ab7d7882ae081c87c12dea6cb77769b1f", "renderer_sha256": "081ee0fd5b6b1b60564b02c52d62547e01e922c8c0a16e91a0d055073e76a10e" }, "sourceRevision": "7f071be7f43ef553348594cfd9340c0a592b06d372b99425ada19628aa1f0539" }