main.py

import time
from fastapi import FastAPI, Request, HTTPException
from pydantic import BaseModel
from g4f.client import Client
import uvicorn

app = FastAPI()

API_PREFIX = "/"

# Middleware for logging request time
@app.middleware("http")
async def log_process_time(request: Request, call_next):
    start_time = time.time()
    response = await call_next(request)
    process_time = time.time() - start_time
    print(f"{request.method} {response.status_code} {request.url.path} {process_time*1000:.2f} ms")
    return response

# Request body model
class ChatCompletionRequest(BaseModel):
    model: str
    messages: list[dict]

@app.get("/")
async def root():
    return {"message": "API server running"}

@app.get("/ping")
async def ping():
    return {"message": "pong"}

@app.get(f"{API_PREFIX}v1/models")
async def get_models():
    return {
        "object": "list",
        "data": [
            {"id": "gpt-4o-mini", "object": "model", "owned_by": "ddg"},
            {"id": "claude-3-haiku", "object": "model", "owned_by": "ddg"},
            {"id": "llama-3.1-70b", "object": "model", "owned_by": "ddg"},
            {"id": "mixtral-8x7b", "object": "model", "owned_by": "ddg"},
            {"id": "o3-mini", "object": "model", "owned_by": "ddg"},
        ],
    }

@app.post(f"{API_PREFIX}v1/chat/completions")
async def chat_completions(request: ChatCompletionRequest):
    try:
        # Only using DuckAI directly
        content = " ".join([msg.get("content", "") for msg in request.messages])
        
        client = Client()
        response = client.chat.completions.create(
            model=request.model,
            messages=[{"role": "user", "content": content}],
            web_search=False
        )
        
        return response

    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

if __name__ == "__main__":
    uvicorn.run("app:app", host="0.0.0.0", port=7860, reload=True)