Source: https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/ Canonical: https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/ Language: uz # MiniMax-M3.1-Flash-Preview [Markdown](https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/index.md) · [JSON](https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/facts.json) ## [MiniMax-M3.1-Flash-Preview](https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/) Dasturlash va murakkab vazifalar uchun boshqariladigan mulohaza chuqurligi hamda 1 mln tokengacha kontekstga ega multimodal model. - [**Ailoot · Anthropic Messages** `POST /v1/messages` `MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/#method-0) - [**Ailoot · OpenAI Responses** `POST /v1/responses` `MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/#method-1) - [**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/minimax-m3-1-flash-preview/#method-2) Model haqida Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan. #### Kod va vositalar bilan uzun vazifa MiniMax M3.1-Flash-Preview — dasturlash, mulohaza yuritish va murakkab vazifalarni tuzilmali bajarish uchun M seriyasining sinov versiyasidagi multimodal modeli. Ishlab chiqaruvchi vositalardan foydalanish va boshlang‘ich materiallar bilan izchil amallar orasidagi bog‘lanishni saqlash kerak bo‘lgan uzun sessiyalarni ta’kidlaydi. E’lon qilingan kontekst oynasi — **1 000 000 tokengacha**. U uzun hujjatlar, kod bazalari va ko‘p bosqichli tarix uchun mo‘ljallangan. Katta kontekstni kartadagi mavjud so‘rov chegarasini hisobga olib, ko‘rsatmalar, materiallar va javob orasida taqsimlash lozim. #### Mulohaza chuqurligini tanlash Bu versiyada mulohaza yuritish doimo yoqilgan: javob berishdan oldin model murakkab topshiriqni qadamlarga ajratadi. Uning chuqurligini `effort` boshqaradi; darajalar — `low`, `medium`, `high`, `xhigh` va `max`. Standart holatda `max` tanlangan; yuqoriroq daraja odatda batafsilroq mulohaza, ko‘proq chiqish tokenlari va uzoqroq kutishni anglatadi. Mulohaza yuritishni o‘chirish ko‘zda tutilmagan. Uning hajmini kamaytirish uchun ishlab chiqaruvchi chuqurlik darajasini pasaytirishni taklif qiladi. Mulohaza va yakuniy javob alohida qaytariladi, bu tayyor javobni alohida matn sifatida ko‘rsatishga imkon beradi. #### Materiallarni tushunish va natija Model imkoniyatlari matn, tasvirlar va videoni tushunishni o‘z ichiga oladi. Bu Ailoot kartasida matn va tasvirlar mavjud, natija esa matnli javob. Kod bajarish, qidiruv va fayllar bilan amallar uchun model umumiy vazifa doirasida boshqara oladigan ulangan vositalar kerak. M3.1-Flash-Preview’ni ko‘rsatilgan rejimlarga ega mustaqil versiya sifatida ko‘rib chiqish lozim. Uning mulohaza sozlamasi M3’ning almashtiriladigan rejimlaridan farq qiladi: sinov versiyasida doimo yoqilgan mulohazaning chuqurligi boshqariladi. Amaliy vazifa ### Amaliy vazifa Ingliz tilidagi texnik misol ``` Plan a backward-compatible rename We must rename API field sku to product_code. Existing clients send sku; new clients will send product_code. Stored records currently contain only sku. Plan a compatible sequence for readers, writers, backfill and eventual removal. Define handling for requests that contain both fields with different values, and name the checks required before removal. ``` #### Kutiladigan natija ``` A staged compatibility plan with an explicit conflict rule and removal gates. ``` #### Natijani tekshirish ``` The plan keeps old clients functional during transition and explicitly handles conflicting dual-field requests. ``` **Ailoot · Anthropic Messages** `POST /v1/messages` `MiniMax-M3.1-Flash-Preview` [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=messages) MiniMax /`MiniMax-M3.1-Flash-Preview` ### Boshlash Dasturlash va murakkab vazifalar uchun boshqariladigan mulohaza chuqurligi hamda 1 mln tokengacha kontekstga ega multimodal model. Qabul qilinadigan kirish ma’lumotlari Matn · Rasmlar Natijalar Matn ### Ailoot da mavjud · kirish ma’lumotlari va usullar **Ailoot · Anthropic Messages** `POST /v1/messages` Kirish `text`, `image` Chiqish `text` Kontekst 1 000 000 tokens Eng katta chiqish 524 288 tokens Chiqish formati json yoki SSE | Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart | | --- | --- | --- | --- | --- | | Maydon`model` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar MiniMax-M3.1-Flash-Preview | Standart— | | Maydon`messages` | Tur`message[]` | TalabMajburiy | Qiymatlar va cheklovlar Elementlarning eng kam soni: 1 | Standart— | | Maydon`messages[].role` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar user, assistant | Standart— | | Maydon`messages[].content` | Tur`string\|content_block[]` | TalabMajburiy | Qiymatlar va cheklovlar | Standart— | | Maydon`system` | Tur`string\|content_block[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`max_tokens` | Tur`integer` | TalabMajburiy | Qiymatlar va cheklovlar Eng kam: 1 Cheklov qo‘llanadigan obyekt: Tanlangan model yoki kartaning aniq yuqori chegarasi | Standart— | | Maydon`stream` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standartfalse | | Maydon`temperature` | Tur`number` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`top_p` | Tur`number` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`stop_sequences` | Tur`string[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tools` | Tur`tool[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tools[].name` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: Vosita taqdim etilgan | Standart— | | Maydon`tools[].description` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`tools[].input_schema` | Tur`JSON_schema` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`tool_choice` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`thinking.type` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`thinking.budget_tokens` | Tur`integer` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`output_config.effort` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`metadata` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`cache_control` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | Kirish materiallari birikmalari **Matn** · UTF8 matni `messages[].content yoki type=text bloki` **Matn + rasm** `{type:image,source:{type:base64,media_type,data}} yoki type=url turidagi manba` Usul parametrlari va hayot sikli | Parametr | Parametr talablari | | --- | --- | | Parametr`material_types` | Parametr talablaritext, image | | Parametr`required` | Parametr talablarimodel, messages, max\_tokens | | Parametr`optional_controls` | Parametr talablarinull | | Parametr`content_type` | Parametr talablariapplication/json | | Parametr`text_file_material` | Parametr talablariHaqiqiy UTF-8 kontenti matn sifatida kiritiladi; fayl IDlari/URLs uchun alohida aniq qo‘llab-quvvatlash kerak | Hayot sikli: `exact retained published method` Metod tuzilishlari va IDlari aniq; yetkazib beruvchining imkoniyati so‘rovni qabul qilishga ruxsatdan alohida. ### Tariflar #### Ailoot usullari tariflari Kirish 0,0003 US$ */ 1K* Chiqish 0,0012 US$ */ 1K* Keshdan o‘qish 0,0003 US$ */ 1K* Keshga yozish 0,0003 US$ */ 1K* Keshga yozish, 5 daqiqa 0,0003 US$ */ 1K tokens* Ailoot so‘rovdan oldin taxminiy summani band qiladi. Natijadan keyin o‘lchangan sarf asosidagi yakuniy to‘lovni yechadi. Oqimli javob bo‘yicha yakuniy hisob-kitob yakuniy sarf yozuviga asoslanadi. [Summani band qilish va to‘lovni hisoblash tartibi →](https://ailoot.ai/docs/uz/billing/reserve/) ### So‘rov namunalari #### Ailoot · Anthropic Messages Matn namunasiKirish, rasmPython SDKNode.js SDKPython oqimi ```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": "MiniMax-M3.1-Flash-Preview", "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": "MiniMax-M3.1-Flash-Preview", "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="MiniMax-M3.1-Flash-Preview", 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: "MiniMax-M3.1-Flash-Preview", 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='MiniMax-M3.1-Flash-Preview',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") ``` ### Natijalarni olish va saqlash #### Ailoot · Anthropic Messages json yoki SSE ##### Barcha tayyor natijalarni saqlash Qaytarilgan har bir to‘liq javob, fayl va kontent qismini saqlang. Barcha kontent bloklari, fikrlash imzolari va haqiqiy vosita ishlatish IDlarini saqlang. SSE bloklarining barcha o‘zgarish qismlarini yig‘ing; birinchi matn bloki to‘liq chiqish emas. ##### Asl javobni tekshirish kerak bo‘lsa So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan. Javob maydonlari | Maydon | Tur | | --- | --- | | Maydon`id` | Turstring | | Maydon`model` | Turstring | | Maydon`content[]` | Turtext\|thinking\|tool\_use\|other content block | | Maydon`stop_reason` | Turstring\|null | | Maydon`usage` | Turobject | Xatolar va keyingi qadamlar | Javob | Shart | Keyingi qadam | | --- | --- | --- | | Javob400 · `invalid_request_error` | ShartMajburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri | Keyingi qadamYangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating. | ### Taxalluslar #### Model taxalluslari **Ailoot** [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=messages) #### Usul yo‘llari taxalluslari Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning. #### Chaqirish uchun tegishli ID lar [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=messages) **Ailoot · OpenAI Responses** `POST /v1/responses` `MiniMax-M3.1-Flash-Preview` [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=responses) MiniMax /`MiniMax-M3.1-Flash-Preview` ### Boshlash Dasturlash va murakkab vazifalar uchun boshqariladigan mulohaza chuqurligi hamda 1 mln tokengacha kontekstga ega multimodal model. Qabul qilinadigan kirish ma’lumotlari Matn · Rasmlar Natijalar Matn ### Ailoot da mavjud · kirish ma’lumotlari va usullar **Ailoot · OpenAI Responses** `POST /v1/responses` Kirish `text`, `image` Chiqish `text` Kontekst 1 000 000 tokens Eng katta chiqish 524 288 tokens Chiqish formati json yoki SSE | Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart | | --- | --- | --- | --- | --- | | Maydon`model` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar MiniMax-M3.1-Flash-Preview | Standart— | | Maydon`input` | Tur`string\|input_item[]` | TalabMajburiy | Qiymatlar va cheklovlar | Standart— | | Maydon`instructions` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`input[].type` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar message, reasoning, function\_call, function\_call\_output | Standart— | | Maydon`input[].content` | Tur`string\|content_part[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`input[].call_id` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: function\_call\_output; haqiqatan qaytarilgan call\_id qiymatini saqlang | Standart— | | Maydon`input[].output` | Tur`string\|content_part[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: function\_call\_output | Standart— | | Maydon`max_output_tokens` | Tur`integer` | TalabIxtiyoriy | Qiymatlar va cheklovlar Eng kam: 1 Modelga bogʻliq | Standart— | | Maydon`stream` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standartfalse | | Maydon`temperature` | Tur`number` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`top_p` | Tur`number` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tools` | Tur`tool[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tool_choice` | Tur`string\|object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`parallel_tool_calls` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`reasoning.effort` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`reasoning.summary` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`text.format` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`text.verbosity` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`include` | Tur`string[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`store` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`previous_response_id` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar ID talabi: Faqat qo‘llab-quvvatlanadigan davom ettirishdan olingan haqiqiy javob IDsi Modelga bogʻliq | Standart— | | Maydon`service_tier` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`prompt_cache_key` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`prompt_cache_options` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | Kirish materiallari birikmalari **Matn** · UTF8 matni `Kirish matni yoki input_text qismi` **Matn + rasm** `{type:input_image,image_url}` Usul parametrlari va hayot sikli | Parametr | Parametr talablari | | --- | --- | | Parametr`material_types` | Parametr talablaritext, image | | Parametr`required` | Parametr talablarimodel, input | | Parametr`optional_controls` | Parametr talablarinull | | Parametr`content_type` | Parametr talablariapplication/json | | Parametr`text_file_material` | Parametr