Source: https://ailoot.ai/models/ms/claude-opus-4-6/ Canonical: https://ailoot.ai/models/ms/claude-opus-4-6/ Language: ms # claude-opus-4-6 [Markdown](https://ailoot.ai/models/ms/claude-opus-4-6/index.md) · [JSON](https://ailoot.ai/models/ms/claude-opus-4-6/facts.json) ## [claude-opus-4-6](https://ailoot.ai/models/ms/claude-opus-4-6/) Claude Opus 4.6 direka untuk pangkalan kod besar, penyahpepijatan, penyelidikan dan analisis dokumen panjang. Menyokong penaakulan adaptif dan konteks sehingga 1 juta token. - [**Ailoot · Anthropic Messages** `POST /v1/messages` `claude-opus-4-6`](https://ailoot.ai/models/ms/claude-opus-4-6/#method-0) - [**Ailoot · OpenAI Responses** `POST /v1/responses` `claude-opus-4-6`](https://ailoot.ai/models/ms/claude-opus-4-6/#method-1) - [**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `claude-opus-4-6`](https://ailoot.ai/models/ms/claude-opus-4-6/#method-2) Tentang model Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih. #### Tugasan besar dan hubungan antara bahagiannya Claude Opus 4.6 menumpukan kerja yang mendapat manfaat daripada pengekalan banyak bahan dalam satu konteks dan penaakulan selepas bahan itu dibaca. Anthropic menekankan pembangunan dalam pangkalan kod besar, pemeriksaan kod, penyahpepijatan, analisis kewangan dan penyelidikan. Model boleh mencari butiran penting, menghubungkan maklumat daripada bahagian bahan yang berbeza dan menggunakannya untuk menyelesaikan tugasan secara berurutan. Dalam pembangunan, ini bermaksud perancangan, kajian sistem yang belum dikenali dan pencarian ralat dalam perubahan. Dalam analisis profesional, ini merangkumi pemprosesan dokumen dan penyediaan kandungan hamparan, laporan atau pembentangan. Bagi senario sebegini, model perlu diberikan tugasan itu sendiri dan bahan yang menjadi asas kesimpulan, bukan sekadar nama topik secara umum. #### Penaakulan adaptif Model menyokong mod adaptif: berdasarkan kandungan arahan, model menentukan bila analisis tambahan berguna. Parameter `effort` menentukan tahap usaha; Opus 4.6 menyediakan `low`, `medium`, `high` dan `max`, dengan `high` sebagai nilai standard. Menurut Anthropic, analisis mendalam boleh memanjangkan masa respons untuk tugasan mudah, jadi tahap yang dipilih perlu disesuaikan dengan kerumitannya. extended thinking lama dengan bajet manual masih disokong, tetapi ditandakan sebagai semakin lapuk. Terdapat perbezaan mod yang penting bagi versi ini: penaakulan antara panggilan alat tersedia dalam mod adaptif, manakala Opus 4.6 tidak melakukannya dalam mod manual. Apabila alat disambungkan, analisis adaptif membantu menggunakan hasil satu tindakan untuk memilih tindakan seterusnya. #### Konteks untuk kerja berpanjangan Spesifikasi Anthropic semasa menetapkan **1 juta token konteks** dan sehingga **128 ribu token respons dalam mod biasa**. **Teks dan imej** diterima sebagai input, manakala respons kekal berupa teks. Batas pengetahuan terbina dalam yang boleh dipercayai ialah **Mei 2025**. Format input visual biasa pengeluar ialah JPEG/PNG/GIF/WebP, dengan bingkai pertama digunakan bagi animasi. Untuk analisis natif: sisi panjang ialah 1568 piksel dan jumlah token visual ialah 1568; imej besar dikecilkan sebelum analisis. Sokongan fail dan parameter bergantung pada kaedah aplikasi. Bagi perbualan panjang dan tugasan ejen, pengeluar menerangkan pemampatan konteks lama: bahagian kerja terdahulu digantikan dengan ringkasan apabila menghampiri ambang yang ditetapkan. Keupayaan ini ditandakan sebagai eksperimen dan memerlukan sokongan aplikasi; saiz konteks sahaja tidak menyediakan memori tanpa had. #### Alat dan pemeriksaan hasil Opus 4.6 direka untuk kerja berbilang langkah dengan carian, kod dan alat lain yang tersedia. Persekitaran aplikasi mesti menyediakan pembacaan bahan, pelaksanaan arahan atau penghasilan fail. Tindakan produksi, kawalan antara muka dan penciptaan pembentangan siap bergantung pada kemudahan ini; model teks tidak memperolehnya secara automatik. Anthropic menerangkan pemeriksaan keselamatan dan langkah perlindungan bagi tugasan keselamatan siber yang berpotensi berbahaya secara berasingan. Untuk pembangunan biasa, model boleh membantu mencari dan membetulkan kelemahan, tetapi sifat permintaan mempengaruhi kemungkinan respons diberikan. Kesimpulan daripada set bahan besar dan perubahan yang dicadangkan perlu diperiksa berdasarkan data itu sendiri dan hasil pelaksanaan. Tugas praktikal ### Tugas praktikal Contoh teknikal dalam bahasa Inggeris ``` Trace a cache invalidation defect Review this change using the supplied contract. Contract: changing an account's role must affect the next permission check. Current flow: update_role writes the database; can_edit reads a role cache with a 15-minute TTL. Propose the smallest correction, explain the failure window, and give regression tests for a demotion and an unrelated account. Do not assume any framework. ``` #### Hasil yang dijangka ``` A code-review note containing cause, a targeted invalidation strategy and two regression-test specifications. ``` #### Semak hasil ``` A demoted account cannot retain edit permission