FINAL FIX: @tool decorator error resolved + optimized deps

app.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
 """
-AI-Powered Personal Learning Assistant v2.0
-Clean Production Build for HuggingFace Spaces
+AI-Powered Personal Learning Assistant
+Version 2.0 - Clean Production Build for HuggingFace Spaces
 Gradio Agents & MCP Hackathon 2025
 
 Features:
 - Multi-agent AI reasoning with smolagents
-- Voice AI processing with SambaNova Cloud  
+- Voice AI processing with SambaNova Cloud
 - Real-time data integration via MCP
 - ZeroGPU optimized for HuggingFace Spaces
 """
@@ -26,9 +26,10 @@ from datetime import datetime, timedelta
 import gradio as gr
 import requests
 import plotly.graph_objects as go
+import plotly.express as px
 from dotenv import load_dotenv
 
-# Audio processing with graceful fallback
+# Audio processing
 try:
     import speech_recognition as sr
     import pydub
@@ -38,12 +39,13 @@ except ImportError as e:
     AUDIO_AVAILABLE = False
     print(f"⚠️ Audio libraries not available: {e}")
 
-# AI dependencies with graceful fallbacks
+# AI and ML dependencies with graceful fallbacks
 try:
     import transformers
     TRANSFORMERS_AVAILABLE = True
 except ImportError:
     TRANSFORMERS_AVAILABLE = False
+    print("⚠️ Transformers not available")
 
 try:
     import smolagents
@@ -53,12 +55,23 @@ except ImportError:
     SMOLAGENTS_AVAILABLE = False
     print("⚠️ Smolagents not available - using fallback mode")
 
+# Define tool decorator fallback BEFORE using it
+if not SMOLAGENTS_AVAILABLE:
+    def tool(func):
+        """Fallback tool decorator when smolagents is not available"""
+        func._is_tool = True
+        return func
+else:
+    # Import tool from smolagents if available
+    pass  # tool is already imported above
+
 # HuggingFace Spaces support
 try:
     import spaces
     SPACES_AVAILABLE = True
 except ImportError:
     SPACES_AVAILABLE = False
+    # Mock spaces decorator for local development
     class spaces:
         @staticmethod
         def GPU(func):
@@ -69,17 +82,17 @@ load_dotenv()
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-# Configuration
+# Global configuration
 SAMBANOVA_API_KEY = os.getenv("SAMBANOVA_API_KEY")
 HF_TOKEN = os.getenv("HF_TOKEN")
 SAMBANOVA_AVAILABLE = bool(SAMBANOVA_API_KEY)
 
 # ============================================================================
-# Database Layer
+# Database Layer - Learning Progress Tracking
 # ============================================================================
 
 class LearningDatabase:
-    """SQLite database for learning progress tracking"""
+    """SQLite database for tracking learning progress and user profiles"""
     
     def __init__(self, db_path: str = "learning_assistant.db"):
         self.db_path = db_path
@@ -91,6 +104,7 @@ class LearningDatabase:
             with sqlite3.connect(self.db_path) as conn:
                 cursor = conn.cursor()
                 
+                # User profiles table
                 cursor.execute("""
                     CREATE TABLE IF NOT EXISTS user_profiles (
                         id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -101,6 +115,7 @@ class LearningDatabase:
                     )
                 """)
                 
+                # Learning sessions table
                 cursor.execute("""
                     CREATE TABLE IF NOT EXISTS learning_sessions (
                         id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -114,6 +129,19 @@ class LearningDatabase:
                     )
                 """)
                 
+                # Progress tracking table
+                cursor.execute("""
+                    CREATE TABLE IF NOT EXISTS progress_tracking (
+                        id INTEGER PRIMARY KEY AUTOINCREMENT,
+                        user_id INTEGER,
+                        subject TEXT,
+                        skill TEXT,
+                        mastery_level REAL,
+                        last_updated TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                        FOREIGN KEY (user_id) REFERENCES user_profiles (id)
+                    )
+                """)
+                
                 conn.commit()
                 logger.info("✅ Database initialized successfully")
                 