talablariHaqiqiy UTF-8 kontenti matn sifatida kiritiladi; fayl IDlari/URLs uchun alohida aniq qo‘llab-quvvatlash kerak | Hayot sikli: `exact retained published method` Metod tuzilishlari va IDlari aniq; yetkazib beruvchining imkoniyati so‘rovni qabul qilishga ruxsatdan alohida. ### Tariflar #### Ailoot usullari tariflari Kirish 0,0003 US$ */ 1K* Chiqish 0,0012 US$ */ 1K* Keshdan o‘qish 0,0003 US$ */ 1K* Keshga yozish 0,0003 US$ */ 1K* Keshga yozish, 5 daqiqa 0,0003 US$ */ 1K tokens* Ailoot so‘rovdan oldin taxminiy summani band qiladi. Natijadan keyin o‘lchangan sarf asosidagi yakuniy to‘lovni yechadi. Oqimli javob bo‘yicha yakuniy hisob-kitob yakuniy sarf yozuviga asoslanadi. [Summani band qilish va to‘lovni hisoblash tartibi →](https://ailoot.ai/docs/uz/billing/reserve/) ### So‘rov namunalari #### Ailoot · OpenAI Responses Matn namunasiKirish, rasmPython SDKNode.js SDKPython oqimi ```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": "MiniMax-M3.1-Flash-Preview", "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": "MiniMax-M3.1-Flash-Preview", "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="MiniMax-M3.1-Flash-Preview", 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: "MiniMax-M3.1-Flash-Preview", 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="MiniMax-M3.1-Flash-Preview", 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") ``` ### Natijalarni olish va saqlash #### Ailoot · OpenAI Responses json yoki SSE ##### Barcha tayyor natijalarni saqlash Qaytarilgan har bir to‘liq javob, fayl va kontent qismini saqlang. Har bir chiqish elementi va kontent qismini, funksiyaning haqiqiy call\_id qiymatini, shifrlangan fikrlash ma’lumotlari va sarfni saqlang. Oqimli uzatishda hodisa va elementning to‘liq identifikatsiyasini saqlang. ##### Asl javobni tekshirish kerak bo‘lsa So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan. Javob maydonlari | Maydon | Tur | | --- | --- | | Maydon`id` | Turstring | | Maydon`status` | Turstring | | Maydon`output[]` | Turmessage\|reasoning\|function\_call\|other item | | Maydon`output[].content[]` | Turcontent part | | Maydon`usage` | Turobject | Xatolar va keyingi qadamlar | Javob | Shart | Keyingi qadam | | --- | --- | --- | | Javob400 · `invalid_request_error` | ShartMajburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri | Keyingi qadamYangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating. | ### Taxalluslar #### Model taxalluslari **Ailoot** [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=responses) #### Usul yo‘llari taxalluslari Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning. #### Chaqirish uchun tegishli ID lar [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=responses) **Ailoot · OpenAI Chat** `POST /v1/chat/completions` `MiniMax-M3.1-Flash-Preview` [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=chat) MiniMax /`MiniMax-M3.1-Flash-Preview` ### Boshlash Dasturlash va murakkab vazifalar uchun boshqariladigan mulohaza chuqurligi hamda 1 mln tokengacha kontekstga ega multimodal model. Qabul qilinadigan kirish ma’lumotlari Matn · Rasmlar Natijalar Matn ### Ailoot da mavjud · kirish ma’lumotlari va usullar **Ailoot · OpenAI Chat** `POST /v1/chat/completions` Kirish `text`, `image` Chiqish `text` Kontekst 1 000 000 tokens Eng katta chiqish 524 288 tokens Chiqish formati json yoki SSE | Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart | | --- | --- | --- | --- | --- | | Maydon`model` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar MiniMax-M3.1-Flash-Preview | Standart— | | Maydon`messages` | Tur`message[]` | TalabMajburiy | Qiymatlar va cheklovlar Elementlarning eng kam soni: 1 | Standart— | | Maydon`messages[].role` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar Namunalar: system, user, assistant, tool, function Shartlar: Bu rollar manba kodining moslik turlarida ochiq ifodalangan; aniq rollar to‘plami har bir modelga xos bo‘lib qoladi. Modelga bogʻliq | Standart— | | Maydon`messages[].content` | Tur`string\|content_part[]\|null` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`messages[].tool_calls` | Tur`tool_call[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`messages[].tool_call_id` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: role=tool; haqiqatan qaytarilgan