Update src/components/ai_tutor.py

src/components/ai_tutor.py

@@ -1,144 +1,6 @@
 import streamlit as st
-from datetime import datetime
-import anthropic
-import os
-from typing import Dict
-
-class AITutorService:
-    def __init__(self):
-        self._client = None
-        self.initialize_client()
-        self._load_avatar_assets()
-
-    def initialize_client(self):
-        """Initialize Anthropic client with better error handling"""
-        try:
-            # First try getting API key from Streamlit secrets
-            api_key = None
-            if hasattr(st, 'secrets') and 'ANTHROPIC_API_KEY' in st.secrets:
-                api_key = st.secrets['ANTHROPIC_API_KEY']
-            
-            # If not in secrets, try environment variable
-            if not api_key:
-                api_key = os.getenv('ANTHROPIC_API_KEY')
-            
-            if not api_key:
-                st.error("Anthropic API key not found. Please set ANTHROPIC_API_KEY in .streamlit/secrets.toml or environment variables.")
-                st.info("For testing, you can set this up locally by creating a .streamlit/secrets.toml file with:\nANTHROPIC_API_KEY='your-key-here'")
-                return
-
-            self._client = anthropic.Anthropic(api_key=api_key)
-
-        except Exception as e:
-            st.error(f"Failed to initialize Anthropic client: {str(e)}")
-            self._client = None
-
-    def _load_avatar_assets(self):
-        """Initialize avatar states and assets"""
-        self.avatar_states = {
-            'neutral': """
-                <svg width="100" height="100" viewBox="0 0 100 100">
-                    <circle cx="50" cy="50" r="45" fill="#4A90E2"/>
-                    <circle cx="35" cy="40" r="5" fill="white"/>
-                    <circle cx="65" cy="40" r="5" fill="white"/>
-                    <path d="M 30 65 Q 50 65 70 65" stroke="white" fill="none" stroke-width="3"/>
-                </svg>
-            """,
-            'thinking': """
-                <svg width="100" height="100" viewBox="0 0 100 100">
-                    <circle cx="50" cy="50" r="45" fill="#4A90E2"/>
-                    <circle cx="35" cy="40" r="5" fill="white"/>
-                    <circle cx="65" cy="40" r="5" fill="white"/>
-                    <path d="M 30 60 Q 50 70 70 60" stroke="white" fill="none" stroke-width="3"/>
-                </svg>
-            """,
-            'happy': """
-                <svg width="100" height="100" viewBox="0 0 100 100">
-                    <circle cx="50" cy="50" r="45" fill="#4A90E2"/>
-                    <circle cx="35" cy="40" r="5" fill="white"/>
-                    <circle cx="65" cy="40" r="5" fill="white"/>
-                    <path d="M 30 60 Q 50 80 70 60" stroke="white" fill="none" stroke-width="3"/>
-                </svg>
-            """
-        }
-
-    @property
-    def client(self):
-        """Property to safely access the Anthropic client"""
-        if self._client is None:
-            raise ValueError("Anthropic client not properly initialized")
-        return self._client
-
-    def display_avatar(self, state: str = 'neutral'):
-        """Display the AI tutor avatar"""
-        avatar_svg = self.avatar_states.get(state, self.avatar_states['neutral'])
-        st.markdown(f"""
-            <div style="display: flex; justify-content: center; margin: 20px 0;">
-                {avatar_svg}
-            </div>
-        """, unsafe_allow_html=True)
-
-    def generate_response(self, user_input: str) -> str:
-        """Generate response using Claude with better error handling"""
-        if not self._client:
-            return "I apologize, but I'm not properly connected right now. Please check the API configuration."
-
-        try:
-            # Get session context
-            context = st.session_state.get('tutor_context', {})
-            current_topic = context.get('current_topic')
-            
-            # Build system prompt
-            system_prompt = """You are an expert tutor helping students learn. 
-                             Give clear, step-by-step explanations with examples.
-                             Focus on the current topic if specified."""
-            
-            if current_topic and current_topic != "All Topics":
-                system_prompt += f"\nYou are currently tutoring about {current_topic}."
-
-            # Generate response
-            response = self.client.messages.create(
-                model="claude-3-opus-20240229",
-                temperature=0.7,
-                max_tokens=1024,
-                system=system_prompt,
-                messages=[{
-                    "role": "user",
-                    "content": user_input
-                }]
-            )
-            
-            # Get response text
-            response_text = response.content[0].text
-            
-            # Update metrics
-            self.update_engagement_metrics(user_input, response_text)
-            
-            return response_text
-
-        except anthropic.APIError as e:
-            st.error(f"API Error: {str(e)}")
-            return "I encountered an API error. Please try again in a moment."
-        except anthropic.APIConnectionError as e:
-            st.error(f"Connection Error: {str(e)}")
-            return "I'm having trouble connecting to my API. Please check your internet connection."
-        except Exception as e:
-            st.error(f"Unexpected error: {str(e)}")
-            return "I encountered an unexpected error. Please try again."
-
-    def update_engagement_metrics(self, user_input: str, response: str):
-        """Update engagement metrics"""
-        if 'tutor_context' not in st.session_state:
-            st.session_state.tutor_context = {
-                'engagement_metrics': []
-            }
-            
-        metrics = st.session_state.tutor_context['engagement_metrics']
-        metrics.append({
-            'timestamp': datetime.now().isoformat(),
-            'sentiment_score': min(1.0, len(user_input) / 100.0),
-            'interaction_length': len(user_input)
-        })
+from src.services.ai_service import AITutorService
+from src.utils.session import get_tutor_context
 
