main.py

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("API_HUGGINGFACE")
API_KEY_NAME = "Authorization"

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

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=["*"],
)

       
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("/")
def read_general(): 
    return {"response": "Benvenuto"}

@app.get("/health")
async def health_check():
    return {"message": "success"}

# ---------------------------------- Generazione Testo ---------------------------------------

@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))