IDdan foydalaning | Standart— | | Maydon`messages[].name` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`messages[].reasoning_content` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: Ushbu model foydalanganda, haqiqatan qaytarilgan fikrlash ma’lumotlarini keyingi so‘rovda qayta yuboring | Standart— | | Maydon`messages[].reasoning_details` | Tur`object\|array` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`max_tokens` | Tur`integer` | TalabIxtiyoriy | Qiymatlar va cheklovlar Eng kam: 1 Modelga bogʻliq | Standart— | | Maydon`max_completion_tokens` | Tur`integer` | TalabIxtiyoriy | Qiymatlar va cheklovlar Eng kam: 1 Modelga bogʻliq | Standart— | | Maydon`stream` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standartfalse | | Maydon`stream_options.include_usage` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`temperature` | Tur`number` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`top_p` | Tur`number` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`stop` | Tur`string\|string[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tools` | Tur`function_tool[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tools[].type` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`tools[].function.name` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: Funksiya vositasi taqdim etilgan | Standart— | | Maydon`tools[].function.description` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`tools[].function.parameters` | Tur`JSON_schema` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— | | Maydon`tool_choice` | Tur`string\|object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`parallel_tool_calls` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`response_format` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`reasoning_effort` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`reasoning` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`service_tier` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`instructions` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Moslik maydoni | Standart— | | Maydon`functions` | Tur`function[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`function_call` | Tur`string\|object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | | Maydon`prompt_cache_options` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— | Kirish materiallari birikmalari **Matn** · UTF8 matni `messages[].content` **Matn + rasm** `{type:image_url,image_url:{url,detail}}` Usul parametrlari va hayot sikli | Parametr | Parametr talablari | | --- | --- | | Parametr`material_types` | Parametr talablaritext, image | | Parametr`required` | Parametr talablarimodel, messages | | Parametr`optional_controls` | Parametr talablarinull | | Parametr`content_type` | Parametr talablariapplication/json | | Parametr`text_file_material` | Parametr talablariHaqiqiy UTF-8 kontenti matn sifatida kiritiladi; fayl IDlari/URLs uchun alohida aniq qo‘llab-quvvatlash kerak | Hayot sikli: `exact retained published method` Metod tuzilishlari va IDlari aniq; yetkazib beruvchining imkoniyati so‘rovni qabul qilishga ruxsatdan alohida. ### Tariflar #### Ailoot usullari tariflari Kirish 0,0003 US$ */ 1K* Chiqish 0,0012 US$ */ 1K* Keshdan o‘qish 0,0003 US$ */ 1K* Keshga yozish 0,0003 US$ */ 1K* Keshga yozish, 5 daqiqa 0,0003 US$ */ 1K tokens* Ailoot so‘rovdan oldin taxminiy summani band qiladi. Natijadan keyin o‘lchangan sarf asosidagi yakuniy to‘lovni yechadi. Oqimli javob bo‘yicha yakuniy hisob-kitob yakuniy sarf yozuviga asoslanadi. [Summani band qilish va to‘lovni hisoblash tartibi →](https://ailoot.ai/docs/uz/billing/reserve/) ### So‘rov namunalari #### Ailoot · OpenAI Chat Matn namunasiKirish, rasmPython SDKNode.js SDKPython oqimi ```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": "MiniMax-M3.1-Flash-Preview", "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": "MiniMax-M3.1-Flash-Preview", "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="MiniMax-M3.1-Flash-Preview", 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: "MiniMax-M3.1-Flash-Preview", 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='MiniMax-M3.1-Flash-Preview',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") ``` ### Natijalarni olish va saqlash #### Ailoot · OpenAI