Gemini 3.7 Flash mulohaza yurituvchi multimodal modellar yo‘nalishini rivojlantiradi. U Gemini 3.6 Flash’ga asoslangan va mulohaza yuritishning asosiy mexanizmidagi o‘zgarishlar hamda agent vazifalarida videoni tushunishni qo‘llab-quvvatlashni o‘z ichiga oladi. Ish ssenariylariga dasturlash, video materiallarning murakkab tahlili va bir nechta bosqichli jarayonlar kiradi.
Google xususiyatlariga ko‘ra, model matn, tasvirlar, video, audio va PDF’ni tushunadi. Ailoot API’ning joriy katalogida matnli metodlar uchun kirishda matn va tasvirlar, chiqishda esa matn e’lon qilingan. Video, audio va PDF bu kirishlar to‘plamiga kiritilmagan. So‘rovning maksimal hajmi — 1 048 576 kirish tokeni, javobniki — 65 536 chiqish tokeni. Javob matnli bo‘lib qoladi; bu versiya uchun tasvir yoki audioni mustaqil yaratish qo‘llab-quvvatlanmaydi.
Thinking uchta qo‘llab-quvvatlanadigan darajaga ega: low, medium va high. Google tavsiflagan bazaviy model rejimida standart daraja — medium. Bu qiymatlar Google’ning bazaviy modelini tavsiflaydi; Ailoot API orqali boshqarish rejimi va mavjudligi tanlangan metod hamda model variantiga bog‘liq. Ular qo‘shimcha mulohaza intensivligini tanlashga imkon beradi. Gemini 3.7 Flash’da minimal darajasi qo‘llab-quvvatlanmaydi: bunday parametr xatoga olib keladi. Mulohaza sozlamalari modelning ish rejimiga ta’sir qiladi, lekin qo‘llab-quvvatlanadigan chiqish turini o‘zgartirmaydi.
Vazifalarni izchil bajarish uchun funksiya chaqiruvlari, kod bajarish va tuzilmali javoblar ko‘zda tutilgan. Model kontekstni keshlash, fayllar bo‘yicha qidiruv, qidiruv natijalari bilan asoslash, Google Maps va veb-manzillar mazmunidan foydalanishi mumkin. Paketli qayta ishlash qo‘llab-quvvatlanadi. Kompyuter interfeysini boshqarish dastlabki imkoniyat deb belgilangan; undan foydalanish tanlangan metod qo‘llab-quvvatlashini talab qiladi.
Barqaror gemini-3.7-flash versiyasi 2026-yil avgustda e’lon qilingan. Ishlab chiqaruvchi ichki bilimlar chegarasi sifatida 2026-yil martni ko‘rsatadi, lekin ayrim sohalarda bilimlar 2025-yil yanvar darajasida qolishi mumkinligini qayd etadi. Tashqi ma’lumotlar bilan ishlash va yuborilgan materialni tushunish model allaqachon biladigan ma’lumotlardan farq qiladi.
Model to‘qima faktlar yaratishi, ayrim so‘rovlarni sekin bajarishi yoki kutish vaqti tugashi bilan yakunlashi mumkin. U murakkab ish sikllari uchun mo‘ljallangan, lekin alohida amalni bajarish qobiliyati bunday jarayonning to‘liq natijasini tekshirish o‘rnini bosmaydi. Multimodal kirishlardan foydalanilganda natija yangi mediafayl emas, materiallar mazmuni bo‘yicha matnli xulosalar bo‘ladi.
