Update app.py

app.py

@@ -955,150 +955,158 @@ def format_project_ideas(ideas):
     
     return result
 
+# Missing function implementations
+
+# Dictionary to store user profiles by session ID
+user_profiles = {}
+
 def user_onboarding(session_id, age, goals, knowledge_level, interests, study_time, learning_style):
-    """Process user profile and provide initial recommendations"""
-    # Save user profile data
-    user_data = {
-        'age': age,
-        'goals': goals,
-        'knowledge_level': knowledge_level,
-        'interests': interests,
-        'study_time': study_time,
-        'learning_style': learning_style
+    """Process user profile information and generate personalized recommendations"""
+    
+    # Store user profile information
+    user_profiles[session_id] = {
+        "age": age,
+        "goals": goals,
+        "knowledge_level": knowledge_level,
+        "interests": interests,
+        "study_time": study_time,
+        "learning_style": learning_style,
+        "last_updated": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
     }
-    save_session(session_id, user_data)
-    
-    # Generate recommendations
-    learning_paths = recommend_learning_path(age, goals, knowledge_level, interests)
-    resources = get_recommended_resources(interests, knowledge_level, learning_paths)
-    project_ideas = get_project_ideas(learning_paths)
-    
-    # Save recommendations to session
-    user_data.update({
-        'recommended_paths': learning_paths,
-        'recommended_resources': resources,
-        'recommended_projects': project_ideas
-    })
-    save_session(session_id, user_data)
     
-    # Format welcome message with personalized recommendations
-    welcome_message = f"""
-    # Welcome to Your Personalized Learning Journey!
+    # Generate initial recommendations based on profile
+    return generate_recommendations(session_id)
 
-    Thank you for providing your profile. Based on your information, I've prepared some tailored recommendations to start your learning journey.
+def generate_recommendations(session_id):
+    """Generate personalized learning recommendations based on user profile"""
+    
+    # Check if user profile exists
+    if session_id not in user_profiles:
+        return "Please complete your profile first to get personalized recommendations."
+    
+    profile = user_profiles[session_id]
+    learning_style = profile["learning_style"]
+    knowledge_level = profile["knowledge_level"].lower()
+    
+    # Map knowledge level to appropriate learning path
+    if "python" in profile["interests"].lower():
+        if knowledge_level == "beginner":
+            learning_path_key = "python_beginner"
+        else:
+            learning_path_key = "python_intermediate"
+    elif "data" in profile["interests"].lower():
+        if knowledge_level == "beginner":
+            learning_path_key = "data_science_beginner"
+        else:
+            learning_path_key = "data_science_advanced"
+    elif "ai" in profile["interests"].lower() or "artificial" in profile["interests"].lower():
+        if "gen" in profile["interests"].lower():
+            learning_path_key = "generative_ai"
+        elif "agent" in profile["interests"].lower():
+            learning_path_key = "agentic_ai"
+        else:
+            learning_path_key = "ai_specialization"
+    else:
+        # Default path
+        learning_path_key = "python_beginner"
     
-    ## Your Profile Summary:
-    - **Age:** {age}
-    - **Knowledge Level:** {knowledge_level}
-    - **Learning Goals:** {goals}
-    - **Interests:** {interests}
-    - **Available Study Time:** {study_time} hours per week
-    - **Preferred Learning Style:** {learning_style}
+    # Get learning path and resources based on style and path
+    learning_path = LEARNING_PATHS.get(learning_path_key, LEARNING_PATHS["python_beginner"])
+    resources = LEARNING_RESOURCES.get(learning_style, LEARNING_RESOURCES["Combination"])
+    path_resources = resources.get(learning_path_key, resources["python_beginner"])
     
-    {format_learning_paths(learning_paths)}
+    # Get project ideas
+    project_ideas = PROJECT_IDEAS.get(learning_style, PROJECT_IDEAS["Combination"])
+    path_projects = project_ideas.get(learning_path_key, project_ideas["python_beginner"])
     
-    {format_resources(resources)}
+    # Build the recommendation markdown
+    markdown = f"## Your Personalized Learning Path: {learning_path['title']}\n\n"
+    markdown += f"*{learning_path['description']}*\n\n"
     
-    {format_project_ideas(project_ideas)}
+    markdown += "### Learning Modules\n"
+    for i, module in enumerate(learning_path['modules'], 1):
+        markdown += f"{i}. {module}\n"
     
-    ## Next Steps:
-    1. Browse through the recommended learning paths and resources
-    2. Ask me any questions about the topics you're interested in
-    3. Request exercises, explanations, or code samples
-    4. Try one of the project ideas to apply your knowledge
+    markdown += "\n### Recommended Resources\n"
+    for i, resource in enumerate(path_resources[:3], 1):
+        markdown += f"{i}. [{resource['title']}]({resource['url']})\n"
     
-    I'm here to help you every step of the way! What would you like to explore first?
-    """
+    markdown += "\n### Project Ideas\n"
+    for i, project in enumerate(path_projects[:3], 1):
+        markdown += f"{i}. {project}\n"
     
-    return welcome_message
-
-def chatbot_interface(session_id, user_message):
-    """Main chatbot interface function"""
-    user_data = load_session(session_id)
-    
-    if not user_data or not user_data.get('age'):
-        return "Please complete your profile first by going to the Profile tab."
+    markdown += f"\n\nRecommendations generated based on your {learning_style} learning style preference."
     
