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import os
import time
import random
import asyncio
import json
from fastapi import FastAPI, HTTPException, Depends
from fastapi.middleware.cors import CORSMiddleware
from fastapi.security.api_key import APIKeyHeader
from pydantic import BaseModel, Field, field_validator
from typing import List, Optional
from dotenv import load_dotenv
from starlette.responses import StreamingResponse
from openai import OpenAI
from typing import List, Optional, Type
load_dotenv()
API_KEYS = [
os.getenv("API_GEMINI_1"),
os.getenv("API_GEMINI_2"),
os.getenv("API_GEMINI_3")
]
BASE_URL = os.getenv("BASE_URL", "https://generativelanguage.googleapis.com/v1beta/openai/")
EXPECTED_API_KEY = os.getenv("EXPECTED_API_KEY", "1234")
API_KEY_NAME = "Authorization"
api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)
app = FastAPI(title="OpenAI-SDK-compatible API", version="1.0.0", description="Un wrapper FastAPI compatibile con le specifiche dell'API OpenAI.")
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
class Message(BaseModel):
role: str
content: str
class ChatCompletionRequest(BaseModel):
model: str = "gemini-2.0-flash"
messages: List[Message]
max_tokens: Optional[int] = 8196
temperature: Optional[float] = 0.8
stream: Optional[bool] = False
def verify_api_key(api_key: str = Depends(api_key_header)):
if not api_key:
raise HTTPException(status_code=403, detail="API key mancante")
if api_key != f"Bearer {EXPECTED_API_KEY}":
raise HTTPException(status_code=403, detail="API key non valida")
return api_key
def get_openai_client():
api_key = random.choice(API_KEYS)
return OpenAI(api_key=api_key, base_url=BASE_URL)
def call_api_sync(params: ChatCompletionRequest):
try:
client = get_openai_client()
print(params)
response = client.chat.completions.create(
model=params.model,
messages=[m.model_dump() for m in params.messages],
max_tokens=params.max_tokens,
temperature=params.temperature,
stream=params.stream
)
return response
except Exception as e:
if "429" in str(e):
time.sleep(2)
return call_api_sync(params)
else:
raise e
async def _resp_async_generator(params: ChatCompletionRequest):
client = get_openai_client()
try:
response = client.chat.completions.create(
model=params.model,
messages=[m.model_dump() for m in params.messages],
max_tokens=params.max_tokens,
temperature=params.temperature,
stream=True
)
for chunk in response:
chunk_data = chunk.to_dict() if hasattr(chunk, "to_dict") else chunk
yield f"data: {json.dumps(chunk_data)}\n\n"
await asyncio.sleep(0.01)
yield "data: [DONE]\n\n"
except Exception as e:
error_data = {"error": str(e)}
yield f"data: {json.dumps(error_data)}\n\n"
@app.get("/health")
async def health_check():
return {"message": "success"}
@app.post("/v1/chat/completions", dependencies=[Depends(verify_api_key)])
async def chat_completions(req: ChatCompletionRequest):
if not req.messages:
raise HTTPException(status_code=400, detail="Nessun messaggio fornito")
if req.stream:
return StreamingResponse(
_resp_async_generator(req),
media_type="application/x-ndjson"
)
else:
try:
response = call_api_sync(req)
return response
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.get("/")
def read_general():
return {"response": "Benvenuto"}
if __name__ == "__main__":
import uvicorn
uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)
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