Update app.py

app.py

@@ -136,13 +136,22 @@ def check_environment():
         return False
 
 @st.cache_resource
-def initialize_model():
-    """Initialize the model with proper error handling and verification"""
+def initialize_model(self):
+    """Initialize the model with proper error handling and verification
+    
+    Returns:
+        Llama: Initialized model instance
+        
+    Raises:
+        FileNotFoundError: If model file cannot be found or downloaded
+        ValueError: If model file is corrupted or too small
+        RuntimeError: If model initialization fails
+    """
     try:
         if not os.path.exists(self.model_path):
             direct_url = "https://huggingface.co/TheBloke/Mistral-7B-v0.1-GGUF/resolve/main/mistral-7b-v0.1.Q4_K_M.gguf"
             download_file_with_progress(direct_url, self.model_path)
-
+            
         # Verify file exists and has content
         if not os.path.exists(self.model_path):
             raise FileNotFoundError(f"Model file {self.model_path} not found after download attempts")
@@ -150,17 +159,28 @@ def initialize_model():
         if os.path.getsize(self.model_path) < 1000000:  # Less than 1MB
             os.remove(self.model_path)
             raise ValueError("Downloaded model file is too small, likely corrupted")
-
-    
-    llm_config = {
-        "n_ctx": 2048,
-        "n_threads": 4,
-        "n_batch": 512,
-        "n_gpu_layers": 0,
-        "verbose": False
-    }
-    
-    return Llama(model_path=model_path, **llm_config)
+            
+        llm_config = {
+            "n_ctx": 2048,
+            "n_threads": 4,
+            "n_batch": 512,
+            "n_gpu_layers": 0,
+            "verbose": False
+        }
+        
+        return Llama(model_path=self.model_path, **llm_config)
+        
+    except FileNotFoundError as e:
+        logging.error(f"Failed to find or download model file: {str(e)}")
+        raise
+        
+    except ValueError as e:
+        logging.error(f"Model file validation failed: {str(e)}")
+        raise
+        
+    except Exception as e:
+        logging.error(f"Unexpected error during model initialization: {str(e)}")
+        raise RuntimeError(f"Failed to initialize model: {str(e)}") from e
 
 
 class SentenceTransformerRetriever: