Source: https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/
Canonical: https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/
Language: uz

# Meta: Llama 3.3 70B Instruct

[Markdown](https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/index.md) · [JSON](https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/facts.json)

## [Meta: Llama 3.3 70B Instruct](https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/)

Llama 3.3 70B Instruct — Meta kompaniyasining yordamchi suhbatlari uchun ko‘p tilli matn modeli. U matn va kod yaratadi, ishlab chiqaruvchi ko‘rsatgan 128K kontekst hamda sakkiz qo‘llab-quvvatlanadigan tilga ega; shu bois hujjatlar bo‘yicha muloqot, qayta yozish va manbaga asoslangan izohlarga mos keladi.

- [**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/#method-0)
- [**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/meta-llama-llama-3-3-70b-instruct/#method-1)

Model haqida

Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.

Llama 3.3 70B Instruct — Meta kompaniyasining ko‘rsatmalarga moslab sozlangan, 70 milliard parametrli til modeli. U matnni qabul qiladi va matn yoki kod qaytaradi. Meta ushbu nashrni ko‘p tilli yordamchi muloqoti uchun loyihalashtirgan; ko‘rsatmalarga qanday javob berishini shakllantirish uchun nazoratli nozik sozlash va inson qayta aloqasi asosidagi mustahkamlovchi o‘qitishdan foydalanadi.

#### Ko‘p tilli suhbat tuzing

Ishlab chiqaruvchi qo‘llab-quvvatlanadigan tillar sifatida ingliz, nemis, fransuz, italyan, portugal, hind, ispan va tay tillarini sanaydi. Yakuniy javob tilini nomlang va izchil qolishi kerak bo‘lgan atamalarni bering. Mahsulot yordamchisi shu tillardan biridagi suhbatni qabul qilishi, mijoz so‘rovini aniqlashi va berilgan siyosat materiali asosida javob loyihasini yozishi mumkin.

Mahalliylashtirish uchun asl parcha, mo‘ljallangan auditoriya va lug‘atni bering. Qayta yozilgan parchani va undan keyin ma’no yoki ohangni o‘zgartiradigan tanlovlarning qisqa ro‘yxatini so‘rang. Mahsulot nomlari, identifikatorlar va miqdorlarni aniq saqlang. Bu muhim tafsilotlarni yo‘qotmasdan tekshiruvchi manba bilan solishtira oladigan materialni yaratadi.

#### Matn to‘plami asosida ishlang

Meta model uchun 128K kontekst oynasini ko‘rsatadi. Bu maydondan tegishli manba parchalari, avvalgi qarorlar va joriy savol uchun foydalaning. Modeldan taqqoslashni so‘rashdan oldin har bir hujjat yoki parchani belgilang. Hujjat bo‘yicha muloqot parcha ID lari bilan asoslangan javobni va berilgan material hal qilmaydigan masalalarning alohida ro‘yxatini so‘rashi mumkin.

Uzunroq suhbatda keyingi javobga ta’sir qiladigan qarorlarni saqlang va takroriy fon ma’lumotini olib tashlang. Muayyan natijani so‘rang: taqqoslash jadvali, tahrirlangan parcha, talablar ro‘yxati yoki nomlangan kod parchasining izohi. Aniq chiqish shakli ko‘rib chiqish uchun konkret obyekt beradi.

#### Kod va ilova vositalari

Modelning hujjatlashtirilgan chiqishlari kodni o‘z ichiga oladi. Kod yozish prompti interfeys, namunaviy kiruvchi qiymatlar va kutilgan chiqishlarni berishi, so‘ng amalga oshirishni siz nomlagan chekka holatlar testlari bilan birga so‘rashi mumkin. Uni qo‘shishdan oldin maqsadli loyihada ishga tushiring va tekshiring.