until the cache expires, while another account's entry remains valid. ``` **Ailoot · Anthropic Messages** `POST /v1/messages` `claude-opus-4-6` [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=messages) Anthropic /`claude-opus-4-6` ### Pengenalan Claude Opus 4.6 direka untuk pangkalan kod besar, penyahpepijatan, penyelidikan dan analisis dokumen panjang. Menyokong penaakulan adaptif dan konteks sehingga 1 juta token. Input yang diterima Teks · Imej Hasil Teks ### Tersedia di Ailoot · input & kaedah **Ailoot · Anthropic Messages** `POST /v1/messages` Input `text`, `image` Output `text` Konteks 1,000,000 tokens Output maksimum 131,072 tokens Format output json atau SSE | Medan | Jenis | Keperluan | Nilai & had | Lalai | | --- | --- | --- | --- | --- | | Medan`model` | Jenis`string` | KeperluanDiperlukan | Nilai & had claude-opus-4-6 | Lalai— | | Medan`messages` | Jenis`message[]` | KeperluanDiperlukan | Nilai & had Item minimum: 1 | Lalai— | | Medan`messages[].role` | Jenis`string` | KeperluanDiperlukan | Nilai & had user, assistant | Lalai— | | Medan`messages[].content` | Jenis`string\|content_block[]` | KeperluanDiperlukan | Nilai & had | Lalai— | | Medan`system` | Jenis`string\|content_block[]` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`max_tokens` | Jenis`integer` | KeperluanDiperlukan | Nilai & had Minimum: 1 Had terpakai pada: had maksimum tepat bagi model/kad yang dipilih | Lalai— | | Medan`stream` | Jenis`boolean` | KeperluanPilihan | Nilai & had | Lalaifalse | | Medan`temperature` | Jenis`number` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`top_p` | Jenis`number` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`stop_sequences` | Jenis`string[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tools` | Jenis`tool[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tools[].name` | Jenis`string` | KeperluanPilihan | Nilai & had Terpakai apabila: alat dibekalkan | Lalai— | | Medan`tools[].description` | Jenis`string` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`tools[].input_schema` | Jenis`JSON_schema` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`tool_choice` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`thinking.type` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`thinking.budget_tokens` | Jenis`integer` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`output_config.effort` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`metadata` | Jenis`object` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`cache_control` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | Gabungan bahan input **Teks** · Teks UTF8 `messages[].content atau blok type=text` **Teks + imej** `{type:image,source:{type:base64,media_type,data}} atau sumber dengan type=url` Parameter kaedah dan kitar hayat | Parameter | Kontrak | | --- | --- | | Parameter`material_types` | Kontraktext, image | | Parameter`required` | Kontrakmodel, messages, max\_tokens | | Parameter`optional_controls` | Kontraknull | | Parameter`content_type` | Kontrakapplication/json | | Parameter`text_file_material` | Kontrakkandungan UTF-8 sebenar dimasukkan sebagai teks; ID fail atau alamat URL (URLs) memerlukan sokongan tepat yang berasingan | Kitar hayat: `exact retained published method` Struktur kaedah dan ID adalah tepat; keupayaan pembekal berasingan daripada penerimaan permintaan. ### Pelan harga #### Kadar kaedah Ailoot Input USD 0.005 */ 1K* Output USD 0.025 */ 1K* Bacaan cache USD 0.0005 */ 1K* Penulisan cache USD 0.00625 */ 1K* Penulisan cache, 5 minit USD 0.00625 */ 1K tokens* Penulisan cache, 1 jam USD 0.01 */ 1K tokens* web\_search\_call USD 0.01 *bagi setiap panggilan* Panggilan maksimum web\_search\_call 8 Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. [Cara rizab dan penyelesaian caj berfungsi →](https://ailoot.ai/docs/ms/billing/reserve/) #### Butiran tarif rujukan Jadual rujukan peringkat model tidak mengubah pemilihan kaedah, sebut harga atau caj. Caj aktif menggunakan kadar kaedah Ailoot yang dipilih. claude-opus-4-6 #### Harga mengikut konfigurasi | Konfigurasi | Syarat pengebilan | Caj | | --- | --- | --- | | Konfigurasiclaude-opus-4-6 · Konfigurasi lalai | Syarat pengebilanKonfigurasi lalai | Caj Input · Input **USD 0.02** / 1K token Output · Output **USD 0.075** / 1K token Input · Penulisan cache **USD 0.025** / 1K token Input · Bacaan cache **USD 0.002** / 1K token | claude-opus-4-6 #### Harga mengikut konfigurasi | Konfigurasi | Syarat pengebilan | Caj | | --- | --- | --- | | Konfigurasiclaude-opus-4-6 · Konfigurasi lalai | Syarat pengebilanKonfigurasi lalai | Caj Input · Input **USD 0.01** / 1K token Output · Output **USD 0.05** / 1K token | ### Contoh permintaan #### Ailoot · Anthropic Messages Contoh teksInput, imejPython SDKNode.js SDKPenstriman Python ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "claude-opus-4-6", "max_tokens": 1024, "messages": []}') f=Path(os.environ["AILOOT_TEXT_FILE"]) if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material") text=f.read_text(encoding="utf-8") if not text.strip():raise SystemExit("Source material must