Source: https://ailoot.ai/models/uz/nvidia-riva-translate-4b-instruct-v1-1/ Canonical: https://ailoot.ai/models/uz/nvidia-riva-translate-4b-instruct-v1-1/ Language: uz # Riva Translate 4B Instruct v1.1 [Markdown](https://ailoot.ai/models/uz/nvidia-riva-translate-4b-instruct-v1-1/index.md) · [JSON](https://ailoot.ai/models/uz/nvidia-riva-translate-4b-instruct-v1-1/facts.json) ## [Riva Translate 4B Instruct v1.1](https://ailoot.ai/models/uz/nvidia-riva-translate-4b-instruct-v1-1/) NVIDIA’ning Riva-Translate-4B-Instruct-v1.1 modeli gaplar va hujjatlarni ingliz tili bilan boshqa 11 til va mintaqaviy variant, jumladan, rus tili o‘rtasida tarjima qiladi. So‘rovda tarjima misollari va 8K tokengacha kontekstni qo‘llab-quvvatlaydi. - [**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `nvidia/riva-translate-4b-instruct-v1.1`](https://ailoot.ai/models/uz/nvidia-riva-translate-4b-instruct-v1-1/#method-0) Model haqida Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan. Riva-Translate-4B-Instruct-v1.1 — yozma tarjima uchun NVIDIA’ning ixtisoslashgan modeli. U alohida gaplar va hujjatlar bilan ishlaydi: matnni qabul qiladi va tanlangan tilda matn qaytaradi. Bunday format ko‘p tilli materiallar tayyorlaydigan tarjimonlar, marketologlar va dasturchilarga mos keladi. #### Tillar va mintaqaviy variantlar Modelda 12 til va variant ko‘zda tutilgan: ingliz, nemis, Yevropa va Lotin Amerikasi ispan, fransuz, Braziliya portugal, rus, soddalashtirilgan va an’anaviy yozuvli xitoy, yapon, koreys va arab. Ispan va xitoy tillari uchun kerakli variantni alohida ko‘rsatish mumkin, portugal tili esa bu versiyada Braziliya varianti bilan taqdim etilgan. Tarjima yo‘nalishlari ingliz tili atrofida belgilangan: ingliz tilidan sanab o‘tilgan tillarga va aksincha. Ruscha matn uchun ingliz tiliga, inglizcha matn uchun esa rus tiliga tarjima ko‘zda tutilgan. Mintaqaviy tur yo‘nalish tanloviga kiradi, shuning uchun uni til bilan birga ko‘rsatish yaxshiroq. #### Tarjima qanday beriladi So‘rovda tarjima yo‘nalishi va materialning o‘zi ajratiladi. Tizim xabari til juftligini belgilaydi, foydalanuvchi xabari boshlang‘ich matnni o‘z ichiga oladi. Masalan, `en-ru` ingliz tilidan rus tiliga, `ru-en` esa rus tilidan ingliz tiliga tarjimani belgilaydi. Yevropa ispan tili uchun `en-es-es`, Lotin Amerikasi varianti uchun `en-es-us`; Braziliya portugal tili uchun esa `en-pt-br` ko‘zda tutilgan. So‘rov doirasida bir nechta tarjima misolini yuborish mumkin. Suhbat shabloni foydalanuvchi matni va tarjimali javobning almashib kelishini qo‘llab-quvvatlaydi. Bu navbatdagi materialdan oldin boshlang‘ich va tarjima qilingan matn juftligini ko‘rsatishga imkon beradi. NVIDIA model qo‘shimcha o‘qitilgan tarjima shablonidan foydalanishni tavsiya etadi: u boshlang‘ich va maqsad tillarini aniq belgilaydi. #### Kontekst va tuzilish Model taxminan to‘rt milliard parametrni o‘z ichiga oladi va dekoderli Transformer sifatida qurilgan. Bazaviy model siqish va distillyatsiya orqali olingan, keyin matnda qo‘shimcha o‘qitish, misollar orqali o‘qitish va afzalliklarni hisobga olgan optimallashtirishdan o‘tgan. Kontekst 8K tokengacha. #### Tarjimaga nima ta’sir qiladi Sifat mavzu, vazifa shartlari, boshlang‘ich matndagi shovqin va mavjud kontekstga bog‘liq. Javobda grammatik xatolar va mazmuniy xatolar bo‘lishi mumkin. So‘rovni aniqlashtirish mosroq tarjima olishga yordam berishi mumkin. Amaliy vazifa ### Amaliy vazifa Ingliz tilidagi texnik misol ``` Translate a collection notice into Russian Translation direction: English to Russian, en-ru. Translate