", "aboutText": "Gemini 3.7 Flash mulohaza yurituvchi multimodal modellar yo‘nalishini rivojlantiradi. U Gemini 3.6 Flash’ga asoslangan va mulohaza yuritishning asosiy mexanizmidagi o‘zgarishlar hamda agent vazifalarida videoni tushunishni qo‘llab-quvvatlashni o‘z ichiga oladi. Ish ssenariylariga dasturlash, video materiallarning murakkab tahlili va bir nechta bosqichli jarayonlar kiradi.\n\n### Kirish va matnli natija\n\nGoogle xususiyatlariga ko‘ra, model **matn, tasvirlar, video, audio va PDF**’ni tushunadi. Ailoot API’ning joriy katalogida matnli metodlar uchun kirishda **matn va tasvirlar**, chiqishda esa matn e’lon qilingan. Video, audio va PDF bu kirishlar to‘plamiga kiritilmagan. So‘rovning maksimal hajmi — **1 048 576 kirish tokeni**, javobniki — **65 536 chiqish tokeni**. Javob matnli bo‘lib qoladi; bu versiya uchun tasvir yoki audioni mustaqil yaratish qo‘llab-quvvatlanmaydi.\n\n### Mulohazani boshqarish\n\nThinking uchta qo‘llab-quvvatlanadigan darajaga ega: **`low`, `medium` va `high`**. Google tavsiflagan bazaviy model rejimida standart daraja — `medium`. Bu qiymatlar Google’ning bazaviy modelini tavsiflaydi; Ailoot API orqali boshqarish rejimi va mavjudligi tanlangan metod hamda model variantiga bog‘liq. Ular qo‘shimcha mulohaza intensivligini tanlashga imkon beradi. Gemini 3.7 Flash’da `minimal` darajasi **qo‘llab-quvvatlanmaydi**: bunday parametr xatoga olib keladi. Mulohaza sozlamalari modelning ish rejimiga ta’sir qiladi, lekin qo‘llab-quvvatlanadigan chiqish turini o‘zgartirmaydi.\n\nVazifalarni izchil bajarish uchun funksiya chaqiruvlari, kod bajarish va tuzilmali javoblar ko‘zda tutilgan. Model kontekstni keshlash, fayllar bo‘yicha qidiruv, qidiruv natijalari bilan asoslash, Google Maps va veb-manzillar mazmunidan foydalanishi mumkin. Paketli qayta ishlash qo‘llab-quvvatlanadi. Kompyuter interfeysini boshqarish dastlabki imkoniyat deb belgilangan; undan foydalanish tanlangan metod qo‘llab-quvvatlashini talab qiladi.\n\n### Chegara qayerdan o‘tadi\n\nBarqaror `gemini-3.7-flash` versiyasi 2026-yil avgustda e’lon qilingan. Ishlab chiqaruvchi ichki bilimlar chegarasi sifatida 2026-yil martni ko‘rsatadi, lekin ayrim sohalarda bilimlar 2025-yil yanvar darajasida qolishi mumkinligini qayd etadi. Tashqi ma’lumotlar bilan ishlash va yuborilgan materialni tushunish model allaqachon biladigan ma’lumotlardan farq qiladi.\n\nModel to‘qima faktlar yaratishi, ayrim so‘rovlarni sekin bajarishi yoki kutish vaqti tugashi bilan yakunlashi mumkin. U murakkab ish sikllari uchun mo‘ljallangan, lekin alohida amalni bajarish qobiliyati bunday jarayonning to‘liq natijasini tekshirish o‘rnini bosmaydi. Multimodal kirishlardan foydalanilganda natija yangi mediafayl emas, materiallar mazmuni bo‘yicha matnli xulosalar bo‘ladi.", "editorialOverlay": { "copy_fields": { "practical_html": "Ingliz tilidagi texnik misol
Audit a staged document handoff\n\nReview this release plan: writer finishes at 10:00; reviewer needs 45 minutes after writing; publisher needs 20 minutes after approval; launch is fixed at 11:00. Can the plan meet launch? Give the earliest finish, the dependency that controls it and one change that would make the plan feasible without overlapping dependent work.A dependency timeline, a feasibility conclusion and one quantified schedule change.The calculation respects write-before-review-before-publication and checks the proposed change against 11:00.gemini-3.7-flash-mediumDasturlash, videoni tushunish va ko‘p bosqichli ish jarayonlari uchun sozlanadigan mulohazaga ega Google’ning multimodal modeli.
Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.