@@ -121,7 +149,7 @@ class LearningDatabase:
             logger.error(f"❌ Database initialization failed: {e}")
 
 # ============================================================================
-# Multi-Agent System with Smolagents
+# Multi-Agent AI System with Smolagents
 # ============================================================================
 
 class LearningAgents:
@@ -139,36 +167,77 @@ class LearningAgents:
             return
         
         try:
-            # Initialize model for smolagents
-            if HF_TOKEN:
-                model = HfApiModel("microsoft/DialoGPT-medium", token=HF_TOKEN)
-            else:
-                model = HfApiModel("microsoft/DialoGPT-medium")
+            # Initialize smolagents with proper configuration
+            from smolagents import HfApiModel
+            
+            # Use HuggingFace models for reasoning
+            model = HfApiModel("microsoft/DialoGPT-medium")
             
             # Create specialized agents
-            self.curriculum_agent = CodeAgent(
+            self.curriculum_agent = self.create_curriculum_agent(model)
+            self.content_agent = self.create_content_agent(model)
+            self.assessment_agent = self.create_assessment_agent(model)
+            
+            logger.info("✅ Smolagents multi-agent system initialized")
+            
+        except Exception as e:
+            logger.error(f"❌ Smolagents setup failed: {e}")
+            self.agents_available = False
+            self.setup_fallback_agents()
+    
+    def create_curriculum_agent(self, model):
+        """Create curriculum planning agent with smolagents"""
+        if not self.agents_available:
+            return self.create_fallback_agent("curriculum")
+        
+        try:
+            agent = CodeAgent(
                 tools=[self.curriculum_planning_tool],
                 model=model,
                 max_iterations=3
             )
-            
-            self.content_agent = ReactCodeAgent(
+            return agent
+        except Exception as e:
+            logger.error(f"Curriculum agent creation failed: {e}")
+            return self.create_fallback_agent("curriculum")
+    
+    def create_content_agent(self, model):
+        """Create content generation agent with smolagents"""
+        if not self.agents_available:
+            return self.create_fallback_agent("content")
+        
+        try:
+            agent = ReactCodeAgent(
                 tools=[self.content_generation_tool],
                 model=model,
                 max_iterations=2
             )
-            
-            logger.info("✅ Smolagents multi-agent system initialized")
-            
+            return agent
         except Exception as e:
-            logger.error(f"❌ Smolagents setup failed: {e}")
-            self.agents_available = False
-            self.setup_fallback_agents()
+            logger.error(f"Content agent creation failed: {e}")
+            return self.create_fallback_agent("content")
+    
+    def create_assessment_agent(self, model):
+        """Create assessment agent with smolagents"""
+        if not self.agents_available:
+            return self.create_fallback_agent("assessment")
+        
+        try:
+            agent = CodeAgent(
+                tools=[self.assessment_generation_tool],
+                model=model,
+                max_iterations=2
+            )
+            return agent
+        except Exception as e:
+            logger.error(f"Assessment agent creation failed: {e}")
+            return self.create_fallback_agent("assessment")
     
     def setup_fallback_agents(self):
         """Setup fallback agents when smolagents is not available"""
         self.curriculum_agent = self.create_fallback_agent("curriculum")
         self.content_agent = self.create_fallback_agent("content")
+        self.assessment_agent = self.create_fallback_agent("assessment")
     
     def create_fallback_agent(self, agent_type: str):
         """Create fallback agent for when smolagents is unavailable"""
@@ -177,147 +246,95 @@ class LearningAgents:
                 self.agent_type = agent_type
             
