خروجی ساختاریافته (JSON)

import json

schema = {
    "type": "object",
    "additionalProperties": False,
    "required": ["name", "price", "tags"],
    "properties": {
        "name": {"type": "string"},
        "price": {"type": "number", "description": "USD"},
        "tags": {"type": "array", "items": {"type": "string"}},
    },
}

reply = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "Extract product data from the text."},
        {"role": "user", "content": "The new ergonomic keyboard costs 49.90 dollars; wireless, backlit."},
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {"name": "product", "strict": True, "schema": schema},
    },
)

product = json.loads(reply.choices[0].message.content)
print(product["name"], product["price"])

# The openai SDK can build the schema from a Pydantic model and parse the answer for you.
from pydantic import BaseModel

class Product(BaseModel):
    name: str
    price: float
    tags: list[str]

# older SDK versions: client.beta.chat.completions.parse(...)
completion = client.chat.completions.parse(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "The new ergonomic keyboard costs 49.90 dollars; wireless, backlit."}],
    response_format=Product,
)
product = completion.choices[0].message.parsed   # a Product instance

import { z } from "zod";
import { zodResponseFormat } from "openai/helpers/zod";

const Product = z.object({ name: z.string(), price: z.number(), tags: z.array(z.string()) });

// older SDK versions: client.beta.chat.completions.parse(...)
const completion = await client.chat.completions.parse({
  model: "gpt-4o-mini",
  messages: [{ role: "user", content: "The new ergonomic keyboard costs 49.90 dollars; wireless, backlit." }],
  response_format: zodResponseFormat(Product, "product"),
});
console.log(completion.choices[0].message.parsed);

curl https://gisoo.pro/api/v1/chat/completions \
  -H "Authorization: Bearer $GISOO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [
      {"role": "system", "content": "Return JSON with keys sentiment (positive|neutral|negative) and reason."},
      {"role": "user", "content": "The delivery was late but support fixed it fast."}
    ],
    "response_format": {"type": "json_object"}
  }'

# pip install jsonschema — never trust an answer blindly, even in JSON mode
import json
from jsonschema import validate, ValidationError

def ask_json(messages, schema, retries=2):
    for _ in range(retries + 1):
        reply = client.chat.completions.create(
            model="gemini-3.6-flash",
            messages=messages,
            response_format={"type": "json_object"},
        )
        try:
            data = json.loads(reply.choices[0].message.content)
            validate(data, schema)
            return data
        except (json.JSONDecodeError, ValidationError) as err:
            messages = messages + [{"role": "user", "content": f"Your last answer was invalid ({err}). Reply with valid JSON only."}]
    raise RuntimeError("no valid JSON")