Gemini 3.7 Flash mulohaza yurituvchi multimodal modellar yo‘nalishini rivojlantiradi. U Gemini 3.6 Flash’ga asoslangan va mulohaza yuritishning asosiy mexanizmidagi o‘zgarishlar hamda agent vazifalarida videoni tushunishni qo‘llab-quvvatlashni o‘z ichiga oladi. Ish ssenariylariga dasturlash, video materiallarning murakkab tahlili va bir nechta bosqichli jarayonlar kiradi.
Google xususiyatlariga ko‘ra, model matn, tasvirlar, video, audio va PDF’ni tushunadi. Ailoot API’ning joriy katalogida matnli metodlar uchun kirishda matn va tasvirlar, chiqishda esa matn e’lon qilingan. Video, audio va PDF bu kirishlar to‘plamiga kiritilmagan. So‘rovning maksimal hajmi — 1 048 576 kirish tokeni, javobniki — 65 536 chiqish tokeni. Javob matnli bo‘lib qoladi; bu versiya uchun tasvir yoki audioni mustaqil yaratish qo‘llab-quvvatlanmaydi.
Thinking uchta qo‘llab-quvvatlanadigan darajaga ega: low, medium va high. Google tavsiflagan bazaviy model rejimida standart daraja — medium. Bu qiymatlar Google’ning bazaviy modelini tavsiflaydi; Ailoot API orqali boshqarish rejimi va mavjudligi tanlangan metod hamda model variantiga bog‘liq. Ular qo‘shimcha mulohaza intensivligini tanlashga imkon beradi. Gemini 3.7 Flash’da minimal darajasi qo‘llab-quvvatlanmaydi: bunday parametr xatoga olib keladi. Mulohaza sozlamalari modelning ish rejimiga ta’sir qiladi, lekin qo‘llab-quvvatlanadigan chiqish turini o‘zgartirmaydi.
Vazifalarni izchil bajarish uchun funksiya chaqiruvlari, kod bajarish va tuzilmali javoblar ko‘zda tutilgan. Model kontekstni keshlash, fayllar bo‘yicha qidiruv, qidiruv natijalari bilan asoslash, Google Maps va veb-manzillar mazmunidan foydalanishi mumkin. Paketli qayta ishlash qo‘llab-quvvatlanadi. Kompyuter interfeysini boshqarish dastlabki imkoniyat deb belgilangan; undan foydalanish tanlangan metod qo‘llab-quvvatlashini talab qiladi.
Barqaror gemini-3.7-flash versiyasi 2026-yil avgustda e’lon qilingan. Ishlab chiqaruvchi ichki bilimlar chegarasi sifatida 2026-yil martni ko‘rsatadi, lekin ayrim sohalarda bilimlar 2025-yil yanvar darajasida qolishi mumkinligini qayd etadi. Tashqi ma’lumotlar bilan ishlash va yuborilgan materialni tushunish model allaqachon biladigan ma’lumotlardan farq qiladi.
Model to‘qima faktlar yaratishi, ayrim so‘rovlarni sekin bajarishi yoki kutish vaqti tugashi bilan yakunlashi mumkin. U murakkab ish sikllari uchun mo‘ljallangan, lekin alohida amalni bajarish qobiliyati bunday jarayonning to‘liq natijasini tekshirish o‘rnini bosmaydi. Multimodal kirishlardan foydalanilganda natija yangi mediafayl emas, materiallar mazmuni bo‘yicha matnli xulosalar bo‘ladi.