-    response = chat_with_groq(user_message, session_id)
-    return response
+    return markdown
 
-def generate_recommendations(session_id):
-    """Generate or refresh recommendations based on current profile"""
-    user_data = load_session(session_id)
-    
-    if not user_data or not user_data.get('age'):
-        return "Please complete your profile first by going to the Profile tab."
-    
-    # Generate fresh recommendations
-    learning_paths = recommend_learning_path(
-        user_data.get('age', ''), 
-        user_data.get('goals', ''), 
-        user_data.get('knowledge_level', ''),
-        user_data.get('interests', '')
-    )
-    resources = get_recommended_resources(
-        user_data.get('interests', ''),
-        user_data.get('knowledge_level', ''),
-        learning_paths
-    )
-    project_ideas = get_project_ideas(learning_paths)
-    
-    # Save recommendations to session
-    user_data.update({
-        'recommended_paths': learning_paths,
-        'recommended_resources': resources,
-        'recommended_projects': project_ideas
-    })
-    save_session(session_id, user_data)
-    
-    # Format recommendations
-    recommendations = f"""
-    # Your Personalized Learning Recommendations
-    
-    {format_learning_paths(learning_paths)}
-    
-    {format_resources(resources)}
-    
-    {format_project_ideas(project_ideas)}
-    """
+def chatbot_interface(session_id, message):
+    """Process user messages and generate assistant responses"""
+    
+    if not message:
+        return "Please type a message to start the conversation."
+    
+    # Build system message with context from user profile if available
+    system_message = SYSTEM_PROMPT
+    
+    if session_id in user_profiles:
+        profile = user_profiles[session_id]
+        system_message += f"\n\nUser Profile Information:\n"
+        system_message += f"- Knowledge Level: {profile['knowledge_level']}\n"
+        system_message += f"- Learning Style: {profile['learning_style']}\n"
+        system_message += f"- Interests: {profile['interests']}\n"
+        system_message += f"- Learning Goals: {profile['goals']}\n"
+    
+    # Call the Groq API
+    try:
+        chat_completion = client.chat.completions.create(
+            model="llama3-70b-8192",  # or another appropriate model
+            messages=[
+                {"role": "system", "content": system_message},
+                {"role": "user", "content": message}
+            ],
+            temperature=0.7,
+            max_tokens=2048
+        )
+        
+        # Extract and return the response
+        return chat_completion.choices[0].message.content
     
-    return recommendations
+    except Exception as e:
+        return f"I apologize, but I encountered an error: {str(e)}\n\nPlease try again in a moment."
 
 def handle_quiz_request(session_id, topic, difficulty):
-    """Handle quiz generation request"""
-    user_data = load_session(session_id)
+    """Generate a quiz based on the specified topic and difficulty"""
+    
+    if not topic:
+        return "Please specify a topic for the quiz."
+    
+    # Build prompt for quiz generation
+    prompt = f"Create a quiz on {topic} at {difficulty} level. Include 5 questions with multiple choice answers and provide the correct answers at the end."
     
-    if not user_data or not user_data.get('age'):
-        return "Please complete your profile first by going to the Profile tab."
+    # Add context from user profile if available
+    if session_id in user_profiles:
+        profile = user_profiles[session_id]
+        prompt += f"\nThe user has a {profile['knowledge_level']} knowledge level and prefers {profile['learning_style']} learning style."
     
-    quiz = generate_quiz(topic, difficulty)
-    return quiz
+    # Use chatbot interface with the quiz prompt
+    return chatbot_interface(session_id, prompt)
 
 def handle_study_plan_request(session_id, topic, time_available):
-    """Handle study plan generation request"""
-    user_data = load_session(session_id)
-    
-    if not user_data or not user_data.get('age'):
-        return "Please complete your profile first by going to the Profile tab."
+    """Generate a personalized study plan based on topic and available time"""
     
-    goals = user_data.get('goals', 'improving skills')
-    knowledge_level = user_data.get('knowledge_level', 'Beginner')
-    study_plan = create_study_plan(topic, time_available, goals, knowledge_level)
+    if not topic:
+        return "Please specify a topic for your study plan."
     
-    # Save the generated study plan to the session
-    if 'study_plans' not in user_data:
-        user_data['study_plans'] = {}
+    # Build prompt for study plan generation
+    prompt = f"Create a detailed study plan for learning {topic} with {time_available} hours available per week. Include specific goals, resources, and milestones."
     
-    study_plan_id = f"{topic}_{time_available}_{datetime.now().strftime('%Y%m%d%H%M%S')}"
-    user_data['study_plans'][study_plan_id] = {
-        'topic': topic,
-        'time_available': time_available,
-        'plan': study_plan,
-        'created_at': datetime.now().isoformat()
-    }
-    save_session(session_id, user_data)
+    # Add context from user profile if available
+    if session_id in user_profiles:
+        profile = user_profiles[session_id]
+        prompt += f"\nThe user has a {profile['knowledge_level']} knowledge level, prefers {profile['learning_style']} learning style, and has these goals: {profile['goals']}."
     
-    return study_plan
+    # Use chatbot interface with the study plan prompt
+    return chatbot_interface(session_id, prompt)
 
 def add_generative_ai_info():
     """Return information about Generative AI"""