             def run(self, prompt):
+                return f"🔄 **Fallback {self.agent_type.title()} Agent**\n\n{self.generate_fallback_response(prompt)}"
+            
+            def generate_fallback_response(self, prompt):
                 if self.agent_type == "curriculum":
                     return self.generate_curriculum_fallback(prompt)
                 elif self.agent_type == "content":
                     return self.generate_content_fallback(prompt)
+                elif self.agent_type == "assessment":
+                    return self.generate_assessment_fallback(prompt)
                 else:
-                    return "Feature requires smolagents. Using fallback mode."
-            
-            def generate_curriculum_fallback(self, prompt):
-                return """
-# 📚 AI-Generated Learning Curriculum
-
-## 🎯 Structured Learning Path
-
-### Phase 1: Foundation Building
-- Core concepts and terminology
-- Essential prerequisites review
-- Hands-on introduction exercises
-
-### Phase 2: Skill Development  
-- Practical application projects
-- Guided practice sessions
-- Real-world case studies
-
-### Phase 3: Advanced Application
-- Complex problem solving
-- Integration with other topics
-- Portfolio development
-
-### 📈 Progress Milestones
-- **Week 1-2**: Foundation mastery
-- **Week 3-4**: Practical application  
-- **Week 5-6**: Advanced projects
-
-*Generated in fallback mode - Install smolagents for advanced reasoning*
-"""
-            
-            def generate_content_fallback(self, prompt):
-                return """
-# 📖 Learning Content
-
-## 🔍 Overview
-Educational content covering essential concepts.
-
-## 🎯 Key Learning Objectives
-- Understand fundamental principles
-- Apply concepts to real scenarios
-- Develop practical skills
-
-## 📚 Content Structure
-1. Introduction & Context
-2. Core Concepts
-3. Practical Examples
-4. Hands-on Exercises
-5. Assessment & Review
-
-*Generated in fallback mode*
-"""
+                    return "This feature requires smolagents. Please install with: pip install smolagents"
         
         return FallbackAgent(agent_type)
     
-    # Smolagents tools (properly decorated)
-    @tool
+    # Tool methods - decorated only when smolagents is available
     def curriculum_planning_tool(self, subject: str, level: str, goals: str) -> str:
-        """Advanced curriculum planning tool for smolagents"""
+        """Curriculum planning tool for smolagents"""
         return f"""
 # 📚 AI-Generated Curriculum: {subject}
 
 ## 🎯 Learning Path for {level.title()} Level
 
-### Customized for Goals: {goals}
-
-### Phase 1: Foundation Building (Weeks 1-2)
-- Core concepts and terminology in {subject}
+### Phase 1: Foundation Building
+- Core concepts and terminology
 - Essential prerequisites review
 - Hands-on introduction exercises
-- Initial skill assessment
 
-### Phase 2: Skill Development (Weeks 3-4)
+### Phase 2: Skill Development  
 - Practical application projects
 - Guided practice sessions
-- Real-world case studies in {subject}
-- Intermediate challenges
+- Real-world case studies
 
-### Phase 3: Advanced Application (Weeks 5-6)
+### Phase 3: Advanced Application
 - Complex problem solving
 - Integration with other topics
 - Portfolio development
-- Mastery demonstrations
 
 ### 📈 Progress Milestones
-1. **Foundation Check**: Week 2 assessment
-2. **Skill Validation**: Week 4 project review
-3. **Mastery Demo**: Week 6 final portfolio
-
-### 🔗 Recommended Next Steps
-- Advanced {subject} topics
-- Related field exploration
-- Professional application
+1. **Week 1-2**: Foundation mastery
+2. **Week 3-4**: Practical application
+3. **Week 5-6**: Advanced projects
 
-*Generated by Smolagents Multi-Agent System*
+**Personalized for:** {goals}
 """
     
-    @tool  
     def content_generation_tool(self, topic: str, difficulty: str) -> str:
         """Content generation tool for smolagents"""
         return f"""
 # 📖 Learning Content: {topic}
 
-## 🔍 Overview ({difficulty.title()} Level)
-Comprehensive educational content covering {topic} at {difficulty} level.
+## 🔍 Overview
+This {difficulty}-level content covers essential concepts in {topic}.
 
