Update app.py

app.py

@@ -6,7 +6,7 @@ from fastapi.middleware.cors import CORSMiddleware
 
 app = FastAPI()
 
-# Enable CORS so your website can talk to your backend
+# This allows your index.html to talk to your Python backend
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -14,11 +14,10 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+# Pulls your secret token from the 'Settings' vault
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
-# IMPORTANT: Replace 'NAME_OF_YOUR_MODEL' with your actual model name
-# Example: "https://api-inference.huggingface.co/models/google/gemma-2b"
-# If your model is danosethrus/EthioDoc, put that here:
+# TARGET: Your actual Model (without the 's')
 MODEL_URL = "https://api-inference.huggingface.co/models/danosethrus/EthioDoc"
 
 @app.get("/", response_class=HTMLResponse)
@@ -26,23 +25,34 @@ async def home():
     try:
         with open("index.html") as f:
             return f.read()
-    except:
-        return "index.html not found in Files tab!"
+    except FileNotFoundError:
+        return "Error: index.html not found in Files tab!"
 
 @app.post("/ask")
 async def ask_ai(request: Request):
-    data = await request.json()
+    user_data = await request.json()
     
     headers = {
         "Authorization": f"Bearer {HF_TOKEN}",
         "Content-Type": "application/json"
     }
 
-    # We send the question to the AI
-    response = requests.post(MODEL_URL, headers=headers, json=data)
-    
-    # Debugging logs
-    print(f"Status: {response.status_code}")
-    print(f"Body: {response.text}")
+    # 'wait_for_model' is the key: it prevents 503 errors while the brain loads
+    payload = {
+        "inputs": user_data.get("inputs", ""),
+        "options": {"wait_for_model": True}
+    }
 
-    return JSONResponse(content=response.json(), status_code=response.status_code)
+    try:
+        response = requests.post(MODEL_URL, headers=headers, json=payload, timeout=60)
+        
+        # This helps you see the result in the 'Logs' tab
+        print(f"DEBUG: Status {response.status_code}")
+        print(f"DEBUG: Response {response.text}")
+
+        # If everything is okay, send the AI answer back to the website
+        return JSONResponse(content=response.json(), status_code=response.status_code)
+
+    except Exception as e:
+        print(f"CRITICAL ERROR: {str(e)}")
+        return JSONResponse({"error": "The bridge is broken. Check Logs."}, status_code=500)