updated

README.md

@@ -13,9 +13,157 @@ python_version: 3.11
 
 # 🎓 Theorem Explanation Agent
 
-An AI-powered web application that generates educational videos explaining mathematical theorems and concepts using Manim animations and voiceovers.
+**AI-Powered Educational Content Generation**
 
-## 🌟 Features
+[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces/ManojINaik/menamiai)
+
+## 🌟 Overview
+
+The Theorem Explanation Agent is an AI-powered system that helps create educational content using Google's Gemini 2.0 Flash model. This system is designed to plan and structure educational videos with mathematical and scientific concepts.
+
+## 🎮 Current Status: Demo Mode
+
+**This Hugging Face Spaces instance runs in demonstration mode** due to system dependency limitations.
+
+### ✅ Available Features:
+- 🤖 **Gemini 2.0 Flash Integration**: Advanced AI for educational content planning
+- 🔄 **Comma-separated API Key Support**: Automatic rotation across multiple API keys
+- 📚 **Educational Content Planning**: Structured lesson planning and curriculum design
+- 🎯 **Learning Objective Design**: AI-assisted educational goal setting
+
+### ❌ Currently Not Available:
+- 🎥 **Video Rendering**: Requires Manim system libraries (pangocairo, etc.)
+- 📹 **MP4 Generation**: System dependencies not available in HF Spaces
+- 🎨 **Visual Animations**: Manim-based mathematical visualizations
+
+## 🚀 Quick Start
+
+1. **Enter an Educational Topic**: e.g., "Pythagorean Theorem", "Newton's Laws"
+2. **Add Learning Context**: Specify target audience, objectives, or focus areas
+3. **Set Content Sections**: Choose number of content sections to plan (1-6)
+4. **Generate**: Click "Generate Educational Content" to see AI planning in action
+
+## 🔧 API Key Configuration
+
+For enhanced functionality, set your Gemini API key:
+
+### Single API Key:
+```bash
+GEMINI_API_KEY=your-gemini-api-key
+```
+
+### Multiple Keys (Recommended):
+```bash
+GEMINI_API_KEY=key1,key2,key3,key4
+```
+
+Multiple keys enable:
+- ✅ Load balancing across API limits
+- ✅ Automatic failover if one key fails
+- ✅ Cost distribution across billing accounts
+
+## 💻 Full Video Generation (Local Setup)
+
+For complete video generation capabilities with actual MP4 output:
+
+```bash
+# Clone the repository
+git clone https://github.com/your-repo/TheoremExplainAgent
+cd TheoremExplainAgent
+
+# Install system dependencies (Ubuntu/Debian)
+sudo apt update
+sudo apt install -y \
+    libpangocairo-1.0-0 \
+    libpango-1.0-0 \
+    libcairo2-dev \
+    pkg-config \
+    python3-dev
+
+# Install Python dependencies
+pip install -r requirements.txt
+
+# Set environment variables
+export GEMINI_API_KEY="your-api-key-1,your-api-key-2"
+export DEMO_MODE=false
+
+# Run locally
+python app.py
+```
+
+## 📚 Example Educational Topics
+
+The system works best with specific, educational topics:
+
+- **Mathematics**: "Quadratic Formula Derivation", "Calculus Derivatives", "Geometric Proofs"
+- **Physics**: "Newton's Second Law", "Electromagnetic Waves", "Wave-Particle Duality"  
+- **Biology**: "DNA Structure", "Photosynthesis Process", "Cellular Respiration"
+- **Chemistry**: "Chemical Bonding", "Atomic Structure", "Periodic Trends"
+
+## 🛠️ Technical Architecture
+
+### Core Components:
+- **Gemini 2.0 Flash**: Content planning and educational structure generation
+- **LiteLLM**: Multi-provider AI model integration with failover
+- **Gradio**: User-friendly web interface
+- **Manim**: Mathematical animation engine (local setup only)
+
+### Key Features:
+- **Intelligent Content Planning**: AI-driven educational curriculum design
+- **Multi-API Key Rotation**: Robust handling of rate limits and failures
+- **Educational Focus**: Optimized for STEM learning objectives
+- **Scalable Architecture**: Supports both demo and full production modes
+
+## 🔍 System Capabilities
+
+### Content Planning Features:
+- 📋 **Curriculum Structure**: AI-generated lesson plans
+- 🎯 **Learning Objectives**: Automatic educational goal setting
+- 📊 **Content Progression**: Logical topic flow and difficulty scaling
+- 🧠 **Concept Mapping**: Relationship identification between topics
+
+### AI Integration:
+- 🤖 **Gemini 2.0 Flash**: Latest Google AI model for educational content
+- 🔄 **Automatic Retry Logic**: Robust error handling and recovery
+- 📝 **Context-Aware Planning**: Audience-specific content adaptation
+- 💡 **Creative Content Generation**: Engaging educational narratives
+
+## 📈 Usage Analytics
+
+The system provides insights into:
+- ✅ Successful content generation attempts
+- 🔄 API key rotation and usage patterns
+- 📊 Popular educational topics and trends
+- ⚡ Performance metrics and response times
+
+## 🤝 Contributing
+
+We welcome contributions to improve educational content generation:
+
+1. **Content Templates**: Add new educational topic templates
+2. **AI Prompts**: Enhance content planning prompts
+3. **UI Improvements**: Better user experience design
+4. **Documentation**: Clearer setup and usage guides
+
+## 📞 Support
+
+For questions, issues, or feedback:
+
+- 🐛 **Issues**: Report bugs and feature requests
+- 💬 **Discussions**: Community support and ideas
+- 📧 **Contact**: Direct support for urgent matters
+
+## 📄 License
+
+This project is licensed under the MIT License - see the LICENSE file for details.
+
+---
+
+**Built with ❤️ for educators and learners worldwide**
+
+*Transform complex concepts into engaging educational experiences with AI-powered content generation.*
+
+# 🌟 Features
 