 class AITutor:
     def __init__(self):
@@ -151,15 +13,13 @@ class AITutor:
         # Voice controls with TTS mode indicator
         col1, col2 = st.columns([3, 2])
         with col1:
-            st.write("Voice features not implemented yet.")
-            # if self.voice_enabled:
-            #     voice_active = st.toggle("Enable Voice", value=False, key="voice_active")
-            # else:
-            #     voice_active = False
+            if self.service.voice_enabled:
+                voice_active = st.toggle("Enable Voice", value=False, key="voice_active")
+            else:
+                voice_active = False
         with col2:
-            st.write("TTS mode not implemented yet.")
-            # if self.tts_mode:
-            #     st.info(f"Using {self.tts_mode.upper()} TTS")
+            if self.service.tts_mode:
+                st.info(f"Using {self.service.tts_mode.upper()} TTS")
 
         # Display avatar
         self.service.display_avatar(state='neutral')
@@ -186,9 +46,9 @@ class AITutor:
                     st.write(message["content"])
                     if message["role"] == "assistant":
                         self.service.display_avatar(state='happy')
-                        # if voice_active and message.get('speak', True):
-                        #     self.speak(message["content"])
-                        #     message['speak'] = False
+                        if voice_active and message.get('speak', True):
+                            self.service.speak(message["content"])
+                            message['speak'] = False
 
         # Chat input
         if prompt := st.text_input("Ask your question...", key="chat_input"):
@@ -216,25 +76,5 @@ class AITutor:
             "speak": True
         })
         
-        # Show happy avatar and rerun
-        self.service.display_avatar(state='happy')
-        st.experimental_rerun()
-
-def get_tutor_context() -> Dict:
-    """Get or initialize tutor context"""
-    if 'tutor_context' not in st.session_state:
-        st.session_state.tutor_context = {
-            'current_topic': None,
-            'chat_history': []
-        }
-    return st.session_state.tutor_context
-
-def main():
-    """Main Streamlit application entry point"""
-    st.set_page_config(page_title="EduAI Platform", page_icon="🎓")
-    
-    ai_tutor = AITutor()
-    ai_tutor.display_chat_interface()
-
-if __name__ == "__main__":
-    main()
+        # Show happy avatar
+        self.service.display_avatar(state='happy')