Meta ushbu ko‘rsatmalarga moslab sozlangan nashr uchun vosita chaqiruv formatlarini ham ko‘rsatadi. Bunday jarayonda tashqi ilova funksiyalarni ochadi, so‘ralgan chaqiruvni bajaradi va natijani suhbatga qaytaradi. Yakuniy javob haqiqiy dalildan foydalana olishi uchun natijalarni tegishli so‘rovga bog‘langan holda saqlang. Bu formatlar ishlab chiqaruvchining integratsiya xatti-harakatini tasvirlaydi; funksiyalarning o‘zi ilovaga tegishli.

Llama 3.3 — oflayn ma’lumot to‘plamida o‘qitilgan statik model. Javob joriy raqamlar, siyosatlar yoki qaydlarga bog‘liq bo‘lsa, ularni bering. Faqat matnli kiritmasi sababli o‘qiladigan parchalar ushbu nashr uchun mos dalildir.

Amaliy vazifa

### Amaliy vazifa

Ingliz tilidagi texnik misol

```
Localize a customer reply with fixed terms

Translate this support reply into Spanish for a customer, keeping product name ClearDesk and reference R-882 unchanged: 'We received your return request for ClearDesk. Please include reference R-882 in your reply. We will review the photos you already sent.' Use a polite conversational register, then briefly identify any tone choice.
```

#### Kutiladigan natija

```
A Spanish reply followed by a short note about the selected register.
```

#### Natijani tekshirish

```
ClearDesk and R-882 stay exact, and the reply does not ask the customer to resend photos.
```

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions` `meta-llama/llama-3.3-70b-instruct`

[`meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/#m=meta-llama%2Fllama-3.3-70b-instruct&route=Ultra&caller=meta-llama%2Fllama-3.3-70b-instruct&fmt=chat)

Meta /`meta-llama/llama-3.3-70b-instruct`

### Boshlash

Llama 3.3 70B Instruct — Meta kompaniyasining yordamchi suhbatlari uchun ko‘p tilli matn modeli. U matn va kod yaratadi, ishlab chiqaruvchi ko‘rsatgan 128K kontekst hamda sakkiz qo‘llab-quvvatlanadigan tilga ega; shu bois hujjatlar bo‘yicha muloqot, qayta yozish va manbaga asoslangan izohlarga mos keladi.

Qabul qilinadigan kirish ma’lumotlari

Matn

Natijalar

Matn

### Ailoot da mavjud · kirish ma’lumotlari va usullar

**Ailoot Ultra · OpenAI Chat** `POST /v1/chat/completions`

Kirish

`text`

Chiqish

`text`

Chiqish formati

json yoki SSE

| Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart |
| --- | --- | --- | --- | --- |
| Maydon`model` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar meta-llama/llama-3.3-70b-instruct | 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 function 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— |
| Maydon`modalities` | Tur`string[]` | TalabIxtiyoriy | Qiymatlar va cheklovlar text | Standart— |
| Maydon`provider` | Tur`object` | TalabIxtiyoriy | Qiymatlar va cheklovlar Shartlar: Ushbu Ultra matn marshrutida provider.options rad etiladi | Standart— |
| Maydon`cache_control.ttl` | Tur`string` | TalabIxtiyoriy | Qiymatlar va cheklovlar Shartlar: Haqiqiy prompt-kesh joylarida 1h rad etiladi | Standart— |

Kirish materiallari birikmalari

**Matn** · UTF8 matni

`messages[].content`

Usul parametrlari va hayot sikli

| Parametr | Parametr talablari |
| --- | --- |
| Parametr`content_type` | Parametr talablariapplication/json |
| Parametr`required` | Parametr talablarimodel, messages |
| Parametr`material_types` | Parametr talablaritext |
| Parametr`messages` | Parametr talablarirole/content tuzilishidagi xabarlar massivi |
| Parametr`file_material` | Parametr talablariHaqiqiy UTF-8 hujjati aynan matn sifatida kiritiladi; fayl IDsi faraz qilinmaydi |
| Parametr`optional_controls` | Parametr talablaristream, temperature, top\_p, stop, max\_tokens, max\_completion\_tokens, reasoning, response\_format, tools, tool\_choice |
| Parametr`control_scope` | Parametr talablariModelga xos; foydalanuvchi funksiya vositalari hostingdagi vositalardan farq qiladi |
| Parametr`output_modalities` | Parametr talablaritext |
| Parametr`hosted_operations` | Parametr talablarifalse |
| Parametr`multimodal_input_binding` | Parametr talablarinull |

Hayot sikli: `synchronous_or_streamed`

Aniq model IDsini messages bilan yuboring.

