Update app.py

app.py

@@ -1,100 +1,157 @@
 import gradio as gr
-from web_learning_bot import WebEnhancedBot
-import os
+from free_web_bot import FreeWebBot
 
-# Initialize the web-enhanced bot
-bot = WebEnhancedBot()
+# Initialize the bot
+bot = FreeWebBot()
 
 def respond(message, history, enable_search):
-    # Get response with actual web integration
-    response, search_used = bot.chat_with_web_search(message, use_search=enable_search)
+    """Process user message and return response"""
+    if not message or not message.strip():
+        return history, history
     
-    # Display context
-    search_info = "🔍 **Web Search Used**" if search_used else "💭 **From Knowledge**"
+    # Get response from bot
+    response, search_used, sources = bot.chat(message, use_web_search=enable_search)
+    
+    # Create learning info display
     stats = bot.get_learning_stats()
+    if search_used and sources:
+        search_info = f"🔍 Web Search ({len(sources)} sources)"
+    elif search_used:
+        search_info = "🔍 Search Attempted"
+    else:
+        search_info = "💭 From Knowledge"
+    
     learning_info = f"{search_info} | Patterns: {stats['patterns']} | Score: {stats['avg_score']:.2f}"
     
+    # Format full response
+    full_response = f"{response}\n\n{learning_info}"
+    
+    # Update history
     if history is None:
         history = []
-    
-    full_response = f"{response}\n\n{learning_info}"
     history.append((message, full_response))
+    
     return history, history
 
-def add_feedback(feedback, history):
-    if feedback and history:
-        try:
-            score = float(feedback)
-            if 1 <= score <= 5:
-                bot.learn_from_feedback(history[-1][0], score / 5.0)
-                return f"✅ Learned from feedback: {score}/5"
-        except:
-            pass
-    return "❌ Please enter 1-5"
+def add_feedback(feedback_text, history):
+    """Process user feedback"""
+    if not feedback_text or not history:
+        return "Please enter feedback and ensure there's a conversation"
+    
+    try:
+        score = float(feedback_text)
+        if 1 <= score <= 5:
+            # Get the last user message from history
+            last_user_message = history[-1][0] if history else ""
+            bot.learn_from_feedback(last_user_message, score / 5.0)
+            return f"✅ Learned from feedback: {score}/5"
+        else:
+            return "❌ Please enter a number between 1-5"
+    except ValueError:
+        return "❌ Please enter a valid number 1-5"
 
-with gr.Blocks(theme=gr.themes.Soft(), title="Phoenix AI - Real Web Search") as demo:
+def clear_chat():
+    """Clear the chat history"""
+    return [], [], "Chat cleared!"
+
+# Create the Gradio interface
+with gr.Blocks(theme=gr.themes.Soft(), title="Phoenix AI - Free Web Chat") as demo:
     gr.Markdown("""
-    # 🌐 Phoenix AI - Real Web Search
-    **Now actually answers questions using real internet information!**
-    *Try: "current news", "weather in Tokyo", "latest AI developments", etc.*
+    # 🌐 Phoenix AI - Free Web Chatbot
+    **Completely free chatbot with real web search capabilities!**
+    
+    *Try asking about: current news, weather, sports, or any topic you're curious about!*
     """)
     
-    chatbot = gr.Chatbot(height=400, label="Web-Enhanced Chat")
-    state = gr.State([])
+    # Chat interface
+    chatbot = gr.Chatbot(
+        label="Conversation",
+        height=500,
+        show_copy_button=True
+    )
+    
+    # State to store conversation history
+    state = gr.State(value=[])
     
+    # Input section
     with gr.Row():
-        with gr.Column(scale=4):
-            msg = gr.Textbox(
-                label="Ask me anything",
-                placeholder="I'll search the web and give you real answers! Try: 'current news' or 'weather in London'",
-                container=False
-            )
+        message_input = gr.Textbox(
+            label="Your message",
+            placeholder="Ask me anything and I'll search the web for answers...",
+            scale=4,
+            container=False
+        )
+        
         with gr.Column(scale=1):
-            search_toggle = gr.Checkbox(label="🔍 Enable Web Search", value=True)
-            send_btn = gr.Button("Send", variant="primary")
+            search_checkbox = gr.Checkbox(
+                label="Enable Web Search", 
+                value=True,
+                info="Search web for current information"
+            )
+            send_button = gr.Button("Send", variant="primary")
     
+    # Feedback section
     with gr.Row():
-        feedback = gr.Textbox(
-            label="Rate this response (1-5)",
-            placeholder="Help me learn! Rate 1-5",
+        feedback_input = gr.Textbox(
+            label="Rate the last response (1-5)",
+            placeholder="Help me learn by rating responses 1 (poor) to 5 (excellent)",
             scale=3
         )
-        learn_btn = gr.Button("Submit Feedback", scale=1)
-        clear_btn = gr.Button("Clear Chat", scale=1)
+        feedback_button = gr.Button("Submit Rating", scale=1)
+        clear_button = gr.Button("Clear Chat", scale=1)
     
-    learning_stats = gr.Textbox(
-        label="Learning Statistics",
-        value="Ready to search and answer questions...",
-        interactive=False
+    # Learning statistics
+    stats_display = gr.Textbox(
+        label="Learning Progress",
+        value="Ready to chat and learn!",
+        interactive=False,
+        max_lines=2
     )
     
-    # Update stats
-    def update_stats():
+    # Update statistics display
+    def update_statistics():
         stats = bot.get_learning_stats()
-        return f"📊 Learned: {stats['patterns']} patterns | Memory: {stats['memory_size']} | Recent Success: {stats['recent_rewards']}/10"
+        return f"📊 Learned: {stats['patterns']} patterns | Memory: {stats['memory_size']} conversations | Success Rate: {stats['avg_score']:.2f}/1.0"
     
-    # Main interaction
-    def user_message(message, history, search_toggle):
-        if not message.strip():
-            return "", history
-        new_history = respond(message, history or [], search_toggle)
-        return "", new_history[0], update_stats()
+    # Handle message submission
+    def handle_message(user_message, chat_history, search_enabled):
+        if not user_message or not user_message.strip():
+            return "", chat_history, update_statistics()
+        
+        new_history = respond(user_message, chat_history, search_enabled)
+        return "", new_history[0], update_statistics()
     
     # Event handlers
-    msg.submit(user_message, [msg, state, search_toggle], [msg, chatbot, learning_stats])
-    send_btn.click(user_message, [msg, state, search_toggle], [msg, chatbot, learning_stats])
+    message_input.submit(
+        handle_message,
+        inputs=[message_input, state, search_checkbox],
+        outputs=[message_input, chatbot, stats_display]
+    )
+    
+    send_button.click(
+        handle_message,
+        inputs=[message_input, state, search_checkbox],
+        outputs=[message_input, chatbot, stats_display]
+    )
     
-    learn_btn.click(
+    feedback_button.click(
         add_feedback,
-        [feedback, chatbot],
-        [feedback]
-    ).then(update_stats, None, [learning_stats])
-    
-    clear_btn.click(
-        lambda: ([], [], "Chat cleared!"),
-        None,
-        [chatbot, state, learning_stats]
+        inputs=[feedback_input, chatbot],
+        outputs=[feedback_input]
+    ).then(
+        update_statistics,
+        outputs=[stats_display]
+    )
+    
+    clear_button.click(
+        clear_chat,
+        outputs=[chatbot, state, stats_display]
     )
 
+# Launch the application
 if __name__ == "__main__":
-    demo.launch(share=True, show_error=True)
+    demo.launch(
+        share=False,
+        show_error=True,
+        debug=True
+    )