Source: https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/
Canonical: https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/
Language: uz

# Ising Calibration 1.5 31B

[Markdown](https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/index.md) · [JSON](https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/facts.json)

## [Ising Calibration 1.5 31B](https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/)

Ising Calibration 1.5 kvant kalibrlash grafiklarini tahlil qiladi va texnik tavsiflar, xulosalar hamda ajratib olingan parametrlarni tayyorlaydi.

- [**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `nvidia/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/#method-0)
- [**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `ising-calibration`](https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/#method-1)
- [**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `ising-calibration-latest`](https://ailoot.ai/models/uz/nvidia-ising-calibration-1-5-31b/#method-2)

Model haqida

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

#### Kvant tajribasining texnik tahlili

Ising Calibration 1.5 — kvant tizimlari tadqiqotchilari va kalibrlash muhandislari uchun NVIDIA’ning ixtisoslashgan multimodal modeli. U tajriba grafiklarini matnli topshiriq bilan birga tahlil qiladi.

#### Tahlilning oltita yo‘nalishi

- Grafik mazmunining texnik tavsifi.
- Tajriba bo‘yicha xulosa.
- Natija ahamiyatini baholash.
- Ma’lumotlarga moslashtirish sifatini tahlil qilish.
- Parametrlarni ajratib olish.
- Kalibrlash muvaffaqiyatini tasniflash.

#### Kirish va natija

Model matn va grafikli bitta yoki bir nechta rasmni ko‘zda tutadi. Tasvirlar PNG va JPEG formatlarida RGB rang ma’lumotlari bilan ifodalanadi. Javob — texnik matn: tavsif, xulosa, moslashtirish bahosi, ajratib olingan qiymatlar yoki tajriba muvaffaqiyati haqidagi qaror. U qurilmani bevosita boshqarishni ifodalamaydi.

#### Asos va topshiriq berish usullari

Zich arxitektura taxminan 31 mlrd parametrni o‘z ichiga oladi va tasvirlarni qayta ishlaydigan Gemma 4 31B asosida qurilgan. O‘qitish kvant kalibrlashning sintetik materiallariga yo‘naltirilgan.

Ko‘rgazmali misollarsiz tahlil va bir nechta tasvir misollari bilan vazifalar tavsiflangan. E’lon qilingan javob uzunliklari shunday misollar sozlamalariga tegishli; kontekstning mustaqil universal maksimumi ko‘rsatilmagan.

Tajriba xulosalari kalibrlashda ishlatilishidan oldin mutaxassis tekshiruvi uchun mo‘ljallangan. Vizual tahlil tasvirlarni qabul qiladigan metodni talab qiladi.

Amaliy vazifa

### Amaliy vazifa

Ingliz tilidagi texnik misol

```
Assess a text calibration fit record

Assess this quantum calibration record as text only. Detuning points in MHz: -1, 0, 1. Measured normalized signal: 0.20, 0.50, 0.80. Fitted values: 0.22, 0.49, 0.77. Report measured-minus-fit residuals and describe their pattern. Identify what uncertainty and acceptance information is missing before judging calibration quality; no chart or hardware access is provided.
```

#### Kutiladigan natija

```
A three-row residual table, a short fit-quality discussion and the missing information needed for a specialist conclusion.
```

#### Natijani tekshirish

```
Residuals are -0.02, 0.01 and 0.03; no calibration-success decision is asserted without criteria or uncertainty.
```

**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `nvidia/ising-calibration-1.5-31b`

[`nvidia/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat)

NVIDIA /`nvidia/ising-calibration-1.5-31b`

Model ID

- `nvidia/ising-calibration-1.5-31b`
- `ising-calibration`
- `ising-calibration-latest`

### Boshlash

Ising Calibration 1.5 kvant kalibrlash grafiklarini tahlil qiladi va texnik tavsiflar, xulosalar hamda ajratib olingan parametrlarni tayyorlaydi.