Kontekst uzunligi chiqishning yuqori chegarasi emas.

Matn fayli aynan matnni taqdim etishi mumkin; tasvir, audio va fayl obyekti kirishlari aniq bog‘lashni talab qiladi.

### Tariflar

Tarif ma’lumotlari so‘rov imkoniyatlarini qo‘shmaydi. Qo‘llab-quvvatlanadigan parametrlar tanlangan usulda ko‘rsatilgan.

Tezkor rejim

Standart tarif Tezkor rejim tanlanganda

Flex rejimi

Standart tarif flex rejimi tanlanganda

Maksimal fikrlash darajasi

Standart tarif Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda

#### Ailoot tariflari

#### Sozlamalar bo‘yicha narxlar

Har bir to‘lovni ko‘rsatilgan shartlarga moslang. Har bir muqobil sozlamalar to‘plami uchun bitta tarifdan foydalaning.

| Sozlama | Tariflar jadvali | Kontekst tokenlari soni bundan ko‘p | Kontekst tokenlari soni bundan oshmaydi, chegara kiradi | To‘lov |
| --- | --- | --- | --- | --- |
| SozlamaTokenlar uchun bazaviy tariflar | Tariflar jadvaliAsosiy tarif | Kontekst tokenlari soni bundan ko‘p— | Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q | To‘lov Kirish · Kirish tokenlari **$0.0018** / 1K token Chiqish · Chiqish tokenlari **$0.0018** / 1K token Kirish · Keshdan o‘qish **$0.00059** / 1K token Kirish · Keshga yozish **$0** / 1K token Kirish · Keshga yozish, 1 soat **—** / 1K token |
| SozlamaSo‘rov uzunligi bo‘yicha 1-daraja | Tariflar jadvali— | Kontekst tokenlari soni bundan ko‘p0 | Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q | To‘lov Kirish · Kirish tokenlari **$0.0018** / 1K token Chiqish · Chiqish tokenlari **$0.0018** / 1K token Kirish · Keshdan o‘qish **$0.00059** / 1K token Kirish · Keshga yozish **$0** / 1K token Kirish · Keshga yozish, 1 soat **—** / 1K token |

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 Ultra · OpenAI Chat

curlPython SDKPython oqimi

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
python3 - <<'PY_REQUEST'
import json,os
from pathlib import Path
p=json.loads('{"model": "meta-llama/llama-3.3-70b-instruct", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}')

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
r=json.loads(Path("result.json").read_text())
for x in r.get("choices",[]):
    if x.get("message",{}).get("content"): print(x["message"]["content"])
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)
result=client.chat.completions.create(model='meta-llama/llama-3.3-70b-instruct',messages=[{"role":"user","content":"Explain observations and hypotheses 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(result.to_dict(mode="json"))
```

```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='meta-llama/llama-3.3-70b-instruct',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 Ultra · 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 Ultra** [`meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/#m=meta-llama%2Fllama-3.3-70b-instruct&route=Ultra&caller=meta-llama%2Fllama-3.3-70b-instruct&fmt=chat)

#### Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

#### Chaqirish uchun tegishli ID lar

[`meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/#m=meta-llama%2Fllama-3.3-70b-instruct&route=Ultra&caller=meta-llama%2Fllama-3.3-70b-instruct&fmt=chat)

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages` `meta-llama/llama-3.3-70b-instruct`

