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AI/참고/instructor-main/examples/logfire-fastapi/server.py

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2026-05-12 19:40:31 +09:00
from pydantic import BaseModel
from fastapi import FastAPI
from openai import AsyncOpenAI
import instructor
import logfire
import asyncio
from collections.abc import Iterable
from fastapi.responses import StreamingResponse
class UserData(BaseModel):
query: str
class MultipleUserData(BaseModel):
queries: list[str]
class UserDetail(BaseModel):
name: str
age: int
app = FastAPI()
openai_client = AsyncOpenAI()
logfire.configure(pydantic_plugin=logfire.PydanticPlugin(record="all"))
logfire.instrument_fastapi(app)
logfire.instrument_openai(openai_client)
client = instructor.from_openai(openai_client)
@app.post("/user", response_model=UserDetail)
async def endpoint_function(data: UserData) -> UserDetail:
user_detail = await client.chat.completions.create(
model="gpt-3.5-turbo",
response_model=UserDetail,
messages=[
{"role": "user", "content": f"Extract: `{data.query}`"},
],
)
logfire.info("/User returning", value=user_detail)
return user_detail
@app.post("/many-users", response_model=list[UserDetail])
async def extract_many_users(data: MultipleUserData):
async def extract_user(query: str):
user_detail = await client.chat.completions.create(
model="gpt-3.5-turbo",
response_model=UserDetail,
messages=[
{"role": "user", "content": f"Extract: `{query}`"},
],
)
logfire.info("/User returning", value=user_detail)
return user_detail
coros = [extract_user(query) for query in data.queries]
return await asyncio.gather(*coros)
@app.post("/extract", response_class=StreamingResponse)
async def extract(data: UserData):
supressed_client = AsyncOpenAI()
logfire.instrument_openai(supressed_client, suppress_other_instrumentation=False)
client = instructor.from_openai(supressed_client)
users = await client.chat.completions.create(
model="gpt-3.5-turbo",
response_model=Iterable[UserDetail],
stream=True,
messages=[
{"role": "user", "content": data.query},
],
)
async def generate():
with logfire.span("Generating User Response Objects"):
async for user in users:
resp_json = user.model_dump_json()
logfire.info("Returning user object", value=resp_json)
yield resp_json
return StreamingResponse(generate(), media_type="text/event-stream")