Update app.py

app.py

@@ -68,34 +68,49 @@ else:
 
 # Function to upload document
 def upload_document(file_path, embed_model):
-    # Generate unique document ID
-    doc_id = uuid.uuid4().int % (2**63 - 1)
-    
-    # Ensure the file is saved to the correct directory with secure handling
-    file_location = os.path.join(UPLOAD_DIR, os.path.basename(file_path))
-    
-    # Safely copy the file to the upload directory
-    shutil.copy(file_path, file_location)
-    
-    # Read the content of the uploaded file
     try:
-        with open(file_location, "r", encoding="utf-8") as f:
-            text = f.read()
-    except Exception as e:
-        print(f"Error reading file {file_location}: {e}")
-        return
-    
-    # Embed the text and add it to the FAISS index
-    try:
-        vector = embed_model.encode(text).astype("float32")
-        index.add_with_ids(np.array([vector]), np.array([doc_id], dtype=np.int64))
-        document_store[doc_id] = {"path": file_location, "text": text}
+        # Generate unique document ID
+        doc_id = uuid.uuid4().int % (2**63 - 1)
+        
+        # Ensure the file is saved to the correct directory with secure handling
+        file_location = os.path.join(UPLOAD_DIR, os.path.basename(file_path))
         
-        # Save the FAISS index after adding the document
-        faiss.write_index(index, faiss_index_file)
-        print(f"Document uploaded with doc_id: {doc_id}")
+        # Safely copy the file to the upload directory
+        shutil.copy(file_path, file_location)
+        
+        # Read the content of the uploaded file
+        try:
+            with open(file_location, "r", encoding="utf-8") as f:
+                text = f.read()
+        except Exception as e:
+            print(f"Error reading file {file_location}: {e}")
+            return {"error": f"Error reading file: {e}"}, 502  # Error while reading file
+        
+        # Embed the text and add it to the FAISS index
+        try:
+            # Ensure the embedding model is valid
+            if embed_model is None:
+                raise ValueError("Embedding model is not initialized properly.")
+            
+            vector = embed_model.encode(text).astype("float32")
+            index.add_with_ids(np.array([vector]), np.array([doc_id], dtype=np.int64))
+            document_store[doc_id] = {"path": file_location, "text": text}
+            
+            # Save the FAISS index after adding the document
+            try:
+                faiss.write_index(index, faiss_index_file)
+                print(f"Document uploaded with doc_id: {doc_id}")
+            except Exception as e:
+                print(f"Error saving FAISS index: {e}")
+                return {"error": f"Error saving FAISS index: {e}"}, 503  # Error while saving FAISS index
+            
+        except Exception as e:
+            print(f"Error during document upload: {e}")
+            return {"error": f"Error during document upload: {e}"}, 504  # Error during embedding or FAISS processing
+    
     except Exception as e:
-        print(f"Error during document upload: {e}")
+        print(f"Unexpected error: {e}")
+        return {"error": f"Unexpected error: {e}"}, 500  # General error
 
 @app.route("/list_uploads", methods=["GET"])
 def list_uploaded_files():