contain text") p["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\n\n"+text}] Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \ -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2)) PY_RESULT ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}" export AILOOT_IMAGE_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "claude-opus-4-6", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}') import base64 f=Path(os.environ["AILOOT_IMAGE_FILE"]) if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image") raw=f.read_bytes() mime="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 if not mime:raise SystemExit("Use PNG JPEG or WebP") b64=base64.b64encode(raw).decode() p["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}}) Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \ -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2)) PY_RESULT ``` ```python import anthropic import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0) msg = client.messages.create( model="claude-opus-4-6", max_tokens=1024, messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}], ) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(msg.to_dict(mode="json")) ``` ```js import Anthropic from "@anthropic-ai/sdk"; if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request"); const client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 }); const msg = await client.messages.create({ model: "claude-opus-4-6", max_tokens: 1024, messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }], }); import { writeFileSync } from "node:fs"; function saveResult(data, stem = "result") { writeFileSync(stem + ".json", JSON.stringify(data, null, 2)); console.log(JSON.stringify(data, null, 2)); const saveBlob = (encoded, suffix, label) => { const raw = Buffer.from(encoded, "base64"); 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; const file = `${stem}-${label}.${ext}`; writeFileSync(file, raw); console.log("Saved", file); }; for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block)); for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {})); for (const [i, item] of (data.output || []).entries()) { console.log("Output", i, JSON.stringify(item)); if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`); } for (const [ci, candidate] of (data.candidates || []).entries()) { for (const [pi, part] of (candidate.content?.parts || []).entries()) { console.log("Candidate/part", ci, pi, JSON.stringify(part)); const blob = part.inlineData || part.inline_data; if (blob?.data) { const mime = blob.mimeType || blob.mime_type; const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin"; saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`); } } } } saveResult(msg); ``` ```python import anthropic,os from pathlib import Path if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) with client.messages.stream(model='claude-opus-4-6',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream: with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for event in stream: payload=event.to_dict(mode="json") log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() print(json.dumps(payload,ensure_ascii=False)) final=stream.get_final_message() save_result(final.to_dict(mode="json"),"stream-result") ``` ### Terima dan simpan hasil #### Ailoot · Anthropic Messages json atau SSE ##### Simpan semua hasil yang selesai Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan. Kekalkan semua blok kandungan, tandatangan penaakulan dan ID penggunaan alat sebenar. Gabungkan semua delta blok SSE; blok teks pertama bukan keseluruhan output. ##### Jika respons asal perlu disemak Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan. Medan respons | Medan | Jenis | | --- | --- | | Medan`id` | Jenisstring | | Medan`model` | Jenisstring | | Medan`content[]` | Jenistext\|thinking\|tool\_use\|other content block | | Medan`stop_reason` | Jenisstring\|null | | Medan`usage` | Jenisobject | Ralat dan langkah seterusnya | Respons | Syarat | Langkah seterusnya | | --- | --- | --- | | Respons400 · `invalid_request_error` | SyaratMedan wajib, perwakilan bahan atau nilai parameter tidak sah | Langkah seterusnyaBetulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu. | ### Alias #### Alias model **Ailoot** [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=messages) #### Alias laluan kaedah Gunakan laluan kaedah yang dipaparkan di atas. #### ID pemanggil berkaitan [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=messages) **Ailoot · OpenAI Responses** `POST /v1/responses` `claude-opus-4-6` [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=responses) Anthropic /`claude-opus-4-6` ### Pengenalan Claude Opus 4.6 direka untuk pangkalan kod besar, penyahpepijatan, penyelidikan dan analisis dokumen panjang. Menyokong penaakulan adaptif dan konteks sehingga 1 juta token. Input yang diterima Teks · Imej Hasil Teks ### Tersedia di Ailoot · input & kaedah **Ailoot · OpenAI Responses** `POST /v1/responses` Input `text`, `image` Output `text` Konteks 1,000,000 tokens Output maksimum 131,072 tokens Format output json atau SSE | Medan | Jenis | Keperluan | Nilai & had | Lalai | | --- | --- | --- | --- | --- | | Medan`model` | Jenis`string` | KeperluanDiperlukan | Nilai & had claude-opus-4-6 | Lalai— | | Medan`input` | Jenis`string\|input_item[]` | KeperluanDiperlukan | Nilai & had | Lalai— | | Medan`instructions` | Jenis`string` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`input[].type` | Jenis`string` | KeperluanPilihan | Nilai & had message, reasoning, function\_call, function\_call\_output | Lalai— | | Medan`input[].content` | Jenis`string\|content_part[]` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`input[].call_id` | Jenis`string` | KeperluanPilihan | Nilai & had Terpakai apabila: function\_call\_output; kekalkan call\_id sebenar yang dipulangkan | Lalai— | | Medan`input[].output` | Jenis`string\|content_part[]` | KeperluanPilihan | Nilai & had Terpakai apabila: function\_call\_output | Lalai— | | Medan`max_output_tokens` | Jenis`integer` | KeperluanPilihan | Nilai & had Minimum: 1 Bergantung pada model | Lalai— | | Medan`stream` | Jenis`boolean` | KeperluanPilihan | Nilai & had | Lalaifalse | | Medan`temperature` | Jenis`number` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`top_p` | Jenis`number` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tools` | Jenis`tool[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tool_choice` | Jenis`string\|object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`parallel_tool_calls` | Jenis`boolean` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`reasoning.effort` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`reasoning.summary` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`text.format` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`text.verbosity` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`include` | Jenis`string[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`store` | Jenis`boolean` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`previous_response_id` | Jenis`string` | KeperluanPilihan | Nilai & had Keperluan ID: Hanya ID respons sebenar daripada penerusan yang disokong Bergantung pada model | Lalai— | | Medan`service_tier` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`prompt_cache_key` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`prompt_cache_options` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | Gabungan bahan input **Teks** · Teks UTF8 `Teks input atau bahagian input_text` **Teks + imej** `{type:input_image,image_url}` Parameter kaedah dan kitar hayat | Parameter | Kontrak | | --- | --- | | Parameter`material_types` | Kontraktext, image | | Parameter`required` | Kontrakmodel, input | | Parameter`optional_controls` | Kontraknull | | Parameter`content_type` | Kontrakapplication/json | | Parameter`text_file_material` | Kontrakkandungan UTF-8 sebenar dimasukkan sebagai teks; ID fail atau alamat URL (URLs) memerlukan sokongan tepat yang berasingan | Kitar hayat: `exact retained published method` Struktur kaedah dan ID adalah tepat; keupayaan pembekal berasingan daripada penerimaan permintaan. ### Pelan harga #### Kadar kaedah Ailoot Input USD 0.005 */ 1K* Output USD 0.025 */ 1K* Bacaan cache USD 0.0005 */ 1K* Penulisan cache USD 0.00625 */ 1K* Penulisan cache, 5 minit USD 0.00625 */ 1K tokens* Penulisan cache, 1 jam USD 0.01 */ 1K tokens* web\_search\_call USD 0.01 *bagi setiap panggilan* Panggilan maksimum web\_search\_call 8 Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. [Cara rizab dan penyelesaian caj berfungsi →](https://ailoot.ai/docs/ms/billing/reserve/) #### Butiran tarif rujukan Jadual rujukan peringkat model tidak mengubah pemilihan kaedah, sebut harga atau caj. Caj aktif menggunakan kadar kaedah Ailoot yang dipilih. claude-opus-4-6 #### Harga mengikut konfigurasi | Konfigurasi | Syarat pengebilan | Caj | | --- | --- | --- | | Konfigurasiclaude-opus-4-6 · Konfigurasi lalai | Syarat pengebilanKonfigurasi lalai | Caj Input · Input **USD 0.02** / 1K token Output · Output **USD 0.075** / 1K token Input · Penulisan cache **USD 0.025** / 1K token Input · Bacaan cache **USD 0.002** / 1K token | claude-opus-4-6 #### Harga mengikut konfigurasi | Konfigurasi | Syarat pengebilan | Caj | | --- | --- | --- | | Konfigurasiclaude-opus-4-6 · Konfigurasi lalai | Syarat pengebilanKonfigurasi lalai | Caj Input · Input **USD 0.01** / 1K token Output · Output **USD 0.05** / 1K token | ### Contoh permintaan #### Ailoot · OpenAI Responses Contoh teksInput, imejPython SDKNode.js SDKPenstriman Python ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "claude-opus-4-6", "input": ""}') f=Path(os.environ["AILOOT_TEXT_FILE"]) if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material") text=f.read_text(encoding="utf-8") if not text.strip():raise SystemExit("Source material must contain text") p["input"]="Summarize this material and quote supporting source passages.