this notice: 'Your repaired kettle is ready for collection at the service desk. Please bring receipt R-204. We will keep it until Friday at 18:00.' Preserve the receipt identifier and the collection deadline. Return only the translated notice. ``` #### Kutiladigan natija ``` A Russian translation preserving the service-desk location, R-204 and Friday 18:00 deadline. ``` #### Natijani tekshirish ``` The translation must not turn the collection deadline into the repair completion time. ``` **Ailoot · OpenAI Chat** `POST /v1/chat/completions` `nvidia/riva-translate-4b-instruct-v1.1` [`nvidia/riva-translate-4b-instruct-v1.1`](https://ailoot.ai/models/uz/#m=nvidia%2Friva-translate-4b-instruct-v1.1&route=Core&caller=nvidia%2Friva-translate-4b-instruct-v1.1&fmt=chat) NVIDIA /`nvidia/riva-translate-4b-instruct-v1.1` ### Boshlash NVIDIA’ning Riva-Translate-4B-Instruct-v1.1 modeli gaplar va hujjatlarni ingliz tili bilan boshqa 11 til va mintaqaviy variant, jumladan, rus tili o‘rtasida tarjima qiladi. So‘rovda tarjima misollari va 8K tokengacha kontekstni qo‘llab-quvvatlaydi. Qabul qilinadigan kirish ma’lumotlari Matn Natijalar Matn ### Ailoot da mavjud · kirish ma’lumotlari va usullar **Ailoot · OpenAI Chat** `POST /v1/chat/completions` Kirish `text` Chiqish `text` Kontekst 4 096 tokens Eng katta chiqish 1 024 tokens Chiqish formati json yoki SSE | Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart | | --- | --- | --- | --- | --- | | Maydon`model` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar nvidia/riva-translate-4b-instruct-v1.1 | 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` Usul parametrlari va hayot sikli | Parametr | Parametr talablari | | --- | --- | | Parametr`material_types` | Parametr talablaritext | | 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 0,0001 US$ */ 1K* Chiqish 0,0002 US$ */ 1K* Keshdan o‘qish 0,0001 US$ */ 1K* Keshga yozish 0,0001 US$ */ 1K* Keshga yozish, 5 daqiqa 0,0001 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 namunasiPython 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": "nvidia/riva-translate-4b-instruct-v1.1", "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 ``` ```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="nvidia/riva-translate-4b-instruct-v1.1", 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: "nvidia/riva-translate-4b-instruct-v1.1", 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='nvidia/riva-translate-4b-instruct-v1.1',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** [`nvidia/riva-translate-4b-instruct-v1.1`](https://ailoot.ai/models/uz/#m=nvidia%2Friva-translate-4b-instruct-v1.1&route=Core&caller=nvidia%2Friva-translate-4b-instruct-v1.1&fmt=chat) #### Usul yo‘llari taxalluslari Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning. #### Chaqirish uchun tegishli ID lar [`nvidia/riva-translate-4b-instruct-v1.1`](https://ailoot.ai/models/uz/#m=nvidia%2Friva-translate-4b-instruct-v1.1&route=Core&caller=nvidia%2Friva-translate-4b-instruct-v1.1&fmt=chat) FAQ · nvidia/riva-translate-4b-instruct-v1.1 Qanday kirish ma’lumotlari va natijalar mavjud? `POST /v1/chat/completions` · `nvidia/riva-translate-4b-instruct-v1.1`: `text` → `text` So‘rov qaysi maydonlardan foydalanadi? `POST /v1/chat/completions` · `nvidia/riva-translate-4b-instruct-v1.1`: `model`, `messages`, `stream` Qanday cheklovlar amal qiladi? `POST /v1/chat/completions` · `nvidia/riva-translate-4b-instruct-v1.1`: `ctx`: `4096`; `max_out`: `1024`; `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.