POST /v1/messagestext, imagetext| Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart |
|---|---|---|---|---|
Maydonmodel | Turstring | TalabMajburiy | Qiymatlar va cheklovlar gemini-3.7-flash-medium | Standart— |
Maydonmessages | Turmessage[] | TalabMajburiy | Qiymatlar va cheklovlar Elementlarning eng kam soni: 1 | Standart— |
Maydonmessages[].role | Turstring | TalabMajburiy | Qiymatlar va cheklovlar user, assistant | Standart— |
Maydonmessages[].content | Turstring|content_block[] | TalabMajburiy | Qiymatlar va cheklovlar | Standart— |
Maydonsystem | Turstring|content_block[] | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— |
Maydonmax_tokens | Turinteger | TalabMajburiy | Qiymatlar va cheklovlar Eng kam: 1 Cheklov qo‘llanadigan obyekt: Tanlangan model yoki kartaning aniq yuqori chegarasi | Standart— |
Maydonstream | Turboolean | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standartfalse |
Maydontemperature | Turnumber | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydontop_p | Turnumber | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydonstop_sequences | Turstring[] | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydontools | Turtool[] | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydontools[].name | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: Vosita taqdim etilgan | Standart— |
Maydontools[].description | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— |
Maydontools[].input_schema | TurJSON_schema | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— |
Maydontool_choice | Turobject | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydonthinking.type | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydonthinking.budget_tokens | Turinteger | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydonoutput_config.effort | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydonmetadata | Turobject | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— |
Maydoncache_control | Turobject | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Matn · UTF8 matni
messages[].content yoki type=text bloki
Matn + rasm
{type:image,source:{type:base64,media_type,data}} yoki type=url turidagi manba
| Parametr | Parametr talablari |
|---|---|
Parametrmaterial_types | Parametr talablaritext, image |
Parametrrequired | Parametr talablarimodel, messages, max_tokens |
Parametroptional_controls | Parametr talablarinull |
Parametrcontent_type | Parametr talablariapplication/json |
Parametrtext_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.
POST /v1/messagesAiloot 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 →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "gemini-3.7-flash-medium", "max_tokens": 1024, "messages": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["messages"]=[{"role":"user","content":"Summarize this material and quote supporting source passages.\\n\\n"+text}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "gemini-3.7-flash-medium", "max_tokens": 1024, "messages": [{"role": "user", "content": [{"type": "text", "text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["messages"][0]["content"].append({"type":"image","source":{"type":"base64","media_type":mime,"data":b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\nimport anthropic\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = anthropic.Anthropic(base_url="https://api.ailoot.ai", api_key=os.environ["AILOOT_API_KEY"], max_retries=0)\nmsg = client.messages.create(\n model="gemini-3.7-flash-medium",\n max_tokens=1024,\n messages=[{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}],\n)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(msg.to_dict(mode="json"))\nimport Anthropic from "@anthropic-ai/sdk";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst client = new Anthropic({ baseURL: "https://api.ailoot.ai", apiKey: process.env.AILOOT_API_KEY, maxRetries: 0 });\nconst msg = await client.messages.create({\n model: "gemini-3.7-flash-medium",\n max_tokens: 1024,\n messages: [{ role: "user", content: "Explain the difference between an observation and a hypothesis in three sentences." }],\n});\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, "base64");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log("Saved", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log("Output", i, JSON.stringify(item));\n if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log("Candidate/part", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(msg);\nimport anthropic,os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=anthropic.Anthropic(base_url="https://api.ailoot.ai",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.messages.stream(model='gemini-3.7-flash-medium',max_tokens=1024,messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n for event in stream:\n payload=event.to_dict(mode="json")\n log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_message()\n save_result(final.to_dict(mode="json"),"stream-result")\njson yoki SSE
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.
So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan.
| Maydon | Tur |
|---|---|
Maydonid | Turstring |
Maydonmodel | Turstring |
Maydoncontent[] | Turtext|thinking|tool_use|other content block |
Maydonstop_reason | Turstring|null |
Maydonusage | Turobject |
| 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. |
Ailoot gemini-3.7-flash-medium
Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.
gemini-3.7-flash-mediumDasturlash, videoni tushunish va ko‘p bosqichli ish jarayonlari uchun sozlanadigan mulohazaga ega Google’ning multimodal modeli.
Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.