[`meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/#m=meta-llama%2Fllama-3.3-70b-instruct&route=Ultra&caller=meta-llama%2Fllama-3.3-70b-instruct&fmt=messages)

Meta /`meta-llama/llama-3.3-70b-instruct`

### Boshlash

Llama 3.3 70B Instruct — Meta kompaniyasining yordamchi suhbatlari uchun ko‘p tilli matn modeli. U matn va kod yaratadi, ishlab chiqaruvchi ko‘rsatgan 128K kontekst hamda sakkiz qo‘llab-quvvatlanadigan tilga ega; shu bois hujjatlar bo‘yicha muloqot, qayta yozish va manbaga asoslangan izohlarga mos keladi.

Qabul qilinadigan kirish ma’lumotlari

Matn

Natijalar

json · sse

### Ailoot da mavjud · kirish ma’lumotlari va usullar

**Ailoot Ultra · Anthropic Messages** `POST /v1/messages`

Kirish

`text`

Chiqish

`json`, `sse`

Chiqish formati

JSON yoki SSE

| Maydon | Tur | Talab | Qiymatlar va cheklovlar | Standart |
| --- | --- | --- | --- | --- |
| Maydon`model` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar meta-llama/llama-3.3-70b-instruct | Standart— |
| Maydon`messages` | Tur`message[]` | TalabMajburiy | Qiymatlar va cheklovlar | Standart— |
| Maydon`messages[].role` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar user, assistant | Standart— |
| Maydon`messages[].content` | Tur`string` | TalabMajburiy | Qiymatlar va cheklovlar | Standart— |
| Maydon`max_tokens` | Tur`integer` | TalabMajburiy | Qiymatlar va cheklovlar | Standart— |
| Maydon`stream` | Tur`boolean` | TalabIxtiyoriy | Qiymatlar va cheklovlar | Standartfalse |

Kirish materiallari birikmalari

**Matn** · UTF-8 matni

`messages[].content satri`

Usul parametrlari va hayot sikli

| Parametr | Parametr talablari |
| --- | --- |
| Parametr`content_type` | Parametr talablariapplication/json |
| Parametr`required` | Parametr talablarimodel, messages, max\_tokens |
| Parametr`optional_controls` | Parametr talablaristream |
| Parametr`material_types` | Parametr talablaritext |
| Parametr`text_file_material` | Parametr talablariHaqiqiy UTF-8 hujjatini o‘qing va uning matnini ko‘rsatilgan kirish yoki xabar kontenti satriga joylashtiring. |

Hayot sikli: `synchronous_or_streamed`

### Tariflar

Tarif ma’lumotlari so‘rov imkoniyatlarini qo‘shmaydi. Qo‘llab-quvvatlanadigan parametrlar tanlangan usulda ko‘rsatilgan.

Tezkor rejim

Standart tarif Tezkor rejim tanlanganda

Flex rejimi

Standart tarif flex rejimi tanlanganda

Maksimal fikrlash darajasi

Standart tarif Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda

#### Ailoot tariflari

#### Sozlamalar bo‘yicha narxlar

Har bir to‘lovni ko‘rsatilgan shartlarga moslang. Har bir muqobil sozlamalar to‘plami uchun bitta tarifdan foydalaning.

| Sozlama | Tariflar jadvali | Kontekst tokenlari soni bundan ko‘p | Kontekst tokenlari soni bundan oshmaydi, chegara kiradi | To‘lov |
| --- | --- | --- | --- | --- |
| SozlamaTokenlar uchun bazaviy tariflar | Tariflar jadvaliAsosiy tarif | Kontekst tokenlari soni bundan ko‘p— | Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q | To‘lov Kirish · Kirish tokenlari **$0.0018** / 1K token Chiqish · Chiqish tokenlari **$0.0018** / 1K token Kirish · Keshdan o‘qish **$0.00059** / 1K token Kirish · Keshga yozish **$0** / 1K token Kirish · Keshga yozish, 1 soat **—** / 1K token |
| SozlamaSo‘rov uzunligi bo‘yicha 1-daraja | Tariflar jadvali— | Kontekst tokenlari soni bundan ko‘p0 | Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q | To‘lov Kirish · Kirish tokenlari **$0.0018** / 1K token Chiqish · Chiqish tokenlari **$0.0018** / 1K token Kirish · Keshdan o‘qish **$0.00059** / 1K token Kirish · Keshga yozish **$0** / 1K token Kirish · Keshga yozish, 1 soat **—** / 1K token |

