结构化输出：让模型结果经过 Schema 和 Pydantic 验证

python -m pip install "pydantic>=2,<3"

import json
from typing import Literal
from pydantic import BaseModel, Field, ValidationError


class EventSummary(BaseModel):
    device_id: str = Field(min_length=1, max_length=32)
    level: Literal["info", "warning", "critical"]
    summary: str = Field(min_length=1, max_length=60)
    needs_review: bool


def parse_result(raw: str) -> dict:
    try:
        data = json.loads(raw)
        value = EventSummary.model_validate(data)
        return {"ok": True, "value": value.model_dump(), "raw": raw, "error": None}
    except (json.JSONDecodeError, ValidationError) as error:
        return {"ok": False, "value": None, "raw": raw, "error": str(error)}


print(parse_result(
    '{"device_id":"AX-3","level":"warning",'
    '"summary":"温度偏高，等待复核","needs_review":true}'
))
print(parse_result('{"device_id":"AX-3","level":"high"}'))

from langchain_openai import ChatOpenAI

model = ChatOpenAI(model="provider-model-name")
structured_model = model.with_structured_output(EventSummary)
result = structured_model.invoke("设备 AX-3 温度偏高，尚未复核。")
print(result.model_dump())

{"ok":false,"raw":"...","error_type":"schema_validation","attempt":1}