app.py

import uvicorn
from fastapi import FastAPI, HTTPException
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
from pydantic import BaseModel
import requests
import os
import uuid

app = FastAPI()

# Token HF récupéré depuis les variables d'environnement (Secrets)
HF_TOKEN = os.environ.get("HF_TOKEN")
# NOUVELLE URL (router.huggingface.co)
API_URL = "https://router.huggingface.co/hf-inference/models/stabilityai/stable-diffusion-xl-base-1.0"

class ImageRequest(BaseModel):
    prompt: str

@app.post("/generate")
async def generate_image(request: ImageRequest):
    print(f"🎨 Génération (HF API) : {request.prompt}")
    
    if not HF_TOKEN:
        raise HTTPException(status_code=500, detail="Token HF manquant. Configurez le secret HF_TOKEN.")

    headers = {"Authorization": f"Bearer {HF_TOKEN}"}
    payload = {"inputs": request.prompt}
    
    try:
        response = requests.post(API_URL, headers=headers, json=payload)
        
        if response.status_code != 200:
            # On logue le contenu complet pour debug
            print(f"Erreur API: {response.text}")
            raise Exception(f"Erreur API HF ({response.status_code}): {response.text}")
            
        # L'API retourne l'image binaire
        image_bytes = response.content
        
        # Sauvegarde locale pour servir l'image
        filename = f"gen_{uuid.uuid4()}.png"
        with open(filename, "wb") as f:
            f.write(image_bytes)
            
        # URL absolue pour le frontend
        return {"image_url": f"/{filename}"}

    except Exception as e:
        print(f"❌ Erreur : {str(e)}")
        raise HTTPException(status_code=500, detail=str(e))

@app.get("/")
async def read_index():
    return FileResponse('index.html')

app.mount("/", StaticFiles(directory=".", html=True), name="static")

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