pratham0011/Multi-Agent-Tutoring-Bot
0
1import gradio as gr2from agents.tutor_agent import TutorAgent3import time4import logging5import traceback6import os7 8# Configure logging9logging.basicConfig(10 level=logging.INFO,11 format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',12 handlers=[13 logging.FileHandler("tutoring_bot.log"),14 logging.StreamHandler()15 ]16)17 18class TutoringBotApp:19 """Main application class for the Multi-Agent Tutoring Bot."""20 21 def __init__(self):22 self.tutor_agent = TutorAgent()23 self.conversation_history = []24 25 def chat_response(self, message, history):26 """Handle chat responses with conversation history."""27 if not message.strip():28 return history, ""29 30 # Process the query31 try:32 logging.info(f"Processing query: {message}")33 response = self.tutor_agent.process_query(message)34 logging.info(f"Query processed successfully. Response: {response[:100]}...")35 36 # Ensure response is a string37 if response is None:38 response = "I apologize, but I couldn't generate a response. Please try again."39 logging.warning("Response was None, using default message")40 41 # Add to history using the new messages format42 new_history = list(history) # Create a copy to avoid modifying the original43 new_history.append({"role": "user", "content": message})44 new_history.append({"role": "assistant", "content": response})45 46 # Log the history for debugging47 logging.info(f"Updated history length: {len(new_history)}")48 if len(new_history) > 0:49 logging.info(f"Last history item: {new_history[-1]}")50 51 # Store in conversation history52 self.conversation_history.append({53 "user": message,54 "bot": response,55 "timestamp": time.time()56 })57 58 return new_history, ""59 60 except Exception as e:61 error_details = traceback.format_exc()62 logging.error(f"Error processing query: {str(e)}")63 logging.error(f"Traceback: {error_details}")64 65 error_response = f"I apologize, but I encountered an error. Please make sure Ollama is running and try again. Error: {str(e)}"66 67 new_history = list(history) # Create a copy to avoid modifying the original68 new_history.append({"role": "user", "content": message})69 new_history.append({"role": "assistant", "content": error_response})70 71 return new_history, ""72 73 def show_capabilities(self):74 """Display bot capabilities."""75 return self.tutor_agent.get_capabilities()76 77 def clear_conversation(self):78 """Clear the conversation history."""79 self.conversation_history = []80 return []81 82 def create_interface(self):83 """Create and configure the Gradio interface."""84 with gr.Blocks(85 title="Multi-Agent Tutoring Bot",86 theme=gr.themes.Soft(),87 css="""88 .main-header {89 text-align: center;90 color: #2E8B57;91 margin-bottom: 20px;92 }93 .info-box {94 background-color: #f0f8ff;95 padding: 15px;96 border-radius: 10px;97 border: 1px solid #add8e6;98 margin: 10px 0;99 }100 """101 ) as demo:102 103 gr.Markdown(104 """105 # 🎓 Multi-Agent Tutoring Bot106 ### Powered by LangChain, Ollama, and Gradio107 108 Get help with **Mathematics** and **Physics** from specialized AI agents!109 """,110 elem_classes=["main-header"]111 )112 113 with gr.Row():114 with gr.Column(scale=2):115 chatbot = gr.Chatbot(116 height=500,117 show_label=False,118 avatar_images=[119 "https://cdn-icons-png.flaticon.com/512/3135/3135810.png", # Student icon120 "https://cdn-icons-png.flaticon.com/512/4712/4712027.png" # Robot icon121 ],122 type="messages",123 render_markdown=True124 )125 126 msg = gr.Textbox(127 placeholder="Ask me about mathematics or physics...",128 label="Your Question",129 lines=2130 )131 132 with gr.Row():133 submit_btn = gr.Button("Send", variant="primary")134 clear_btn = gr.Button("Clear Chat", variant="secondary")135 136 with gr.Column(scale=1):137 gr.Markdown(138 """139 ### 📚 Quick Examples140 **Mathematics:**141 - "Solve the equation 2x + 5 = 11"142 - "What is the derivative of x²?"143 - "Calculate 15 × 23"144 145 **Physics:**146 - "What is Newton's second law?"147 - "Explain kinetic energy"148 - "What is the speed of light?"149 150 ### ⚙️ System Info151 - **Model:** Qwen3 0.6b via Ollama152 - **Framework:** LangChain153 - **Agents:** Math & Physics specialists154 """,155 elem_classes=["info-box"]156 )157 158 capabilities_btn = gr.Button("Show Full Capabilities")159 capabilities_output = gr.Markdown(visible=False)160 161 # Event handlers162 def submit_message(message, history):163 logging.info(f"Submit message called with message: '{message}'")164 logging.info(f"Current history length: {len(history) if history else 0}")165 166 # Ensure message is not empty167 if not message or not message.strip():168 logging.warning("Empty message submitted, ignoring")169 return history, ""170 171 # Process the message and get updated history172 updated_history, _ = self.chat_response(message, history)173 logging.info(f"Updated history returned with length: {len(updated_history)}")174 175 return updated_history, ""176 177 def clear_chat():178 return self.clear_conversation()179 180 def toggle_capabilities():181 capabilities_text = self.show_capabilities()182 return gr.Markdown(capabilities_text, visible=True)183 184 # Wire up the events185 msg.submit(186 submit_message,187 inputs=[msg, chatbot],188 outputs=[chatbot, msg]189 )190 191 submit_btn.click(192 submit_message,193 inputs=[msg, chatbot],194 outputs=[chatbot, msg]195 )196 197 clear_btn.click(198 clear_chat,199 outputs=[chatbot]200 )201 202 capabilities_btn.click(203 toggle_capabilities,204 outputs=[capabilities_output]205 )206 207 # Welcome message - updated for new format208 demo.load(209 lambda: [{"role": "assistant", "content": "Hello! I'm your AI tutoring assistant. I can help you with mathematics and physics questions. What would you like to learn about today?"}],210 outputs=[chatbot]211 )212 213 return demo214 215def main():216 """Main function to run the application."""217 print("Starting Multi-Agent Tutoring Bot...")218 print("Make sure Ollama is running with qwen3:0.6b model")219 220 logging.info("Initializing Tutoring Bot application")221 222 try:223 app = TutoringBotApp()224 demo = app.create_interface()225 226 logging.info("Application initialized successfully")227 228 # Launch the app229 server_name = os.environ.get("SERVER_NAME", "127.0.0.1")230 server_port = int(os.environ.get("SERVER_PORT", "7860"))231 logging.info(f"Launching web interface on http://{server_name}:{server_port}")232 demo.launch(233 server_name="0.0.0.0", 234 server_port=7860,235 share=False,236 show_error=True,237 quiet=False,238 debug=True239 )240 except Exception as e:241 error_details = traceback.format_exc()242 logging.error(f"Failed to start application: {str(e)}")243 logging.error(f"Traceback: {error_details}")244 print(f"Error starting application: {str(e)}")245 print("Check tutoring_bot.log for details")246 247if __name__ == "__main__":248 main()249