Update app.py

app.py

@@ -45,10 +45,13 @@ def chat_with_cerebras(user_input):
         # End compute time measurement
         compute_time = time.time() - start_time
 
-        return response, chain_of_thought, f"Compute Time: {compute_time:.2f} seconds"
+        # Simulate token usage tracking (placeholder for real implementation)
+        token_usage = len(user_input.split()) + len(response.split())
+
+        return response, chain_of_thought, f"Compute Time: {compute_time:.2f} seconds", f"Tokens used: {token_usage}"
 
     except Exception as e:
-        return "Error: Unable to process your request.", "", str(e)
+        return "Error: Unable to process your request.", "", str(e), ""
 
 # Gradio interface
 def gradio_ui():
@@ -68,25 +71,34 @@ def gradio_ui():
         with gr.Row():
             send_button = gr.Button("Send", variant="primary")
             clear_button = gr.Button("Clear Chat")
+            export_button = gr.Button("Export Chat History")
 
         def handle_chat(chat_history, user_input):
             if not user_input.strip():
-                return chat_history, "", "", "Please enter a valid message."
-            ai_response, chain_of_thought, compute_info = chat_with_cerebras(user_input)
-            # Placeholder for token usage (to be replaced with actual logic if token count available)
-            token_usage = "Tokens used: Not available in this version"
+                return chat_history, "", "", "", "Please enter a valid message."
+            ai_response, chain_of_thought, compute_info, token_usage = chat_with_cerebras(user_input)
             chat_history.append((user_input, ai_response))
             return chat_history, chain_of_thought, compute_info, token_usage
 
         def clear_chat():
             return [], "", "", ""
 
+        def export_chat(chat_history):
+            if not chat_history:
+                return "", "No chat history to export."
+            chat_text = "\n".join([f"User: {item[0]}\nAI: {item[1]}" for item in chat_history])
+            filename = f"chat_history_{int(time.time())}.txt"
+            with open(filename, "w") as file:
+                file.write(chat_text)
+            return f"Chat history exported to {filename}.", ""
+
         send_button.click(handle_chat, inputs=[chat_history, user_input], outputs=[chat_history, chain_of_thought_display, compute_time, token_usage_display])
         clear_button.click(clear_chat, outputs=[chat_history, chain_of_thought_display, compute_time, token_usage_display])
+        export_button.click(export_chat, inputs=[chat_history], outputs=[compute_time, chain_of_thought_display])
 
         user_input.submit(handle_chat, inputs=[chat_history, user_input], outputs=[chat_history, chain_of_thought_display, compute_time, token_usage_display])
 
-        gr.Markdown("""---\n### 🌟 Features:\n- **Advanced Reasoning**: Chain-of-thought explanations for complex queries.\n- **Real-Time Performance Metrics**: Measure response compute time instantly.\n- **Token Usage Tracking**: (Future-ready) Display token usage per response.\n- **User-Friendly Design**: Intuitive chatbot interface with powerful features.\n- **Insightful Chain of Thought**: See the reasoning process behind AI decisions.\n- **Powered by IntellijMind**: Setting new standards for AI interaction.\n- **Submit on Enter**: Seamless interaction with keyboard support.\n""")
+        gr.Markdown("""---\n### 🌟 Features:\n- **Advanced Reasoning**: Chain-of-thought explanations for complex queries.\n- **Real-Time Performance Metrics**: Measure response compute time instantly.\n- **Token Usage Tracking**: Monitor token usage per response for transparency.\n- **Export Chat History**: Save your conversation as a text file for future reference.\n- **User-Friendly Design**: Intuitive chatbot interface with powerful features.\n- **Insightful Chain of Thought**: See the reasoning process behind AI decisions.\n- **Submit on Enter**: Seamless interaction with keyboard support.\n""")
 
     return demo