Chat json yoki SSE ##### Barcha tayyor natijalarni saqlash Qaytarilgan har bir to‘liq javob, fayl va kontent qismini saqlang. Har bir javob variantini va uning kontenti, vosita chaqiruvlari hamda fikrlash ma’lumotlarini saqlang. SSEda o‘zgarish qismlarini variant va vosita indeksi bo‘yicha yig‘ing, yakuniy tugash sababi va sarf ma’lumotlarini saqlang. ##### Asl javobni tekshirish kerak bo‘lsa So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan. Javob maydonlari | Maydon | Tur | | --- | --- | | Maydon`choices[].index` | Turinteger | | Maydon`choices[].message.content` | Turstring\|null | | Maydon`choices[].message.tool_calls` | Turtool\_call\[\] | | Maydon`choices[].message.reasoning_content` | Turstring | | Maydon`choices[].message.reasoning_details` | Turobject\|array | | Maydon`choices[].finish_reason` | Turstring\|null | | Maydon`usage` | Turobject | Xatolar va keyingi qadamlar | Javob | Shart | Keyingi qadam | | --- | --- | --- | | Javob400 · `invalid_request_error` | ShartMajburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri | Keyingi qadamYangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating. | ### Taxalluslar #### Model taxalluslari **Ailoot** [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=chat) #### Usul yo‘llari taxalluslari Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning. #### Chaqirish uchun tegishli ID lar [`MiniMax-M3.1-Flash-Preview`](https://ailoot.ai/models/uz/#m=MiniMax-M3.1-Flash-Preview&route=Core&caller=MiniMax-M3.1-Flash-Preview&fmt=chat) FAQ · MiniMax-M3.1-Flash-Preview Qanday kirish ma’lumotlari va natijalar mavjud? `POST /v1/messages` · `MiniMax-M3.1-Flash-Preview`: `text`, `image` → `text` `POST /v1/responses` · `MiniMax-M3.1-Flash-Preview`: `text`, `image` → `text` `POST /v1/chat/completions` · `MiniMax-M3.1-Flash-Preview`: `text`, `image` → `text` So‘rov qaysi maydonlardan foydalanadi? `POST /v1/messages` · `MiniMax-M3.1-Flash-Preview`: `model`, `messages`, `system`, `max_tokens`, `stream`, `metadata` `POST /v1/responses` · `MiniMax-M3.1-Flash-Preview`: `model`, `input`, `instructions`, `stream` `POST /v1/chat/completions` · `MiniMax-M3.1-Flash-Preview`: `model`, `messages`, `stream` Qanday cheklovlar amal qiladi? `POST /v1/messages` · `MiniMax-M3.1-Flash-Preview`: `ctx`: `1000000`; `max_out`: `524288`; `messages.min_items`: `1`; `max_tokens.minimum`: `1` `POST /v1/responses` · `MiniMax-M3.1-Flash-Preview`: `ctx`: `1000000`; `max_out`: `524288` `POST /v1/chat/completions` · `MiniMax-M3.1-Flash-Preview`: `ctx`: `1000000`; `max_out`: `524288`; `messages.min_items`: `1` Ailoot’ni Claude Code, OpenCode, Hermes yoki ilovangizga ulang. ## Kompaniya va uning loyihalar portfeli Kompaniya va uning loyihalar portfeli: millionlab mijozlar; oylik sotuvlar hajmi milliardlarda. ## Tokenlarni chegirma bilan xarid qiling. Muntazam ish uchun obuna chegirmasi. Token xaridiga promokodlar — 50% gacha. Obuna Muntazam so‘rovlaringiz uchun chegirmali tarif tanlang. 50% gacha promokod Xaridda kod kiriting. Narx amaldagi aksiya bilan qayta hisoblanadi. Tarixdagi xarajatlar Har so‘rov uchun model, token va summa saqlanadi. [Obuna tanlash](https://ailoot.ai/docs/uz/billing/subscriptions/) · [Model narxlarini ko‘rish](https://ailoot.ai/models/uz/) ## API’ni sotadigan mahsulotingizga ulang. SaaS, ilova va botlar Ailoot ofertasi hamda litsenziya shartnomasiga muvofiq. Qayta sotishga reseller litsenziyasi so‘rang. Tijorat ilovasi Xizmatingizning pullik funksiyalariga matn, rasm, video va ovoz yaratishni qo‘shing. Reseller litsenziyasi Loyiha tavsifi va kirish sxemasini yuboring. Foydalanish va qayta sotishga yozma shartlarni so‘rang. Saytdagi hujjatlar Oferta, litsenziya shartnomasi va ma’lumotlar siyosati ulashdan oldin ochiq. [Reseller litsenziyasini so‘rash](mailto:support@ailoot.ai) · [Oferta va litsenziya shartnomasi](https://ailoot.ai/legal/offer?lang=uz) ## Ailoot · Kompaniya va uning loyihalar portfeli Ailoot to‘plangan faoliyat tajribasi, keng mijozlar bazasi, barqaror xizmat va doimiy KPI nazoratiga tayanadi. Kompaniya va uning loyihalar portfeli: millionlab mijozlar; oylik sotuvlar hajmi milliardlarda. Ailoot bu faoliyat tajribasini mijozlar mahsulotlari, agentlar, ilovalar va avtomatlashtirishlarda AI imkoniyatlariga API orqali kirishni ta’minlashda qo‘llaydi.