Gemini 3.7 Flash mulohaza yurituvchi multimodal modellar yo‘nalishini rivojlantiradi. U Gemini 3.6 Flash’ga asoslangan va mulohaza yuritishning asosiy mexanizmidagi o‘zgarishlar hamda agent vazifalarida videoni tushunishni qo‘llab-quvvatlashni o‘z ichiga oladi. Ish ssenariylariga dasturlash, video materiallarning murakkab tahlili va bir nechta bosqichli jarayonlar kiradi.
Google xususiyatlariga ko‘ra, model matn, tasvirlar, video, audio va PDF’ni tushunadi. Ailoot API’ning joriy katalogida matnli metodlar uchun kirishda matn va tasvirlar, chiqishda esa matn e’lon qilingan. Video, audio va PDF bu kirishlar to‘plamiga kiritilmagan. So‘rovning maksimal hajmi — 1 048 576 kirish tokeni, javobniki — 65 536 chiqish tokeni. Javob matnli bo‘lib qoladi; bu versiya uchun tasvir yoki audioni mustaqil yaratish qo‘llab-quvvatlanmaydi.
Thinking uchta qo‘llab-quvvatlanadigan darajaga ega: low, medium va high. Google tavsiflagan bazaviy model rejimida standart daraja — medium. Bu qiymatlar Google’ning bazaviy modelini tavsiflaydi; Ailoot API orqali boshqarish rejimi va mavjudligi tanlangan metod hamda model variantiga bog‘liq. Ular qo‘shimcha mulohaza intensivligini tanlashga imkon beradi. Gemini 3.7 Flash’da minimal darajasi qo‘llab-quvvatlanmaydi: bunday parametr xatoga olib keladi. Mulohaza sozlamalari modelning ish rejimiga ta’sir qiladi, lekin qo‘llab-quvvatlanadigan chiqish turini o‘zgartirmaydi.
Vazifalarni izchil bajarish uchun funksiya chaqiruvlari, kod bajarish va tuzilmali javoblar ko‘zda tutilgan. Model kontekstni keshlash, fayllar bo‘yicha qidiruv, qidiruv natijalari bilan asoslash, Google Maps va veb-manzillar mazmunidan foydalanishi mumkin. Paketli qayta ishlash qo‘llab-quvvatlanadi. Kompyuter interfeysini boshqarish dastlabki imkoniyat deb belgilangan; undan foydalanish tanlangan metod qo‘llab-quvvatlashini talab qiladi.
Barqaror gemini-3.7-flash versiyasi 2026-yil avgustda e’lon qilingan. Ishlab chiqaruvchi ichki bilimlar chegarasi sifatida 2026-yil martni ko‘rsatadi, lekin ayrim sohalarda bilimlar 2025-yil yanvar darajasida qolishi mumkinligini qayd etadi. Tashqi ma’lumotlar bilan ishlash va yuborilgan materialni tushunish model allaqachon biladigan ma’lumotlardan farq qiladi.
Model to‘qima faktlar yaratishi, ayrim so‘rovlarni sekin bajarishi yoki kutish vaqti tugashi bilan yakunlashi mumkin. U murakkab ish sikllari uchun mo‘ljallangan, lekin alohida amalni bajarish qobiliyati bunday jarayonning to‘liq natijasini tekshirish o‘rnini bosmaydi. Multimodal kirishlardan foydalanilganda natija yangi mediafayl emas, materiallar mazmuni bo‘yicha matnli xulosalar bo‘ladi.