 ## 🎯 Key Learning Objectives
-- Master core concepts in {topic}
-- Apply knowledge to practical scenarios
-- Develop transferable skills
-- Build confidence in {topic}
-
-## 📚 Structured Content
-
-### 1. Introduction & Context
-Understanding the importance and applications of {topic}.
-
-### 2. Core Concepts
-Fundamental principles you need to master.
-
-### 3. Practical Examples
-Real-world applications and case studies.
-
-### 4. Hands-on Exercises
-Interactive practice opportunities.
+- Understand fundamental principles
+- Apply concepts to real scenarios
+- Develop practical skills
 
-### 5. Assessment & Review
-Check your understanding and identify areas for improvement.
+## 📚 Content Structure
+1. **Introduction & Context**
+2. **Core Concepts**
+3. **Practical Examples**
+4. **Hands-on Exercises**
+5. **Assessment & Review**
 
 ## 🚀 Next Steps
-- Practice with additional exercises
-- Explore advanced topics
-- Apply skills to personal projects
-
-*Generated by Smolagents Content Agent*
+Continue with advanced topics or apply skills in projects.
 """
+    
+    def assessment_generation_tool(self, topic: str, num_questions: int = 5) -> Dict:
+        """Assessment generation tool for smolagents"""
+        return {
+            "quiz_title": f"{topic} Assessment",
+            "questions": [
+                {
+                    "question": f"What is the main concept of {topic}?",
+                    "options": ["Option A", "Option B", "Option C", "Option D"],
+                    "correct": 0
+                } for i in range(num_questions)
+            ],
+            "difficulty": "intermediate",
+            "estimated_time": f"{num_questions * 2} minutes"
+        }
+
+# Apply @tool decorator if smolagents is available
+if SMOLAGENTS_AVAILABLE:
+    LearningAgents.curriculum_planning_tool = tool(LearningAgents.curriculum_planning_tool)
+    LearningAgents.content_generation_tool = tool(LearningAgents.content_generation_tool)
+    LearningAgents.assessment_generation_tool = tool(LearningAgents.assessment_generation_tool)
 
 # ============================================================================
 # SambaNova Audio AI Integration
@@ -339,13 +356,14 @@ class SambaNovaAudioAI:
         if not self.available:
             return {
                 "error": "SambaNova Audio AI not available",
-                "message": "Please configure SAMBANOVA_API_KEY"
+                "message": "Please set SAMBANOVA_API_KEY environment variable"
             }
         
         try:
-            # Prepare audio data
+            # Convert audio to required format
             audio_data = self.prepare_audio(audio_path)
             
+            # Prepare request for SambaNova API
             headers = {
                 "Authorization": f"Bearer {self.api_key}",
                 "Content-Type": "application/json"
@@ -357,7 +375,7 @@ class SambaNovaAudioAI:
                     {
                         "role": "user", 
                         "content": [
-                            {"type": "text", "text": prompt or "Analyze this audio for educational insights"},
+                            {"type": "text", "text": prompt or "Analyze this audio and provide educational insights"},
                             {"type": "audio", "audio": audio_data}
                         ]
                     }
@@ -391,14 +409,14 @@ class SambaNovaAudioAI:
     def prepare_audio(self, audio_path: str) -> str:
         """Prepare audio for SambaNova API"""
         try:
-            # Convert to WAV if needed
+            # Convert to WAV format if needed
             if not audio_path.endswith('.wav'):
                 audio = pydub.AudioSegment.from_file(audio_path)
                 wav_path = audio_path.replace(Path(audio_path).suffix, '.wav')
                 audio.export(wav_path, format="wav")
                 audio_path = wav_path
             
-            # Encode to base64
+            # Read and encode audio
             import base64
             with open(audio_path, 'rb') as f:
                 audio_data = base64.b64encode(f.read()).decode('utf-8')
@@ -412,9 +430,10 @@ class SambaNovaAudioAI:
     def generate_learning_plan_from_audio(self, audio_path: str) -> str:
         """Generate learning plan from audio input"""
         prompt = """
-        Analyze this audio and create a comprehensive learning plan. Include:
+        Listen to this audio and create a comprehensive learning plan. 
+        Include:
         1. Identified learning goals from the audio
-        2. Recommended curriculum structure  
+        2. Recommended curriculum structure
         3. Timeline and milestones
         4. Resources and next steps
         """
@@ -441,7 +460,7 @@ class SambaNovaAudioAI:
         """Answer questions from audio input"""
         prompt = """
         Listen to this audio question and provide a comprehensive educational answer.
-        Include:
+        Structure your response with:
         1. Clear explanation of the concept
         2. Practical examples
         3. Additional learning resources
@@ -469,34 +488,19 @@ class SambaNovaAudioAI:
     def convert_speech_to_text(self, audio_path: str) -> str:
         """Convert speech to text using local speech recognition"""
         if not AUDIO_AVAILABLE:
-            return "❌ Speech recognition libraries not available"
+            return "❌ Speech recognition not available"
         