\n\n"+text Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(json.loads(Path("result.json").read_text(encoding="utf-8"))) PY_RESULT ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}" export AILOOT_IMAGE_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "claude-opus-4-6", "input": [{"role": "user", "content": [{"type": "input_text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}') import base64 f=Path(os.environ["AILOOT_IMAGE_FILE"]) if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image") raw=f.read_bytes() mime="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 if not mime:raise SystemExit("Use PNG JPEG or WebP") b64=base64.b64encode(raw).decode() p["input"][0]["content"].append({"type":"input_image","image_url":"data:"+mime+";base64,"+b64}) Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/responses \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(json.loads(Path("result.json").read_text(encoding="utf-8"))) PY_RESULT ``` ```python from openai import OpenAI import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0) resp = client.responses.create(model="claude-opus-4-6", input="Explain the difference between an observation and a hypothesis in three sentences.") import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(resp.to_dict(mode="json")) ``` ```js import OpenAI from "openai"; if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request"); const client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 }); const resp = await client.responses.create({ model: "claude-opus-4-6", input: "Explain the difference between an observation and a hypothesis in three sentences." }); import { writeFileSync } from "node:fs"; function saveResult(data, stem = "result") { writeFileSync(stem + ".json", JSON.stringify(data, null, 2)); console.log(JSON.stringify(data, null, 2)); const saveBlob = (encoded, suffix, label) => { const raw = Buffer.from(encoded, "base64"); 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; const file = `${stem}-${label}.${ext}`; writeFileSync(file, raw); console.log("Saved", file); }; for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block)); for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {})); for (const [i, item] of (data.output || []).entries()) { console.log("Output", i, JSON.stringify(item)); if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`); } for (const [ci, candidate] of (data.candidates || []).entries()) { for (const [pi, part] of (candidate.content?.parts || []).entries()) { console.log("Candidate/part", ci, pi, JSON.stringify(part)); const blob = part.inlineData || part.inline_data; if (blob?.data) { const mime = blob.mimeType || blob.mime_type; const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin"; saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`); } } } } saveResult(resp); ``` ```python from openai import OpenAI import os from pathlib import Path import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) with client.responses.stream(model="claude-opus-4-6", input="Explain the difference between an observation and a hypothesis in three sentences.") as stream: with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for event in stream: payload=event.to_dict(mode="json") log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() print(json.dumps(payload,ensure_ascii=False)) final=stream.get_final_response() save_result(final.to_dict(mode="json"),"stream-result") ``` ### Terima dan simpan hasil #### Ailoot · OpenAI Responses json atau SSE ##### Simpan semua hasil yang selesai Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan. Kekalkan setiap item output dan bahagian kandungan, call\_id fungsi sebenar, penaakulan disulitkan serta data penggunaan. Semasa penstriman, kekalkan identiti peristiwa/item yang lengkap. ##### Jika respons asal perlu disemak Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan. Medan respons | Medan | Jenis | | --- | --- | | Medan`id` | Jenisstring | | Medan`status` | Jenisstring | | Medan`output[]` | Jenismessage\|reasoning\|function\_call\|other item | | Medan`output[].content[]` | Jeniscontent part | | Medan`usage` | Jenisobject | Ralat dan langkah seterusnya | Respons | Syarat | Langkah seterusnya | | --- | --- | --- | | Respons400 · `invalid_request_error` | SyaratMedan wajib, perwakilan bahan atau nilai parameter tidak sah | Langkah seterusnyaBetulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu. | ### Alias #### Alias model **Ailoot** [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=responses) #### Alias laluan kaedah Gunakan laluan kaedah yang dipaparkan di atas. #### ID pemanggil berkaitan [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=responses) **Ailoot · OpenAI Chat** `POST /v1/chat/completions` `claude-opus-4-6` [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=chat) Anthropic /`claude-opus-4-6` ### Pengenalan Claude Opus 4.6 direka untuk pangkalan kod besar, penyahpepijatan, penyelidikan dan analisis dokumen panjang. Menyokong penaakulan adaptif dan konteks sehingga 1 juta token. Input yang diterima Teks · Imej Hasil Teks ### Tersedia di Ailoot · input & kaedah **Ailoot · OpenAI Chat** `POST /v1/chat/completions` Input `text`, `image` Output `text` Konteks 1,000,000 tokens Output maksimum 131,072 tokens Format output json atau SSE | Medan | Jenis | Keperluan | Nilai & had | Lalai | | --- | --- | --- | --- | --- | | Medan`model` | Jenis`string` | KeperluanDiperlukan | Nilai & had claude-opus-4-6 | Lalai— | | Medan`messages` | Jenis`message[]` | KeperluanDiperlukan | Nilai & had Item minimum: 1 | Lalai— | | Medan`messages[].role` | Jenis`string` | KeperluanDiperlukan | Nilai & had Contoh: system, user, assistant, tool, function Syarat: Peranan ini diwakili secara eksplisit oleh jenis keserasian dalam kod sumber; set peranan model yang tepat kekal khusus untuk setiap model. Bergantung pada model | Lalai— | | Medan`messages[].content` | Jenis`string\|content_part[]\|null` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`messages[].tool_calls` | Jenis`tool_call[]` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`messages[].tool_call_id` | Jenis`string` | KeperluanPilihan | Nilai & had Terpakai apabila: role=tool; gunakan ID sebenar yang dipulangkan | Lalai— | | Medan`messages[].name` | Jenis`string` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`messages[].reasoning_content` | Jenis`string` | KeperluanPilihan | Nilai & had Terpakai apabila: Hantar semula penaakulan sebenar yang dipulangkan apabila model ini menggunakannya | Lalai— | | Medan`messages[].reasoning_details` | Jenis`object\|array` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`max_tokens` | Jenis`integer` | KeperluanPilihan | Nilai & had Minimum: 1 Bergantung pada model | Lalai— | | Medan`max_completion_tokens` | Jenis`integer` | KeperluanPilihan | Nilai & had Minimum: 1 Bergantung pada model | Lalai— | | Medan`stream` | Jenis`boolean` | KeperluanPilihan | Nilai & had | Lalaifalse | | Medan`stream_options.include_usage` | Jenis`boolean` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`temperature` | Jenis`number` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`top_p` | Jenis`number` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`stop` | Jenis`string\|string[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tools` | Jenis`function_tool[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tools[].type` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`tools[].function.name` | Jenis`string` | KeperluanDiperlukan | Nilai & had Terpakai apabila: alat fungsi dibekalkan | Lalai— | | Medan`tools[].function.description` | Jenis`string` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`tools[].function.parameters` | Jenis`JSON_schema` | KeperluanPilihan | Nilai & had | Lalai— | | Medan`tool_choice` | Jenis`string\|object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`parallel_tool_calls` | Jenis`boolean` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`response_format` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`reasoning_effort` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`reasoning` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`service_tier` | Jenis`string` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`instructions` | Jenis`string` | KeperluanPilihan | Nilai & had Medan keserasian | Lalai— | | Medan`functions` | Jenis`function[]` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`function_call` | Jenis`string\|object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | | Medan`prompt_cache_options` | Jenis`object` | KeperluanPilihan | Nilai & had Bergantung pada model | Lalai— | Gabungan bahan input **Teks** · Teks UTF8 `messages[].content` **Teks + imej** `{type:image_url,image_url:{url,detail}}` Parameter kaedah dan kitar hayat | Parameter | Kontrak | | --- | --- | | Parameter`material_types` | Kontraktext, image | | Parameter`required` | Kontrakmodel, messages | | Parameter`optional_controls` | Kontraknull | | Parameter`content_type` | Kontrakapplication/json | | Parameter`text_file_material` | Kontrakkandungan UTF-8 sebenar dimasukkan sebagai teks; ID fail atau alamat URL (URLs) memerlukan sokongan tepat yang berasingan | Kitar hayat: `exact retained published method` Struktur kaedah dan ID adalah tepat; keupayaan pembekal berasingan daripada penerimaan permintaan. ### Pelan harga #### Kadar kaedah Ailoot Input USD 0.005 */ 1K* Output USD 0.025 */ 1K* Bacaan cache USD 0.0005 */ 1K* Penulisan cache USD 0.00625 */ 1K* Penulisan cache, 5 minit USD 0.00625 */ 1K tokens* Penulisan cache, 1 jam USD 0.01 */ 1K tokens* web\_search\_call USD 0.01 *bagi setiap panggilan* Panggilan maksimum web\_search\_call 8 Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. [Cara rizab dan penyelesaian caj berfungsi →](https://ailoot.ai/docs/ms/billing/reserve/) #### Butiran tarif rujukan Jadual rujukan peringkat model tidak mengubah pemilihan kaedah, sebut harga atau caj. Caj aktif menggunakan kadar kaedah Ailoot yang dipilih. claude-opus-4-6 #### Harga mengikut konfigurasi | Konfigurasi | Syarat pengebilan | Caj | | --- | --- | --- | | Konfigurasiclaude-opus-4-6 · Konfigurasi lalai | Syarat pengebilanKonfigurasi lalai | Caj Input · Input **USD 0.02** / 1K token Output · Output **USD 0.075** / 1K token Input · Penulisan cache **USD 0.025** / 1K token Input · Bacaan cache **USD 0.002** / 1K token | claude-opus-4-6 #### Harga mengikut konfigurasi | Konfigurasi | Syarat pengebilan | Caj | | --- | --- | --- | | Konfigurasiclaude-opus-4-6 · Konfigurasi lalai | Syarat pengebilanKonfigurasi lalai | Caj Input · Input **USD 0.01** / 1K token Output · Output **USD 0.05** / 1K token | ### Contoh permintaan #### Ailoot · OpenAI Chat Contoh teksInput, imejPython SDKNode.js SDKPenstriman Python ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}" export AILOOT_TEXT_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "claude-opus-4-6", "messages": []}') f=Path(os.environ["AILOOT_TEXT_FILE"]) if not f.is_file():raise SystemExit("Choose your actual UTF-8 source material") text=f.read_text(encoding="utf-8") if not text.strip():raise SystemExit("Source material must contain text") p["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\n\n"+text}] Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2)) PY_RESULT ``` ```bash set -eu : "${AILOOT_API_KEY:?Set your Ailoot API key}" : "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}" export AILOOT_IMAGE_FILE python3 - <<'PY_REQUEST' import json,os from pathlib import Path p=json.loads('{"model": "claude-opus-4-6", "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}') import base64 f=Path(os.environ["AILOOT_IMAGE_FILE"]) if not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image") raw=f.read_bytes() mime="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 if not mime:raise SystemExit("Use PNG JPEG or WebP") b64=base64.b64encode(raw).decode() p["messages"][0]["content"].append({"type":"image_url","image_url":{"url":"data:"+mime+";base64,"+b64}}) Path("request.json").write_text(json.dumps(p,ensure_ascii=False)) PY_REQUEST curl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \ -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \ --data-binary @request.json -D response-headers.txt -o result.json python3 - <<'PY_RESULT' import json from pathlib import Path print(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2)) PY_RESULT ``` ```python from openai import OpenAI import os if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client = OpenAI(base_url="https://api.ailoot.ai/v1", api_key=os.environ["AILOOT_API_KEY"], max_retries=0) resp = client.chat.completions.create( model="claude-opus-4-6", messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}], ) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) save_result(resp.to_dict(mode="json")) ``` ```js import OpenAI from "openai"; if (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request"); const client = new OpenAI({ baseURL: "https://api.ailoot.ai/v1", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 }); const resp = await client.chat.completions.create({ model: "claude-opus-4-6", messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }], }); import { writeFileSync } from "node:fs"; function saveResult(data, stem = "result") { writeFileSync(stem + ".json", JSON.stringify(data, null, 2)); console.log(JSON.stringify(data, null, 2)); const saveBlob = (encoded, suffix, label) => { const raw = Buffer.from(encoded, "base64"); 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; const file = `${stem}-${label}.${ext}`; writeFileSync(file, raw); console.log("Saved", file); }; for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block)); for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {})); for (const [i, item] of (data.output || []).entries()) { console.log("Output", i, JSON.stringify(item)); if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`); } for (const [ci, candidate] of (data.candidates || []).entries()) { for (const [pi, part] of (candidate.content?.parts || []).entries()) { console.log("Candidate/part", ci, pi, JSON.stringify(part)); const blob = part.inlineData || part.inline_data; if (blob?.data) { const mime = blob.mimeType || blob.mime_type; const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin"; saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`); } } } } saveResult(resp); ``` ```python from openai import OpenAI import os from pathlib import Path if not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request") client=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0) import base64, json from pathlib import Path def save_result(data, stem="result"): # Keep every field, including usage, IDs, reasoning and tool requests. Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8") print(json.dumps(data, ensure_ascii=False, indent=2)) def save_blob(encoded, suffix, label): raw = base64.b64decode(encoded, altchars=b"-_", validate=True) 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 file = Path(stem + "-" + label + "." + ext) file.write_bytes(raw) print("Saved", file) for index, block in enumerate(data.get("content") or []): print("Content", index, json.dumps(block, ensure_ascii=False)) for choice in data.get("choices") or []: print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False)) for index, item in enumerate(data.get("output") or []): print("Output", index, json.dumps(item, ensure_ascii=False)) if item.get("type") == "image_generation_call" and