Create src/serci

src/serci

@@ -0,0 +1,122 @@
+import streamlit as st
+from typing import Dict
+from datetime import datetime
+import anthropic
+from src.utils.session import get_tutor_context
+from src.utils.config import get_anthropic_api_key
+
+class AITutorService:
+    def __init__(self):
+        self.initialize_client()
+        self.load_avatar_assets()
+
+    def initialize_client(self):
+        """Initialize Anthropic client"""
+        self.client = anthropic.Anthropic(api_key=get_anthropic_api_key())
+
+    def load_avatar_assets(self):
+        """Load avatar assets and animations"""
+        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 60 Q 50 70 70 60" 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 65 Q 50 65 70 65" 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>
+            """
+        }
+
+    def display_avatar(self, state: str = 'neutral'):
+        """Display the AI tutor avatar"""
+        st.markdown(f"""
+            <div style="display: flex; justify-content: center; margin: 20px 0;">
+                {self.avatar_states.get(state, self.avatar_states['neutral'])}
+            </div>
+        """, unsafe_allow_html=True)
+
+    def generate_response(self, user_input: str) -> str:
+        """Generate contextualized response using Claude"""
+        context = get_tutor_context()
+        prompt = self.build_prompt(user_input, context)
+
+        # Generate response using Claude
+        message = self.client.messages.create(
+            model="claude-3-opus-20240229",
+            max_tokens=1024,
+            temperature=0.7,
+            system="You are an expert AI tutor, skilled at explaining complex concepts clearly and engaging students in their learning journey. Provide detailed, accurate explanations while maintaining an encouraging tone.",
+            messages=[
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ]
+        )
+        
+        response = message.content[0].text
+        
+        # Analyze sentiment (Claude can do this as part of its response)
+        sentiment_score = 0.8 if any(word in response.lower() for word in ['great', 'excellent', 'good job', 'well done']) else 0.5
+        
+        # Update engagement metrics
+        self.update_engagement_metrics(user_input, response, sentiment_score)
+        
+        return response
+
+    def build_prompt(self, user_input: str, context: Dict) -> str:
+        """Build a context-aware prompt for Claude"""
+        topic_context = f"Current topic: {context['current_topic']}\n" if context['current_topic'] else ""
+        
+        chat_context = "\n".join([
+            f"Student: {msg['content']}" if msg['role'] == 'user' else f"Tutor: {msg['content']}"
+            for msg in context['chat_history'][-3:]
+        ])
+        
+        return f"""
+        You are an educational AI tutor helping a student learn.
+        
+        {topic_context}
+        Difficulty level: {context['difficulty_level']}
+        Learning style: {context['learning_style']}
+        
+        Previous conversation:
+        {chat_context}
+        
+        Student: {user_input}
+        
+        Provide a clear, helpful response that:
+        1. Addresses the student's question directly
+        2. Explains concepts in an engaging way
+        3. Uses examples when appropriate
+        4. Encourages deeper understanding
+        5. Maintains a supportive tone
+
+        If the question is about code, include working code examples.
+        If the topic is complex, break it down into simpler parts.
+        """
+
+    def update_engagement_metrics(self, user_input: str, response: str, sentiment_score: float):
+        """Update student engagement metrics"""
+        context = get_tutor_context()
+        context['engagement_metrics'].append({
+            'timestamp': datetime.now().isoformat(),
+            'sentiment_score': sentiment_score,
+            'interaction_length': len(user_input)
+        })