Update app.py

app.py

@@ -263,18 +263,14 @@ Instructions:
         
         # Add conversation history (last 3 exchanges for context)
         if history and len(history) > 0:
-            # History is in tuple format [[user, bot], [user, bot]]
-            # Take last 3 exchanges
+            # Get last 3 user messages (skip current one which isn't in history yet)
             recent_history = history[-3:] if len(history) > 3 else history
-            for exchange in recent_history:
-                if isinstance(exchange, (list, tuple)) and len(exchange) >= 2:
+            for msg in recent_history:
+                # History format from Gradio Chatbot with type="messages"
+                if isinstance(msg, dict) and "role" in msg and "content" in msg:
                     messages.append({
-                        "role": "user",
-                        "content": exchange[0]
-                    })
-                    messages.append({
-                        "role": "assistant",
-                        "content": exchange[1]
+                        "role": msg["role"],
+                        "content": msg["content"]
                     })
         
         # Add current query with context
@@ -288,10 +284,10 @@ Question: {query}"""
             "content": user_message
         })
         
-        # Call Groq API
+        # Call Groq API with updated model
         chat_completion = client.chat.completions.create(
             messages=messages,
-            model="llama3-8b-8192",
+            model="llama-3.1-8b-instant",  # Updated model
             temperature=0.3,
             max_tokens=1024,
         )
@@ -341,117 +337,127 @@ def download_chat_history():
 def clear_history():
     """Clear conversation history"""
     document_store['conversation_history'] = []
-    return [], "History cleared successfully!"
+    return None, "History cleared successfully!"
 
 # Build Gradio Interface
-with gr.Blocks(title="Enhanced RAG Chatbot") as demo:
-    
-    gr.Markdown("""
-    # Enhanced RAG-Based Chatbot
-    Upload PDF/DOCX files and ask questions about their content!
-    
-    **Features:**
-    - Multiple file support (PDF & DOCX)
-    - Semantic embeddings with sentence-transformers
-    - Document preview & summaries
-    - Conversational memory
-    - Source references with page numbers
-    - Download chat history
-    """)
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            file_upload = gr.File(
-                label="Upload Documents (PDF/DOCX)",
-                file_count="multiple",
-                file_types=[".pdf", ".docx"]
-            )
-            process_btn = gr.Button("Process Documents", variant="primary")
-            process_output = gr.Markdown(label="Processing Status")
+def create_demo():
+    with gr.Blocks(title="Enhanced RAG Chatbot") as demo:
+        
+        gr.Markdown("""
+        # Enhanced RAG-Based Chatbot
+        Upload PDF/DOCX files and ask questions about their content!
+        
+        **Features:**
+        - Multiple file support (PDF & DOCX)
+        - Semantic embeddings with sentence-transformers
+        - Document preview & summaries
+        - Conversational memory
+        - Source references with page numbers
+        - Download chat history
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=1):
+                file_upload = gr.File(
+                    label="Upload Documents (PDF/DOCX)",
+                    file_count="multiple",
+                    file_types=[".pdf", ".docx"]
+                )
+                process_btn = gr.Button("Process Documents", variant="primary")
+                process_output = gr.Markdown(label="Processing Status")
+                
+                gr.Markdown("### Chat History Options")
+                download_btn = gr.Button("Download History (JSON)")
+                download_file = gr.File(label="Download", visible=True)
+                clear_btn = gr.Button("Clear History")
+                clear_msg = gr.Textbox(label="Status", interactive=False, visible=False)
             
-            gr.Markdown("### Chat History Options")
-            download_btn = gr.Button("Download History (JSON)")
-            download_file = gr.File(label="Download", visible=True)
-            clear_btn = gr.Button("Clear History")
-            clear_msg = gr.Textbox(label="Status", interactive=False, visible=False)
-        
-        with gr.Column(scale=2):
-            chatbot = gr.Chatbot(label="Conversation", height=500)
-            query_input = gr.Textbox(
-                label="Ask a question",
-                placeholder="Type your question here and press Enter...",
-                lines=2
-            )
-            submit_btn = gr.Button("Ask Question", variant="primary")
-    
-    # Event handlers
-    process_btn.click(
-        fn=process_files,
-        inputs=[file_upload],
-        outputs=[process_output]
-    )
-    
-    def handle_question(question, history):
-        """Handle user question and return updated chat"""
-        if not question or not question.strip():
-            return history, ""
+            with gr.Column(scale=2):
+                chatbot = gr.Chatbot(
+                    label="Conversation", 
+                    height=500,
+                    type="messages"
+                )
+                query_input = gr.Textbox(
+                    label="Ask a question",
+                    placeholder="Type your question here and press Enter...",
+                    lines=2
+                )
+                submit_btn = gr.Button("Ask Question", variant="primary")
         