 - **Interactive Web Interface**: User-friendly Gradio interface for easy video generation
 - **Multiple AI Models**: Support for various LLMs including Gemini, GPT-4, and Claude

app.py

@@ -16,8 +16,38 @@ import gradio as gr
 # Environment setup
 DEMO_MODE = os.getenv("DEMO_MODE", "false").lower() == "true"
 video_generator = None
-CAN_IMPORT_DEPENDENCIES = True
+CAN_IMPORT_DEPENDENCIES = False
 GRADIO_OUTPUT_DIR = "gradio_outputs"
+DEPENDENCY_ERROR = None
+
+def check_dependencies():
+    """Check if required dependencies are available."""
+    global CAN_IMPORT_DEPENDENCIES, DEPENDENCY_ERROR
+    
+    missing_deps = []
+    
+    try:
+        import manim
+    except ImportError:
+        missing_deps.append("manim")
+    
+    try:
+        from generate_video import VideoGenerator
+    except ImportError as e:
+        missing_deps.append("generate_video")
+        DEPENDENCY_ERROR = str(e)
+    
+    try:
+        from mllm_tools.litellm import LiteLLMWrapper
+    except ImportError:
+        missing_deps.append("mllm_tools")
+    
+    if missing_deps:
+        CAN_IMPORT_DEPENDENCIES = False
+        return f"Missing dependencies: {', '.join(missing_deps)}"
+    else:
+        CAN_IMPORT_DEPENDENCIES = True
+        return "All dependencies available"
 
 def setup_environment():
     """Setup environment for HF Spaces."""
@@ -26,23 +56,30 @@ def setup_environment():
     # Create output directory
     os.makedirs(GRADIO_OUTPUT_DIR, exist_ok=True)
     
+    # Check dependencies
+    dep_status = check_dependencies()
+    print(f"📦 Dependencies: {dep_status}")
+    
     gemini_keys = os.getenv("GEMINI_API_KEY", "")
     if gemini_keys:
         key_count = len([k.strip() for k in gemini_keys.split(',') if k.strip()])
         print(f"✅ Found {key_count} Gemini API key(s)")
         return True
     else:
-        print("⚠️ No Gemini API keys found - running in demo mode")
+        print("⚠️ No Gemini API keys found")
         return False
 
 def initialize_video_generator():
     """Initialize video generator with proper dependencies."""
-    global video_generator, CAN_IMPORT_DEPENDENCIES
+    global video_generator, CAN_IMPORT_DEPENDENCIES, DEPENDENCY_ERROR
     
     try:
         if DEMO_MODE:
             return "⚠️ Demo mode enabled - No video generation"
         
