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Ulanish

Google GenAI SDK

Markdown

Gemini’ning o‘z formati: Python va JavaScript uchun Google GenAI SDK’si va bevosita REST so‘rovlari.

To‘liq qo‘llanma

O‘rnatish

pip install google-genai

Ulanish

Manzil — https://api.ailoot.ai quyidagisiz /v1beta: SDK quyidagi yo‘lni yig‘adi: /v1beta/models/<model>:generateContent o‘zi. Python’da manzil quyidagicha beriladi: HttpOptions(base_url=…), JavaScript’da esa quyidagicha: httpOptions.baseUrl. SDK kalitni quyidagi sarlavhada yuboradi: x-goog-api-key.

from google import genai
from google.genai import types
import os

client = genai.Client(
    api_key=os.environ["AILOOT_API_KEY"],
    http_options=types.HttpOptions(base_url="https://api.ailoot.ai"),  # /v1beta’siz
)

resp = client.models.generate_content(
    model="gemini-3.8-flash",
    contents="Qahvaxona uchun uchta nom o‘ylab toping.",
)
print(resp.text)

Nimalarni yuborish mumkin

  • Yuqori darajadagi maydonlar: contents, systemInstruction, generationConfig, safetySettings, tools va toolConfig.
  • generationConfig qabul qiladi: temperature, topP, topK, maxOutputTokens, thinkingConfig, responseMimeType (text/plain yoki application/json), responseSchema yoki responseJsonSchema (JSON obyekt), stopSequences (satrlar massivi), candidateCount: 1, butun sonli seed, sonli presencePenalty va frequencyPenalty. Ruxsat etilgan oraliqlar va imkoniyatlar aniq modelga bog‘liq; JSON javob uchun qo‘llab-quvvatlanadigan sxema shakllaridan bittasini va quyidagini tanlang: application/json. Matn modellarida responseModalities — faqat ["TEXT"].
  • safetySettings — quyidagi maydonli obyektlar massivi: category, threshold va ixtiyoriy maydon: method; qiymatlarni aynan shu model hujjatlariga qarab tanlang.
  • Tegishli kirish turini qo‘llab-quvvatlaydigan Gemini modellarida parts[].inlineData quyidagini o‘z ichiga oladi: mimeType va bo‘sh bo‘lmagan base64 ma’lumotlar; PDF haqiqiy PDF bo‘lishi kerak. fileData quyidagilarni o‘z ichiga oladi: ochiq https-manzilni quyidagi maydonda: fileUri va fayl turining MIME qiymatini. YouTube uchun MIME’ni ko‘rsatmaslik mumkin. http, yopiq manzillar, gs:// va Google Files API obyektlari qo‘llab-quvvatlanmaydi; Google Files API orqali yuklash ham qo‘llab-quvvatlanmaydi. Video uchun quyidagini qo‘shish mumkin: videoMetadata: startOffset/endOffset soniyalardagi satr ko‘rinishida (masalan, 1.5s) va fps 0 dan katta va 24 dan katta emas. Tana hajmi, kontekst, ruxsat etilgan kirish va javob limiti model hamda format bo‘yicha tekshiriladi.
  • Mijoz tomonidagi functionDeclarations ni ilovangiz bajaradi. Matn modellarida quyidagilar ham qabul qilinadi: {"googleSearch": {}} va {"urlContext": {}}: alohida yoki birga quyidagi massivda: tools. Google Search ham, URL context ham quyidagisi bilan birga ishlatilmaydi: functionDeclarations bitta so‘rovda. Chiqishda rasmlar uchun faqat mijoz funksiyalari mavjud. Boshqa ichki vositalar va explicit cache qo‘llab-quvvatlanmaydi. Search/URL context to‘liq kirish limiti uchun zaxira talab qilishi mumkin; haqiqiy toolUsePromptTokenCount kirish tokenlari sifatida hisobga olinadi.
  • Model maydonni, ilovani yoki vositalar birikmasini qo‘llab-quvvatlamasa, so‘rov zaxiradan oldin rad etiladi — hech narsa yechib olinmaydi. HTTP kodi quyidagicha bo‘ladi: 400 quyidagi qiymat bilan: status INVALID_ARGUMENT va quyidagi sinf bilan: invalid_request (quyidagi maydonda: ErrorInfo.reason — INVALID_REQUEST). Noto‘g‘ri JSON, yo‘l parametrlari xatolari va boshqa tekshiruvlar ham quyidagi kodni qaytaradi: 400; xato matni va Request ID’ni o‘qing. Imkoniyatlar modelga bog‘liq: uning formatlari va kirishlarini katalogda tekshiring.
KirishQo‘llab-quvvatlanadigan MIME
Inline rasmlarimage/png, image/jpeg, image/webp
Hujjatlarapplication/pdf; text/plain, text/html, text/css, text/csv, text/xml, text/rtf, text/markdown, text/javascript, application/x-javascript, text/x-python, application/x-python
Audioaudio/wav, audio/mp3, audio/mpeg, audio/aiff, audio/aac, audio/ogg, audio/flac
Videovideo/mp4, video/mpeg, video/mov, video/quicktime, video/avi, video/x-flv, video/mpg, video/webm, video/wmv, video/3gpp
import json, os, urllib.request