-        # Ensure history is a list
-        if history is None:
-            history = []
+        # Event handlers
+        process_btn.click(
+            fn=process_files,
+            inputs=[file_upload],
+            outputs=[process_output]
+        )
         
-        # Generate answer
-        answer = generate_answer(question, history)
+        def respond(message, chat_history):
+            """Handle user message and generate response"""
+            if not message or not message.strip():
+                return chat_history
+            
+            # Ensure chat_history is a list
+            if chat_history is None:
+                chat_history = []
+            
+            # Generate answer
+            bot_response = generate_answer(message, chat_history)
+            
+            # Append user message and bot response in Gradio messages format
+            chat_history.append({"role": "user", "content": message})
+            chat_history.append({"role": "assistant", "content": bot_response})
+            
+            return chat_history
+        
+        # Submit button and enter key
+        submit_btn.click(
+            fn=respond,
+            inputs=[query_input, chatbot],
+            outputs=[chatbot]
+        ).then(
+            lambda: "",
+            outputs=[query_input]
+        )
         
-        # Append as tuple (user_msg, bot_msg) - Gradio default format
-        history = history + [[question, answer]]
+        query_input.submit(
+            fn=respond,
+            inputs=[query_input, chatbot],
+            outputs=[chatbot]
+        ).then(
+            lambda: "",
+            outputs=[query_input]
+        )
         
-        return history, ""
-    
-    # Submit button click
-    submit_btn.click(
-        fn=handle_question,
-        inputs=[query_input, chatbot],
-        outputs=[chatbot, query_input]
-    )
-    
-    # Enter key press
-    query_input.submit(
-        fn=handle_question,
-        inputs=[query_input, chatbot],
-        outputs=[chatbot, query_input]
-    )
-    
-    # Download history
-    download_btn.click(
-        fn=download_chat_history,
-        outputs=[download_file]
-    )
-    
-    # Clear history
-    def clear_and_show(history):
-        document_store['conversation_history'] = []
-        return [], "History cleared!", gr.update(visible=True)
-    
-    clear_btn.click(
-        fn=clear_and_show,
-        inputs=[chatbot],
-        outputs=[chatbot, clear_msg, clear_msg]
-    )
-    
-    gr.Markdown("""
-    ---
-    ### How RAG Works:
-    1. **Retrieval**: Finds relevant text chunks from uploaded documents using semantic similarity
-    2. **Augmentation**: Combines retrieved context with your question
-    3. **Generation**: Uses Groq LLM to generate accurate answers based on the context
+        # Download history
+        download_btn.click(
+            fn=download_chat_history,
+            outputs=[download_file]
+        )
+        
+        # Clear history
+        clear_btn.click(
+            fn=clear_history,
+            outputs=[chatbot, clear_msg]
+        )
+        
+        gr.Markdown("""
+        ---
+        ### How RAG Works:
+        1. **Retrieval**: Finds relevant text chunks from uploaded documents using semantic similarity
+        2. **Augmentation**: Combines retrieved context with your question
+        3. **Generation**: Uses Groq LLM to generate accurate answers based on the context
+        
+        ### Usage Instructions:
+        1. Upload one or more PDF/DOCX files
+        2. Click "Process Documents" and wait for confirmation
+        3. Ask questions about the content
+        4. Download chat history anytime as JSON
+        """)
     
-    ### Usage Instructions:
-    1. Upload one or more PDF/DOCX files
-    2. Click "Process Documents" and wait for confirmation
-    3. Ask questions about the content
-    4. Download chat history anytime as JSON
-    """)
+    return demo
 
+# Launch the app
 if __name__ == "__main__":
+    demo = create_demo()
     demo.launch(ssr_mode=False)