POST /v1beta/models/{model}:generateContenttext, imagetext| Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart |
|---|---|---|---|---|
Maydonpath.model | Turstring | TalabMajburiy | Qiymatlar va cheklovlar gemini-3.7-flash-medium | Standart— |
Maydoncontents | Turcontent[] | TalabMajburiy | Qiymatlar va cheklovlar Elementlarning eng kam soni: 1 | Standart— |
Maydoncontents[].role | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar user, model | Standart— |
Maydoncontents[].parts | Turpart[] | TalabMajburiy | Qiymatlar va cheklovlar | Standart— |
MaydonsystemInstruction | Turcontent | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— |
MaydongenerationConfig.maxOutputTokens | Turinteger | TalabIxtiyoriy | Qiymatlar va cheklovlar Eng kam: 1 Modelga bogʻliq | Standart— |
MaydongenerationConfig.temperature | Turnumber | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydongenerationConfig.topP | Turnumber | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydongenerationConfig.topK | Turinteger | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydongenerationConfig.stopSequences | Turstring[] | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydongenerationConfig.thinkingConfig.includeThoughts | Turboolean | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydongenerationConfig.thinkingConfig.thinkingBudget | Turinteger | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
Maydontools[].functionDeclarations | Turfunction_declaration[] | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydontoolConfig.functionCallingConfig.mode | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydonsafetySettings | Turobject[] | TalabIxtiyoriy | Qiymatlar va cheklovlar Modelga bogʻliq | Standart— |
MaydonsessionId | Turstring | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standart— |
Matn · UTF8 matni
contents[].parts[].text
Matn + rasm
parts[].inlineData={mimeType,data}
| Parametr | Parametr talablari |
|---|---|
Parametrmaterial_types | Parametr talablaritext, image |
Parametrrequired | Parametr talablaricontents |
Parametroptional_controls | Parametr talablarinull |
Parametrcontent_type | Parametr talablariapplication/json |
Parametrtext_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.
POST /v1beta/models/{model}:generateContentAiloot 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 →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source-material file}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"contents": []}')\nf=Path(os.environ["AILOOT_TEXT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 source material")\ntext=f.read_text(encoding="utf-8")\nif not text.strip():raise SystemExit("Source material must contain text")\np["contents"]=[{"role":"user","parts":[{"text":"Summarize this material and quote supporting source passages.\\n\\n"+text}]}]\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1beta/models/gemini-3.7-flash-medium:generateContent \\\n -H "x-goog-api-key: $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_IMAGE_FILE:?Set your actual PNG JPEG or WebP image}"\nexport AILOOT_IMAGE_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"contents": [{"role": "user", "parts": [{"text": "Read labels and numbers in this image; flag unreadable text."}]}]}')\nimport base64\nf=Path(os.environ["AILOOT_IMAGE_FILE"])\nif not f.is_file():raise SystemExit("Choose an actual PNG JPEG or WebP image")\nraw=f.read_bytes()\nmime="image/png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "image/jpeg" if raw.startswith(b"\\xff\\xd8") else "image/webp" if raw[:4]==b"RIFF" and raw[8:12]==b"WEBP" else None\nif not mime:raise SystemExit("Use PNG JPEG or WebP")\nb64=base64.b64encode(raw).decode()\np["contents"][0]["parts"].append({"inlineData":{"mimeType":mime,"data":b64}})\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1beta/models/gemini-3.7-flash-medium:generateContent \\\n -H "x-goog-api-key: $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(json.loads(Path("result.json").read_text(encoding="utf-8")))\nPY_RESULT\nfrom google import genai\nfrom google.genai import types\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient = genai.Client(\n api_key=os.environ["AILOOT_API_KEY"],\n http_options=types.HttpOptions(base_url="https://api.ailoot.ai"),\n)\nresp = client.models.generate_content(model="gemini-3.7-flash-medium", contents="Explain the difference between an observation and a hypothesis in three sentences.")