item.get("result"): save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index)) for ci, candidate in enumerate(data.get("candidates") or []): for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []): print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False)) blob = part.get("inlineData") or part.get("inline_data") if blob and blob.get("data"): mime = blob.get("mimeType") or blob.get("mime_type") suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin") save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi)) with client.chat.completions.stream(model='claude-opus-4-6',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream: with Path("stream-events.jsonl").open("w",encoding="utf-8") as log: for event in stream: payload=event.to_dict(mode="json") log.write(json.dumps(payload,ensure_ascii=False)+"\n"); log.flush() print(json.dumps(payload,ensure_ascii=False)) final=stream.get_final_completion() save_result(final.to_dict(mode="json"),"stream-result") ``` ### Terima dan simpan hasil #### Ailoot · OpenAI Chat json atau SSE ##### Simpan semua hasil yang selesai Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan. Kekalkan setiap pilihan jawapan bersama kandungan, panggilan alat dan penaakulannya. Dalam SSE, gabungkan delta mengikut indeks pilihan jawapan/alat dan kekalkan sebab penamatan akhir serta data penggunaan. ##### Jika respons asal perlu disemak Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan. Medan respons | Medan | Jenis | | --- | --- | | Medan`choices[].index` | Jenisinteger | | Medan`choices[].message.content` | Jenisstring\|null | | Medan`choices[].message.tool_calls` | Jenistool\_call\[\] | | Medan`choices[].message.reasoning_content` | Jenisstring | | Medan`choices[].message.reasoning_details` | Jenisobject\|array | | Medan`choices[].finish_reason` | Jenisstring\|null | | Medan`usage` | Jenisobject | Ralat dan langkah seterusnya | Respons | Syarat | Langkah seterusnya | | --- | --- | --- | | Respons400 · `invalid_request_error` | SyaratMedan wajib, perwakilan bahan atau nilai parameter tidak sah | Langkah seterusnyaBetulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu. | ### Alias #### Alias model **Ailoot** [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=chat) #### Alias laluan kaedah Gunakan laluan kaedah yang dipaparkan di atas. #### ID pemanggil berkaitan [`claude-opus-4-6`](https://ailoot.ai/models/ms/#m=claude-opus-4-6&route=Core&caller=claude-opus-4-6&fmt=chat) FAQ · claude-opus-4-6 Apakah input dan hasil yang tersedia? `POST /v1/messages` · `claude-opus-4-6`: `text`, `image` → `text` `POST /v1/responses` · `claude-opus-4-6`: `text`, `image` → `text` `POST /v1/chat/completions` · `claude-opus-4-6`: `text`, `image` → `text` Apakah medan yang digunakan oleh permintaan? `POST /v1/messages` · `claude-opus-4-6`: `model`, `messages`, `system`, `max_tokens`, `stream`, `metadata` `POST /v1/responses` · `claude-opus-4-6`: `model`, `input`, `instructions`, `stream` `POST /v1/chat/completions` · `claude-opus-4-6`: `model`, `messages`, `stream` Apakah had yang terpakai? `POST /v1/messages` · `claude-opus-4-6`: `ctx`: `1000000`; `max_out`: `131072`; `messages.min_items`: `1`; `max_tokens.minimum`: `1` `POST /v1/responses` · `claude-opus-4-6`: `ctx`: `1000000`; `max_out`: `131072` `POST /v1/chat/completions` · `claude-opus-4-6`: `ctx`: `1000000`; `max_out`: `131072`; `messages.min_items`: `1` Sambungkan Ailoot kepada Claude Code, OpenCode, Hermes atau aplikasi anda. ## Syarikat dan portfolio projeknya Syarikat dan portfolio projeknya: jutaan pelanggan; jualan bernilai berbilion setiap bulan. ## Beli token dengan diskaun. Diskaun langganan untuk penggunaan berkala. Kod promosi — sehingga 50% bagi pembelian token. Langganan Pilih pelan berdiskaun untuk permintaan berkala anda. Kod promosi sehingga 50% Masukkan kod semasa pembelian. Harga dikira semula mengikut promosi semasa. Perbelanjaan dalam sejarah Model, token dan jumlah disimpan bagi setiap permintaan. [Pilih langganan](https://ailoot.ai/docs/ms/billing/subscriptions/) · [Lihat harga model](https://ailoot.ai/models/ms/) ## Sambungkan API kepada produk yang anda jual. SaaS, aplikasi dan bot — di bawah tawaran rasmi serta perjanjian lesen Ailoot. Untuk jualan semula, mohon lesen penjual semula. Aplikasi komersial Tambahkan penjanaan teks, imej, video dan audio pada ciri berbayar perkhidmatan anda. Lesen penjual semula Hantar keterangan projek dan susunan akses. Minta terma penggunaan serta jualan semula secara bertulis. Dokumen pada laman Tawaran, perjanjian lesen dan dasar pemprosesan data tersedia sebelum sambungan. [Mohon lesen penjual semula](mailto:support@ailoot.ai) · [Tawaran dan perjanjian lesen](https://ailoot.ai/legal/offer?lang=ms) ## Ailoot · Syarikat dan portfolio projeknya Ailoot berteraskan pengalaman operasi yang mantap, pangkalan pelanggan yang besar, perkhidmatan yang stabil dan pemantauan KPI berterusan. Syarikat dan portfolio projeknya: jutaan pelanggan; jualan bernilai berbilion setiap bulan. Ailoot menggunakan pengalaman operasi ini untuk akses API kepada ciri AI dalam produk pelanggan, ejen, aplikasi dan automasi.