         try:
             recognizer = sr.Recognizer()
-            
-            # Convert audio to WAV if needed
-            if not audio_path.endswith('.wav'):
-                audio = pydub.AudioSegment.from_file(audio_path)
-                wav_path = audio_path.replace(Path(audio_path).suffix, '.wav')
-                audio.export(wav_path, format="wav")
-                audio_path = wav_path
-            
             with sr.AudioFile(audio_path) as source:
                 audio_data = recognizer.record(source)
                 text = recognizer.recognize_google(audio_data)
-                return f"""
-# 🎤 Speech-to-Text Result
-
-**Transcribed Text**: {text}
-
----
-*Local Speech Recognition*
-"""
+                return f"**Transcribed Text**: {text}"
         except Exception as e:
             return f"❌ **Speech Recognition Error**: {e}"
 
 # ============================================================================
-# Main Learning Assistant
+# Main Learning Assistant Class
 # ============================================================================
 
 class LearningAssistant:
@@ -515,7 +519,7 @@ class LearningAssistant:
             if self.agents.agents_available:
                 # Use smolagents for advanced reasoning
                 prompt = f"""
-                Create comprehensive curriculum for:
+                Create a comprehensive curriculum for:
                 Subject: {subject}
                 Level: {level}
                 Goals: {goals}
@@ -526,11 +530,55 @@ class LearningAssistant:
                 return result
             else:
                 # Fallback curriculum generation
-                return self.agents.curriculum_agent.run(f"Generate curriculum for {subject} at {level} level with goals: {goals}")
+                return self.generate_fallback_curriculum(subject, level, goals)
                 
         except Exception as e:
             logger.error(f"Curriculum generation error: {e}")
-            return f"❌ **Error**: {e}\n\nTrying fallback mode..."
+            return f"❌ **Error**: {e}\n\nPlease try again or use the fallback interface."
+    
+    def generate_fallback_curriculum(self, subject: str, level: str, goals: str) -> str:
+        """Fallback curriculum generation when agents are unavailable"""
+        return f"""
+# 📚 Learning Curriculum: {subject}
+
+## 🎯 Customized for {level.title()} Level
+
+### 📋 Learning Goals
+{goals}
+
+### 🗓️ Structured Learning Path
+
+#### Phase 1: Foundation (Weeks 1-2)
+- **Core Concepts**: Introduction to {subject} fundamentals
+- **Prerequisites**: Review essential background knowledge
+- **Initial Projects**: Hands-on practice exercises
+
+#### Phase 2: Development (Weeks 3-4)  
+- **Skill Building**: Intermediate concepts and techniques
+- **Practical Applications**: Real-world project work
+- **Problem Solving**: Guided challenges and exercises
+
+#### Phase 3: Mastery (Weeks 5-6)
+- **Advanced Topics**: Complex applications and integrations
+- **Portfolio Development**: Showcase projects
+- **Knowledge Integration**: Connecting concepts across domains
+
+### 📈 Progress Tracking
+- **Weekly Assessments**: Track understanding and skill development
+- **Milestone Projects**: Demonstrate cumulative learning
+- **Peer Reviews**: Collaborative learning opportunities
+
+### 🔗 Recommended Resources
+- Online courses and tutorials
+- Practice platforms and tools
+- Community forums and support groups
+
+### 🎯 Next Steps
+Continue to advanced topics or apply skills in specialized areas.
+
+---
+*Generated by AI Learning Assistant - Fallback Mode*
+"""
     
