from fastapi import FastAPI, Request, HTTPException
import os
import requests
from typing import Dict, Any
from openai import OpenAI
import httpx
import time



app = FastAPI()

# Configuration de l'API d'inférence NVIDIA
BOT_USERNAME = "@DiscussionBot"
NVIDIA_API_URL = "https://integrate.api.nvidia.com/v1"
NVIDIA_API_KEY = os.getenv("NVIDIA_API_KEY")
MODEL = "mistralai/mixtral-8x7b-instruct-v0.1"

# Vérification de la clé API NVIDIA
if not NVIDIA_API_KEY:
    raise ValueError("NVIDIA_API_KEY environment variable is not set.")

# Vérification du jeton Hugging Face
HF_TOKEN = os.getenv("HF_TOKEN")
if not HF_TOKEN:
    raise ValueError("HF_TOKEN environment variable is not set.")

# Initialisation du client NVIDIA
try:
    client = OpenAI(
        base_url=NVIDIA_API_URL,
        api_key=NVIDIA_API_KEY,
        http_client=httpx.Client(proxies=None, timeout=30.0)
    )
except Exception as e:
    raise ValueError(f"Failed to initialize NVIDIA API client: {str(e)}")

@app.get("/")
async def root(request: Request) -> Dict[str, Any]:
    """
    Gère les requêtes GET et renvoie une réponse JSON simple.
    """
    return {
        "method": request.method,
        "host": request.headers.get("host", "unknown"),
        "user_agent": request.headers.get("user-agent", "unknown"),
        "query_test": request.query_params.get("test", None),
        "message": "Webhook server is running. Use POST to interact with the bot."
    }

@app.post("/")
async def webhook(request: Request) -> Dict[str, Any]:
    """
    Gère les requêtes POST des Webhooks pour traiter les commentaires mentionnant le bot.
    """
    try:
        if request.headers.get("X-Webhook-Secret") != os.getenv("WEBHOOK_SECRET"):
            raise HTTPException(status_code=400, detail="Secret incorrect")

        data = await request.json()
        event = data.get("event", {})

        if (
            event.get("action") == "create"
            and event.get("scope") == "discussion.comment"
            and BOT_USERNAME in data.get("comment", {}).get("content", "")
        ):
            # Préparation du prompt pour l'API NVIDIA
            messages = [
                {
                    "role": "user",
                    "content": f"Faites comme si vous étiez un robot qui répond aux discussions sur l'apprentissage automatique et répondez au commentaire suivant :\n{data['comment']['content']}"
                }
            ]

            # Requête à l'API NVIDIA
            try:
                completion = client.chat.completions.create(
                    model=MODEL,
                    messages=messages,
                    temperature=0.5,
                    top_p=1,
                    max_tokens=100,
                    stream=True
                )
                continuation_text = ""
                for chunk in completion:
                    if chunk.choices[0].delta.content is not None:
                        continuation_text += chunk.choices[0].delta.content
                continuation_text = continuation_text.strip()
                if not continuation_text:
                    raise ValueError("No text generated by NVIDIA API")
            except Exception as e:
                raise HTTPException(status_code=500, detail=f"Inference failed: {str(e)}")

            # Publication du commentaire avec gestion des nouvelles tentatives
            comment_url = data["discussion"]["url"]["api"] + "/comment"
            for attempt in range(5):  # 5 tentatives maximum
                try:
                    comment_response = requests.post(
                        comment_url,
                        headers={
                            "Authorization": f"Bearer {HF_TOKEN}",
                            "Content-Type": "application/json",
                        },
                        json={"comment": continuation_text},
                    )
                    comment_response.raise_for_status()
                    # Vérifier si la réponse contient "newMessage" (succès implicite)
                    if comment_response.json().get("newMessage"):
                        return {"success": True}
                    return {"success": True}
                except requests.exceptions.HTTPError as e:
                    if "429" in str(e) or "rate-limited" in str(e):
                        time.sleep((2 ** attempt) * 10)  # Backoff exponentiel plus long
                        continue
                    raise HTTPException(status_code=500, detail=f"Failed to post comment: {str(e)}")

            raise HTTPException(status_code=429, detail="Rate limit exceeded after retries")

        return {"success": False}

    except HTTPException as he:
        raise he
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Unexpected error: {str(e)}")

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