def generate(model, payload):
    req = urllib.request.Request(
        "https://api.ailoot.ai/v1beta/models/" + model + ":generateContent",
        data=json.dumps(payload).encode(),
        headers={"x-goog-api-key": os.environ["AILOOT_API_KEY"],
                 "Content-Type": "application/json"},
    )
    # Bir marta yuboring. Kutish vaqti tugasa, qayta urinishdan oldin foydalanish tarixidagi Request ID ni tekshiring.
    with urllib.request.urlopen(req, timeout=300) as response:
        print("Request ID:", response.headers.get("X-Request-ID"))
        return json.load(response)

import base64, pathlib, sys

# Haqiqiy mahalliy PDF, audio yoki video faylini va unga mos MIME turini ko‘rsating.
path, mime = pathlib.Path(sys.argv[1]), sys.argv[2]
payload = {"contents": [{"role": "user", "parts": [
    {"text": "Fayl mazmunini qisqacha bayon qiling."},
    {"inlineData": {"mimeType": mime,
                    "data": base64.b64encode(path.read_bytes()).decode()}},
]}]}
print(generate("gemini-3.8-flash", payload))
# Muqobil biriktirma: {"fileData": {"mimeType": mime, "fileUri": public_https_url}}
# Haqiqiy YouTube URL uchun: {"fileData": {"fileUri": youtube_url}}

Funksiyaning to‘liq sikli

Funksiya e’lonini yuboring, functionCall’ni oling, o‘z funksiyangizni bajaring, functionResponse’ni qaytaring va keyingi javobni so‘rang. Modelning butun content’ini, jumladan thoughtSignature’ni saqlang; imzoni o‘zingiz yaratmang.

import json, os, urllib.request

def generate(model, payload):
    req = urllib.request.Request(
        "https://api.ailoot.ai/v1beta/models/" + model + ":generateContent",
        data=json.dumps(payload).encode(),
        headers={"x-goog-api-key": os.environ["AILOOT_API_KEY"],
                 "Content-Type": "application/json"},
    )
    # Bir marta yuboring. Kutish vaqti tugasa, qayta urinishdan oldin foydalanish tarixidagi Request ID ni tekshiring.
    with urllib.request.urlopen(req, timeout=300) as response:
        print("Request ID:", response.headers.get("X-Request-ID"))
        return json.load(response)

tools = [{"functionDeclarations": [{
    "name": "multiply", "description": "Ikki sonni ko‘paytirish",
    "parameters": {"type": "object", "properties": {
        "a": {"type": "number"}, "b": {"type": "number"}},
        "required": ["a", "b"]},
}]}]
contents = [{"role": "user", "parts": [{"text": "Funksiya yordamida 7 ni 8 ga ko‘paytiring"}]}]
for turn in range(4):  # Vosita siklini cheklang; natijasi noaniq so‘rovni qayta yubormang.
    reply = generate("gemini-3.8-flash", {"contents": contents, "tools": tools})
    content = reply["candidates"][0]["content"]
    contents.append(content)  # BARCHA asl parts va thoughtSignature qiymatlarini o‘zgartirmasdan saqlang.
    results = []
    for part in content.get("parts", []):
        call = part.get("functionCall")
        if not call:
            continue
        if call["name"] != "multiply":
            raise ValueError("Unexpected function")
        args = call["args"]
        result = {"name": call["name"], "response": {"value": args["a"] * args["b"]}}
        if "id" in call:
            result["id"] = call["id"]
        results.append({"functionResponse": result})
    if not results:
        print(content)
        break
    contents.append({"role": "user", "parts": results})
else:
    raise RuntimeError("Tool loop limit reached")

Oqimli javob

for chunk in client.models.generate_content_stream(
    model="gemini-3.8-flash",
    contents="Dengiz ustidagi quyosh botishini tasvirlang",
):
    print(chunk.text, end="", flush=True)

Mavjud modellar

Gemini formatida 27 ta identifikator mavjud: gemini-3.8-flash, gemini-3.1-pro, gemini-pro-agent, gemini-3.8-flash-tiered, gemini-3.8-flash-medium, gemini-3.8-flash-low, gemini-3.8-flash-high, gemini-3.7-flash, gemini-3.7-flash-tiered, gemini-3.7-flash-medium, gemini-3.7-flash-low, gemini-3.7-flash-high, gemini-3.6-flash, gemini-3.6-flash-tiered, gemini-3.6-flash-medium, gemini-3.6-flash-low, gemini-3.6-flash-high, gemini-3.5-flash-lite, gemini-3.1-pro-preview, gemini-3.1-pro-low, gemini-3.1-pro-high, gemini-3.1-flash-lite, gemini-3-flash, gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-flash-thinking, gemini-2.5-flash-lite.

Gemini modellari Anthropic Messages formatida ham mavjud — faqat shu formatni qo‘llab-quvvatlaydigan mijoz dasturlari uchun qulay: Anthropic SDK.

Savollaringiz qoldimi? Request ID va tavsifni yuboring — tushunishga yordam beramiz.Yordam xizmatiga yozish