     def process_audio_learning_request(self, audio_input) -> str:
         """Process audio input for learning plan generation"""
@@ -538,9 +586,15 @@ class LearningAssistant:
             return "❌ **Error**: No audio provided"
         
         try:
+            # Save audio from Gradio input
             audio_path = self.save_gradio_audio(audio_input)
+            
+            # Process with SambaNova
             result = self.audio_ai.generate_learning_plan_from_audio(audio_path)
+            
+            # Cleanup temp file
             self.cleanup_temp_file(audio_path)
+            
             return result
             
         except Exception as e:
@@ -581,10 +635,13 @@ class LearningAssistant:
         """Save Gradio audio input to temporary file"""
         try:
             if isinstance(audio_input, str):
+                # Already a file path
                 return audio_input
             elif hasattr(audio_input, 'name'):
+                # File object
                 return audio_input.name
             else:
+                # Handle other audio input types
                 temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
                 temp_file.write(audio_input)
                 temp_file.close()
@@ -627,10 +684,10 @@ def create_learning_interface():
     # Initialize learning assistant
     learning_assistant = LearningAssistant()
     
-    # Custom CSS
+    # Custom CSS for better styling
     custom_css = """
     .gradio-container {
-        font-family: 'Segoe UI', system-ui, sans-serif;
+        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
     }
     .main-header {
         background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
@@ -647,6 +704,14 @@ def create_learning_interface():
         margin: 1rem 0;
         border-left: 4px solid #667eea;
     }
+    .status-indicator {
+        padding: 0.5rem;
+        border-radius: 5px;
+        margin: 0.5rem 0;
+    }
+    .status-success { background: #d4edda; color: #155724; }
+    .status-warning { background: #fff3cd; color: #856404; }
+    .status-error { background: #f8d7da; color: #721c24; }
     """
     
     with gr.Blocks(css=custom_css, title="AI Learning Assistant v2.0") as interface:
@@ -657,34 +722,44 @@ def create_learning_interface():
             <h1>🤖 AI-Powered Personal Learning Assistant</h1>
             <p><strong>Version 2.0</strong> - Clean Production Build</p>
             <p>Multi-Agent Reasoning • Voice AI • Real-Time Data • ZeroGPU Optimized</p>
-            <p><em>Gradio Agents & MCP Hackathon 2025</em></p>
         </div>
         """)
         
         # System Status
-        status_html = f"""
-        <div class="feature-card">
-            <h3>🔧 System Status</h3>
-            <p>🧠 <strong>Smolagents</strong>: {'✅ Available' if SMOLAGENTS_AVAILABLE else '⚠️ Fallback Mode'}</p>
-            <p>🎤 <strong>SambaNova Audio AI</strong>: {'✅ Available' if SAMBANOVA_AVAILABLE else '⚠️ Not Configured'}</p>
-            <p>🔊 <strong>Audio Processing</strong>: {'✅ Available' if AUDIO_AVAILABLE else '⚠️ Limited'}</p>
-            <p>☁️ <strong>HuggingFace Spaces</strong>: {'✅ Available' if SPACES_AVAILABLE else '⚠️ Local Mode'}</p>
-        </div>
-        """
-        gr.HTML(status_html)
+        with gr.Row():
+            with gr.Column():
+                status_html = f"""
+                <div class="feature-card">
+                    <h3>🔧 System Status</h3>
+                    <div class="status-indicator {'status-success' if SMOLAGENTS_AVAILABLE else 'status-warning'}">
+                        🧠 <strong>Smolagents</strong>: {'Available' if SMOLAGENTS_AVAILABLE else 'Fallback Mode'}
+                    </div>
+                    <div class="status-indicator {'status-success' if SAMBANOVA_AVAILABLE else 'status-warning'}">
+                        🎤 <strong>SambaNova Audio AI</strong>: {'Available' if SAMBANOVA_AVAILABLE else 'Not Configured'}
+                    </div>
+                    <div class="status-indicator {'status-success' if AUDIO_AVAILABLE else 'status-warning'}">
+                        🔊 <strong>Audio Processing</strong>: {'Available' if AUDIO_AVAILABLE else 'Limited'}
+                    </div>
+                    <div class="status-indicator {'status-success' if SPACES_AVAILABLE else 'status-warning'}">
+                        ☁️ <strong>HuggingFace Spaces</strong>: {'Available' if SPACES_AVAILABLE else 'Local Mode'}
+                    </div>
+                </div>
+                """
+                gr.HTML(status_html)
         
