fix

main.py

@@ -26,6 +26,11 @@ except Exception as e:
 app = FastAPI()
 security = HTTPBearer()
 
+client = OpenAI(
+    api_key=config.HF_TOKEN,
+    base_url="https://s5jfvadty4tkdlkr.eu-west-1.aws.endpoints.huggingface.cloud/v1"
+)
+
 # --- UTILITY ---
 async def send_to_telegram(message: str):
     url = f"https://api.telegram.org/bot{config.TELEGRAM_BOT_TOKEN}/sendMessage"
@@ -77,46 +82,38 @@ async def root():
 async def extract_image(uid: str = Depends(verify_firebase_token), file: UploadFile = File(...)):
     await send_to_telegram(f"Nuova richiesta VLM da {uid}")
     
-    # 1. Leggi i bytes e convertili in Base64
+    # Leggi l'immagine e convertila in base64
     image_bytes = await file.read()
     encoded_image = base64.b64encode(image_bytes).decode('utf-8')
     
-    # 2. Prepara il payload esattamente come nella tua curl
-    payload = {
-        "model": "ggml-org/Qwen2.5-VL-7B-Instruct-GGUF",
-        "messages": [
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "image_url",
-                        "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}
-                    },
-                    {
-                        "type": "text",
-                        "text": "Describe this image in one sentence."
-                    }
-                ]
-            }
-        ],
-        "stream": True, # Ho impostato True come nella tua curl
-        "max_tokens": 100
-    }
-
-    async with httpx.AsyncClient(timeout=120.0) as client:
-        try:
-            # 3. Invio come JSON (corrisponde a -H "Content-Type: application/json")
-            response = await client.post(
-                config.HF_ENDPOINT_URL, 
-                headers={"Authorization": f"Bearer {config.HF_TOKEN}"},
-                json=payload  # 'json' imposta automaticamente Content-Type: application/json
-            )
-            response.raise_for_status()
-            return response.json()
-            
-        except Exception as e:
-            await send_to_telegram(f"🚨 Errore VLM: {str(e)}")
-            raise HTTPException(status_code=502, detail=str(e))
+    try:
+        # La chiamata all'API tramite il client OpenAI
+        response = client.chat.completions.create(
+            model="ggml-org/Qwen2.5-VL-7B-Instruct-GGUF",
+            messages=[
+                {
+                    "role": "user",
+                    "content": [
+                        {
+                            "type": "image_url",
+                            "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}
+                        },
+                        {
+                            "type": "text", 
+                            "text": "Describe this image in one sentence."
+                        }
+                    ]
+                }
+            ],
+            max_tokens=100
+        )
+        
+        # Ritorna il risultato
+        return response.choices[0].message.content
+        
+    except Exception as e:
+        await send_to_telegram(f"🚨 Errore VLM: {str(e)}")
+        raise HTTPException(status_code=502, detail=str(e))
 
 @app.post("/analyze-document")
 async def analyze_document(request: Request, uid: str = Depends(verify_firebase_token)):

requirements.txt

@@ -6,4 +6,5 @@ httpx
 python-magic
 # Aggiunto per il parsing PDF lato backend se necessario in futuro
 pymupdf
-uvloop
+uvloop
+openai