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/ising-calibration-1.5-31b | 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

0,0002 US$ */ 1K*

Chiqish

0,0002 US$ */ 1K*

Keshdan o‘qish

0,0002 US$ */ 1K*

Keshga yozish

0,0002 US$ */ 1K*

Keshga yozish, 5 daqiqa

0,0002 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/ising-calibration-1.5-31b", "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/ising-calibration-1.5-31b",
    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/ising-calibration-1.5-31b",
  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/ising-calibration-1.5-31b',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/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat), [`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat), [`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

#### Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

#### Chaqirish uchun tegishli ID lar

[`nvidia/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat), [`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat), [`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `ising-calibration`

[`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat)

NVIDIA /`ising-calibration`

Model ID

- `nvidia/ising-calibration-1.5-31b`
- `ising-calibration`
- `ising-calibration-latest`

### Boshlash

Ising Calibration 1.5 kvant kalibrlash grafiklarini tahlil qiladi va texnik tavsiflar, xulosalar hamda ajratib olingan parametrlarni tayyorlaydi.

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 ising-calibration | 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

0,0002 US$ */ 1K*

Chiqish

0,0002 US$ */ 1K*

Keshdan o‘qish

0,0002 US$ */ 1K*

Keshga yozish

0,0002 US$ */ 1K*

Keshga yozish, 5 daqiqa

0,0002 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": "ising-calibration", "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="ising-calibration",
    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: "ising-calibration",
  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='ising-calibration',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/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat), [`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat), [`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

#### Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

#### Chaqirish uchun tegishli ID lar

[`nvidia/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat), [`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat), [`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

**Ailoot · OpenAI Chat** `POST /v1/chat/completions` `ising-calibration-latest`

[`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

NVIDIA /`ising-calibration-latest`

Model ID

- `nvidia/ising-calibration-1.5-31b`
- `ising-calibration`
- `ising-calibration-latest`

### Boshlash

Ising Calibration 1.5 kvant kalibrlash grafiklarini tahlil qiladi va texnik tavsiflar, xulosalar hamda ajratib olingan parametrlarni tayyorlaydi.

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 ising-calibration-latest | 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

0,0002 US$ */ 1K*

Chiqish

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Keshdan o‘qish

0,0002 US$ */ 1K*

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### 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": "ising-calibration-latest", "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="ising-calibration-latest",
    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: "ising-calibration-latest",
  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='ising-calibration-latest',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/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat), [`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat), [`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

#### Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

#### Chaqirish uchun tegishli ID lar

[`nvidia/ising-calibration-1.5-31b`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=nvidia%2Fising-calibration-1.5-31b&fmt=chat), [`ising-calibration`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration&fmt=chat), [`ising-calibration-latest`](https://ailoot.ai/models/uz/#m=nvidia%2Fising-calibration-1.5-31b&route=Core&caller=ising-calibration-latest&fmt=chat)

FAQ · nvidia/ising-calibration-1.5-31b

Qanday kirish ma’lumotlari va natijalar mavjud?

`POST /v1/chat/completions` · `nvidia/ising-calibration-1.5-31b`: `text` → `text` `POST /v1/chat/completions` · `ising-calibration`: `text` → `text` `POST /v1/chat/completions` · `ising-calibration-latest`: `text` → `text`

So‘rov qaysi maydonlardan foydalanadi?

`POST /v1/chat/completions` · `nvidia/ising-calibration-1.5-31b`: `model`, `messages`, `stream` `POST /v1/chat/completions` · `ising-calibration`: `model`, `messages`, `stream` `POST /v1/chat/completions` · `ising-calibration-latest`: `model`, `messages`, `stream`

Qanday cheklovlar amal qiladi?

`POST /v1/chat/completions` · `nvidia/ising-calibration-1.5-31b`: `ctx`: `4096`; `max_out`: `1024`; `messages.min_items`: `1` `POST /v1/chat/completions` · `ising-calibration`: `ctx`: `4096`; `max_out`: `1024`; `messages.min_items`: `1` `POST /v1/chat/completions` · `ising-calibration-latest`: `ctx`: `4096`; `max_out`: `1024`; `messages.min_items`: `1`

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

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