AI의 모든 것,
하나의 워크스페이스

# TAVGA AI API 연동 예시 코드
# FastAPI + OpenAI 통합 엔드포인트

from fastapi import FastAPI, HTTPException
from openai import AsyncOpenAI
from redis import asyncio as aioredis
import hashlib

app = FastAPI(title="TAVGA API")
client = AsyncOpenAI()
redis = aioredis.from_url("redis://localhost")

async def get_cached_response(prompt: str):
    """Redis 캐싱으로 API 비용 최적화"""
    cache_key = f"tavga:{hashlib.md5(prompt.encode()).hexdigest()}"
    cached = await redis.get(cache_key)
    if cached:
        return cached.decode()
    return None

@app.post("/api/chat")
async def chat_endpoint(prompt: str, model: str = "gpt-4o"):
    # 캐시 확인
    cached = await get_cached_response(prompt)
    if cached:
        return {"response": cached, "cached": True}

    # OpenAI API 호출
    response = await client.chat.completions.create(
        model=model,
        messages=[{"role": "user", "content": prompt}],
        max_tokens=2048
    )
    result = response.choices[0].message.content

    # 캐시 저장 (TTL: 1시간)
    cache_key = f"tavga:{hashlib.md5(prompt.encode()).hexdigest()}"
    await redis.setex( cache_key, 3600, result)

    return {"response": result, "model": model}