\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(resp.to_json_dict())\nimport { GoogleGenAI } from "@google/genai";\n\nif (!process.env.AILOOT_API_KEY?.trim()) throw new Error("Set AILOOT_API_KEY before making a request");\nconst ai = new GoogleGenAI({ apiKey: process.env.AILOOT_API_KEY, httpOptions: { baseUrl: "https://api.ailoot.ai" } });\nconst resp = await ai.models.generateContent({ model: "gemini-3.7-flash-medium", contents: "Explain the difference between an observation and a hypothesis in three sentences." });\nimport { writeFileSync } from "node:fs";\n\nfunction saveResult(data, stem = "result") {\n writeFileSync(stem + ".json", JSON.stringify(data, null, 2));\n console.log(JSON.stringify(data, null, 2));\n const saveBlob = (encoded, suffix, label) => {\n const raw = Buffer.from(encoded, "base64");\n const ext = raw.subarray(0,8).equals(Buffer.from([137,80,78,71,13,10,26,10])) ? "png" : raw[0]===255 && raw[1]===216 ? "jpg" : raw.subarray(0,4).toString()==="RIFF" && raw.subarray(8,12).toString()==="WEBP" ? "webp" : suffix;\n const file = `${stem}-${label}.${ext}`;\n writeFileSync(file, raw); console.log("Saved", file);\n };\n for (const [i, block] of (data.content || []).entries()) console.log("Content", i, JSON.stringify(block));\n for (const choice of data.choices || []) console.log("Choice", choice.index, JSON.stringify(choice.message || choice.delta || {}));\n for (const [i, item] of (data.output || []).entries()) {\n console.log("Output", i, JSON.stringify(item));\n if (item.type === "image_generation_call" && item.result) saveBlob(item.result, item.output_format || "bin", `output-${i}`);\n }\n for (const [ci, candidate] of (data.candidates || []).entries()) {\n for (const [pi, part] of (candidate.content?.parts || []).entries()) {\n console.log("Candidate/part", ci, pi, JSON.stringify(part));\n const blob = part.inlineData || part.inline_data;\n if (blob?.data) {\n const mime = blob.mimeType || blob.mime_type;\n const suffix = ({"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"})[mime] || "bin";\n saveBlob(blob.data, suffix, `candidate-${ci}-part-${pi}`);\n }\n }\n }\n}\n\nsaveResult(resp);\nfrom google import genai\nfrom google.genai import types\nimport os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=genai.Client(api_key=os.environ["AILOOT_API_KEY"],http_options=types.HttpOptions(base_url="https://api.ailoot.ai"))\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n file = Path(stem + "-" + label + "." + ext)\n file.write_bytes(raw)\n print("Saved", file)\n for index, block in enumerate(data.get("content") or []):\n print("Content", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get("choices") or []:\n print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n for index, item in enumerate(data.get("output") or []):\n print("Output", index, json.dumps(item, ensure_ascii=False))\n if item.get("type") == "image_generation_call" and item.get("result"):\n save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n for ci, candidate in enumerate(data.get("candidates") or []):\n for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get("inlineData") or part.get("inline_data")\n if blob and blob.get("data"):\n mime = blob.get("mimeType") or blob.get("mime_type")\n suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\ncount=0\nwith Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n for chunk in client.models.generate_content_stream(model='gemini-3.7-flash-medium',contents="Explain observations and hypotheses in three sentences."):\n payload=chunk.to_json_dict()\n log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n save_result(payload,"stream-chunk-"+str(count))\n count+=1\njson yoki qo‘llab-quvvatlanadigan oqimli uzatish
Qaytarilgan har bir to‘liq javob, fayl va kontent qismini saqlang.
Funksiya chaqiruvlari, fikrlash imzolari va sarf ma’lumotlari bilan birga barcha nomzod javoblar va qismlarni saqlang; oqim qismlarini tartib bilan yig‘ing.
So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan.
| Maydon | Tur |
|---|---|
MaydonresponseId | Turstring |
MaydonmodelVersion | Turstring |
Maydoncandidates[].content.parts[] | Turtext|inlineData|functionCall|other part |
Maydoncandidates[].finishReason | Turstring |
MaydonusageMetadata | Turobject |
| 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. |
Ailoot gemini-3.7-flash-medium
Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.
Ingliz tilidagi texnik misol
Audit a staged document handoff\n\nReview this release plan: writer finishes at 10:00; reviewer needs 45 minutes after writing; publisher needs 20 minutes after approval; launch is fixed at 11:00. Can the plan meet launch? Give the earliest finish, the dependency that controls it and one change that would make the plan feasible without overlapping dependent work.A dependency timeline, a feasibility conclusion and one quantified schedule change.The calculation respects write-before-review-before-publication and checks the proposed change against 11:00.