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 Ultra · Anthropic Messages

To‘liq minimal JSON so‘rov tanasicurl · O‘zingizning UTF-8 hujjatingizdan foydalaningPython · Natijani to‘liq saqlang

```json
{
  "model": "meta-llama/llama-3.3-70b-instruct",
  "max_tokens": 128,
  "messages": [
    {
      "role": "user",
      "content": "Summarize the incident report."
    }
  ],
  "stream": false
}
```

```bash
set -eu
: "${AILOOT_API_KEY:?Set your Ailoot API key}"
: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"
export AILOOT_TEXT_FILE
python3 - <<'PY_REQUEST'
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'meta-llama/llama-3.3-70b-instruct', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
Path('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')
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

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
PY_RESULT
```

```python
import json, os
from pathlib import Path

source_file = Path(os.environ['AILOOT_TEXT_FILE'])
if not source_file.is_file():
    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')
text = source_file.read_text(encoding='utf-8')
if not text.strip():
    raise SystemExit('Choose a document containing text')
payload = {'model': 'meta-llama/llama-3.3-70b-instruct', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}
payload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\n\n' + text
from urllib.request import Request, urlopen
from urllib.error import HTTPError

api_key = os.environ['AILOOT_API_KEY']
if not api_key.strip():
    raise SystemExit('Set AILOOT_API_KEY before making a request')
headers = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}
headers['x-api-key'] = api_key
request = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')
try:
    with urlopen(request, timeout=120) as response:
        raw = response.read()
        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')
except HTTPError as error:
    Path('result.json').write_bytes(error.read())
    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')
    raise
Path('result.json').write_bytes(raw)
import json
from pathlib import Path

result = json.loads(Path('result.json').read_text(encoding='utf-8'))
print(json.dumps(result, ensure_ascii=False, indent=2))
```

### Natijalarni olish va saqlash

#### Ailoot Ultra · 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 Ultra** [`meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/#m=meta-llama%2Fllama-3.3-70b-instruct&route=Ultra&caller=meta-llama%2Fllama-3.3-70b-instruct&fmt=messages)

#### Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

#### Chaqirish uchun tegishli ID lar

[`meta-llama/llama-3.3-70b-instruct`](https://ailoot.ai/models/uz/#m=meta-llama%2Fllama-3.3-70b-instruct&route=Ultra&caller=meta-llama%2Fllama-3.3-70b-instruct&fmt=messages)

FAQ · Meta: Llama 3.3 70B Instruct

Qanday kirish ma’lumotlari va natijalar mavjud?

`POST /v1/chat/completions` · `meta-llama/llama-3.3-70b-instruct`: `text` → `text` `POST /v1/messages` · `meta-llama/llama-3.3-70b-instruct`: `text` → `json`, `sse`

So‘rov qaysi maydonlardan foydalanadi?

`POST /v1/chat/completions` · `meta-llama/llama-3.3-70b-instruct`: `model`, `messages`, `stream`, `modalities`, `provider` `POST /v1/messages` · `meta-llama/llama-3.3-70b-instruct`: `model`, `messages`, `max_tokens`, `stream`

Qanday cheklovlar amal qiladi?

`POST /v1/chat/completions` · `meta-llama/llama-3.3-70b-instruct`: `messages.min_items`: `1`

Ailoot’ni Claude Code, OpenCode, Hermes yoki ilovangizga ulang.

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Obuna

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