Update app.py

app.py

@@ -9,7 +9,7 @@ client = Cerebras(api_key=os.getenv("CEREBRAS_API_KEY"))
 def chat_with_cerebras(user_input):
     """
     Handles interaction with the Cerebras model.
-    Sends user input and returns the model's response along with compute time.
+    Sends user input and returns the model's response along with compute time and chain-of-thought reasoning.
     """
     # Start compute time measurement
     start_time = time.time()
@@ -18,7 +18,7 @@ def chat_with_cerebras(user_input):
         # Create a chat stream with Cerebras
         stream = client.chat.completions.create(
             messages=[
-                {"role": "system", "content": "You are IntellijMind, an advanced AI designed to assist users with detailed insights and problem-solving."},
+                {"role": "system", "content": "You are IntellijMind, an advanced AI designed to assist users with detailed insights, problem-solving, and chain-of-thought reasoning."},
                 {"role": "user", "content": user_input}
             ],
             model="llama-3.3-70b",
@@ -30,44 +30,49 @@ def chat_with_cerebras(user_input):
 
         # Collect response from the stream
         response = ""
+        chain_of_thought = ""
         for chunk in stream:
-            response += chunk.choices[0].delta.content or ""
+            if chunk.choices[0].delta.content:
+                response += chunk.choices[0].delta.content
+            if "Chain of Thought:" in chunk.choices[0].delta.content:
+                chain_of_thought += chunk.choices[0].delta.content.split("Chain of Thought:", 1)[-1]
 
         # End compute time measurement
         compute_time = time.time() - start_time
 
-        return response, f"Compute Time: {compute_time:.2f} seconds"
+        return response, chain_of_thought, f"Compute Time: {compute_time:.2f} seconds"
 
     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():
     with gr.Blocks() as demo:
-        gr.Markdown("""# 🚀 IntellijMind: The Future of AI Chatbots\nExperience the most advanced chatbot for deep insights and chain-of-thought reasoning!""")
+        gr.Markdown("""# 🚀 IntellijMind: The Future of AI Chatbots\nExperience the most advanced chatbot for deep insights, chain-of-thought reasoning, and unmatched clarity!""")
 
         with gr.Row():
-            with gr.Column(scale=8):
+            with gr.Column(scale=6):
                 chat_history = gr.Chatbot(label="Chat History")
             with gr.Column(scale=2):
                 compute_time = gr.Textbox(label="Compute Time", interactive=False)
+                chain_of_thought_display = gr.Textbox(label="Chain of Thought", interactive=False, lines=10)
 
         user_input = gr.Textbox(label="Type your message", placeholder="Ask me anything...", lines=2)
         send_button = gr.Button("Send", variant="primary")
         clear_button = gr.Button("Clear Chat")
 
         def handle_chat(chat_history, user_input):
-            ai_response, compute_info = chat_with_cerebras(user_input)
+            ai_response, chain_of_thought, compute_info = chat_with_cerebras(user_input)
             chat_history.append((user_input, ai_response))
-            return chat_history, compute_info
+            return chat_history, chain_of_thought, compute_info
 
         def clear_chat():
-            return [], ""
+            return [], "", ""
 
-        send_button.click(handle_chat, inputs=[chat_history, user_input], outputs=[chat_history, compute_time])
-        clear_button.click(clear_chat, outputs=[chat_history, compute_time])
+        send_button.click(handle_chat, inputs=[chat_history, user_input], outputs=[chat_history, chain_of_thought_display, compute_time])
+        clear_button.click(clear_chat, outputs=[chat_history, chain_of_thought_display, compute_time])
 
-        gr.Markdown("""---\n### 🌟 Features:\n- **Advanced Reasoning**: Chain-of-thought explanations for complex queries.\n- **Performance Metrics**: Measure response compute time instantly.\n- **User-Friendly Design**: Intuitive chatbot interface.\n- **Powered by IntellijMind**: Redefining AI interaction standards.\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- **Insightful Chain of Thought**: See the reasoning process behind AI decisions.\n- **User-Friendly Design**: Intuitive chatbot interface with powerful features.\n- **Powered by IntellijMind**: Setting new standards for AI interaction.\n""")
 
     return demo