Update app.py

app.py

@@ -76,21 +76,48 @@ vector_store = None
 chain = None
 chat_history = []
 
-# Function to handle file uploads
+# Function to handle file uploads - FIXED to handle Gradio's file objects properly
 def upload_file(files):
-    for file in files:
-        file_path = os.path.join("documents", os.path.basename(file.name))
-        with open(file_path, "wb") as f:
-            f.write(file.read())
-    
-    global vector_store, chain
-    vector_store = process_documents()
-    chain = create_chain(vector_store)
-    
-    if chain is None:
-        return "Files uploaded and processed, but HuggingFace API token is missing. Set the environment variable to enable the chatbot."
-    
-    return "Files uploaded and processed successfully!"
+    try:
+        # Clear existing documents if we're uploading new ones
+        for f in os.listdir("documents"):
+            file_path = os.path.join("documents", f)
+            if os.path.isfile(file_path):
+                os.remove(file_path)
+        
+        # Handle the uploaded files
+        for file in files:
+            # Get file content and name
+            if hasattr(file, "name"):  # For standard file objects
+                file_name = os.path.basename(file.name)
+                if hasattr(file, "read"):
+                    content = file.read()
+                else:  # For NamedString objects
+                    content = file.decode('utf-8') if isinstance(file, bytes) else str(file)
+            else:  # For tuple format (file_name, file_data)
+                if isinstance(file, tuple) and len(file) >= 2:
+                    file_name = os.path.basename(file[0])
+                    content = file[1]
+                else:
+                    # If none of the above, try to handle as string with a default name
+                    file_name = f"document_{len(os.listdir('documents'))}.txt"
+                    content = str(file)
+            
+            # Write content to file
+            file_path = os.path.join("documents", file_name)
+            with open(file_path, "w", encoding='utf-8') as f:
+                f.write(content if isinstance(content, str) else content.decode('utf-8'))
+        
+        global vector_store, chain
+        vector_store = process_documents()
+        chain = create_chain(vector_store)
+        
+        if chain is None:
+            return "Files uploaded and processed, but HuggingFace API token is missing. Set the environment variable to enable the chatbot."
+        
+        return "Files uploaded and processed successfully!"
+    except Exception as e:
+        return f"Error processing files: {str(e)}"
 
 # Function to handle user queries
 def chat(message, history):
@@ -127,7 +154,7 @@ def chat(message, history):
         error_message = f"Error processing your request: {str(e)}"
         return history + [[message, error_message]]
 
-# Create Gradio interface
+# Create Gradio interface - UPDATED to use a simpler file upload approach
 with gr.Blocks(title="RAG Chatbot") as demo:
     gr.Markdown("# RAG-based Conversational Chatbot")
     gr.Markdown("Upload text documents and chat with an AI that can answer questions based on their content.")
@@ -137,7 +164,8 @@ with gr.Blocks(title="RAG Chatbot") as demo:
             file_output = gr.Textbox(label="Upload Status")
             file_input = gr.File(
                 file_count="multiple",
-                label="Upload Documents (.txt files)"
+                label="Upload Documents (.txt files)",
+                type="text"  # Specifying text type for proper handling
             )
             upload_button = gr.Button("Process Documents")
             upload_button.click(upload_file, inputs=[file_input], outputs=[file_output])