         # Main Interface Tabs
         with gr.Tabs():
             
             # Tab 1: Smart Curriculum Generation
             with gr.Tab("📚 Smart Curriculum"):
-                gr.HTML('<div class="feature-card"><h3>🧠 AI-Powered Curriculum Generation</h3><p>Generate personalized learning paths using multi-agent AI reasoning</p></div>')
+                gr.HTML('<div class="feature-card"><h3>🧠 AI-Powered Curriculum Generation</h3></div>')
                 
                 with gr.Row():
                     with gr.Column():
                         subject_input = gr.Textbox(
                             label="📖 Subject/Topic",
-                            placeholder="e.g., Python Programming, Data Science, Machine Learning"
+                            placeholder="e.g., Python Programming, Data Science, Machine Learning",
+                            lines=1
                         )
                         level_input = gr.Dropdown(
                             choices=["beginner", "intermediate", "advanced"],
@@ -706,7 +781,7 @@ def create_learning_interface():
                     with gr.Column():
                         curriculum_output = gr.Markdown(
                             label="Generated Curriculum",
-                            value="*Ready to generate personalized curriculum with multi-agent AI reasoning...*"
+                            value="*Ready to generate personalized curriculum...*"
                         )
                 
                 # Event handler
@@ -725,13 +800,13 @@ def create_learning_interface():
                     outputs=[curriculum_output]
                 )
             
-            # Tab 2: Voice AI Learning  
+            # Tab 2: Voice AI Learning
             with gr.Tab("🎤 Voice AI"):
-                gr.HTML('<div class="feature-card"><h3>🎵 Voice-Powered Learning with SambaNova</h3><p>Use Qwen2-Audio-7B-Instruct for voice-based learning interactions</p></div>')
+                gr.HTML('<div class="feature-card"><h3>🎵 Voice-Powered Learning with SambaNova</h3></div>')
                 
                 with gr.Row():
                     with gr.Column():
-                        # CLEAN Audio component - NO deprecated parameters
+                        # Clean Audio component - NO deprecated parameters
                         audio_input = gr.Audio(
                             label="🎤 Record Your Learning Request",
                             type="filepath"
@@ -756,10 +831,7 @@ def create_learning_interface():
 
 **Instructions:**
 1. Click the microphone to record your voice
-2. Choose processing type:
-   - **Learning Plan**: Generate curriculum from voice
-   - **Q&A Answer**: Get answers to spoken questions  
-   - **Speech-to-Text**: Convert speech to text
+2. Choose processing type (Learning Plan, Q&A, or Speech-to-Text)
 3. Click "Process" to send to Qwen2-Audio-7B-Instruct
 
 *Powered by SambaNova Cloud*"""
@@ -790,7 +862,7 @@ def create_learning_interface():
             
             # Tab 3: User Profile
             with gr.Tab("👤 Profile"):
-                gr.HTML('<div class="feature-card"><h3>📝 Create Your Learning Profile</h3><p>Personalize your learning experience</p></div>')
+                gr.HTML('<div class="feature-card"><h3>📝 Create Your Learning Profile</h3></div>')
                 
                 with gr.Row():
                     with gr.Column():
@@ -817,7 +889,7 @@ def create_learning_interface():
                     with gr.Column():
                         profile_output = gr.Markdown(
                             label="Profile Status",
-                            value="*Ready to create your personalized learning profile...*"
+                            value="*Ready to create your learning profile...*"
                         )
                 
                 create_profile_btn.click(
@@ -863,4 +935,4 @@ if __name__ == "__main__":
         show_api=False,
         server_name="0.0.0.0",
         server_port=7860
-    ) 
+    )