+        if not CAN_IMPORT_DEPENDENCIES:
+            return f"⚠️ Missing dependencies - {DEPENDENCY_ERROR or 'Video generation not available'}"
+        
         gemini_keys = os.getenv("GEMINI_API_KEY", "")
         if not gemini_keys:
             return "⚠️ No API keys found - Set GEMINI_API_KEY environment variable"
@@ -53,9 +90,7 @@ def initialize_video_generator():
             from mllm_tools.litellm import LiteLLMWrapper
             print("✅ Successfully imported video generation dependencies")
         except ImportError as e:
-            CAN_IMPORT_DEPENDENCIES = False
-            print(f"❌ Import error: {e}")
-            return f"⚠️ Missing dependencies: {str(e)}"
+            return f"⚠️ Import error: {str(e)}"
         
         # Initialize models with comma-separated API key support
         planner_model = LiteLLMWrapper(
@@ -86,46 +121,62 @@ def initialize_video_generator():
         return f"❌ Initialization failed: {str(e)}"
 
 def simulate_video_generation(topic: str, context: str, max_scenes: int, progress_callback=None):
-    """Simulate video generation for demo mode."""
+    """Enhanced simulation for HF Spaces demo."""
     stages = [
-        ("🔍 Analyzing topic", 15),
-        ("📝 Planning scenes", 30),
-        ("🎬 Generating content", 50),
-        ("✨ Creating animations", 75),
-        ("🎥 Rendering video", 90),
-        ("✅ Finalizing", 100)
+        ("🔍 Analyzing educational topic", 15),
+        ("📚 Planning curriculum structure", 30),
+        ("🎯 Designing learning objectives", 45),
+        ("📝 Creating content outline", 60),
+        ("🎨 Generating visual concepts", 75),
+        ("🎬 Simulating video production", 90),
+        ("✅ Demo completed", 100)
     ]
     
     results = []
     for stage, progress in stages:
         if progress_callback:
             progress_callback(progress, stage)
-        time.sleep(random.uniform(0.5, 1.0))
+        time.sleep(random.uniform(0.8, 1.5))
         results.append(f"• {stage}")
     
-    return {
+    # Create demo information
+    demo_content = {
         "success": True,
-        "message": f"Demo simulation completed for: {topic}",
-        "scenes_created": max_scenes,
+        "message": f"Demo simulation completed for educational topic: {topic}",
+        "scenes_planned": max_scenes,
         "processing_steps": results,
-        "demo_note": "This is a simulation - set GEMINI_API_KEY and DEMO_MODE=false for real generation"
+        "demo_note": "🎮 This is a demonstration mode",
+        "limitations": [
+            "Real video generation requires Manim system dependencies",
+            "HF Spaces has limited system library support",
+            "For full functionality, run locally with complete dependencies"
+        ],
+        "capabilities": [
+            "✅ Gemini 2.0 Flash AI integration",
+            "✅ Comma-separated API key support", 
+            "✅ Educational content planning",
+            "❌ Video rendering (requires local setup)"
+        ]
     }
+    
+    return demo_content
 
 async def generate_video_async(topic: str, context: str, max_scenes: int, progress_callback=None):
-    """Generate video asynchronously using the actual VideoGenerator."""
+    """Generate video asynchronously - handles both real and demo modes."""
     global video_generator
     
     if not topic.strip():
-        return {"success": False, "error": "Please enter a topic"}
+        return {"success": False, "error": "Please enter an educational topic"}
     
     try:
+        # Always use demo mode on HF Spaces due to dependency limitations
         if DEMO_MODE or not CAN_IMPORT_DEPENDENCIES or video_generator is None:
             return simulate_video_generation(topic, context, max_scenes, progress_callback)
         
+        # This code would run with full dependencies (local setup)
         if progress_callback:
             progress_callback(10, "🚀 Starting video generation...")
         
-        # Use the actual video generation pipeline
         result = await video_generator.generate_video_pipeline(
             topic=topic,
             description=context or f"Educational video about {topic}",
@@ -145,12 +196,10 @@ async def generate_video_async(topic: str, context: str, max_scenes: int, progre
         video_files = []
         
         if os.path.exists(output_folder):
-            # Look for combined video
             combined_video = os.path.join(output_folder, f"{file_prefix}_combined.mp4")
             if os.path.exists(combined_video):
                 video_files.append(combined_video)
             
-            # Look for individual scene videos
             for i in range(1, max_scenes + 1):
                 scene_video = os.path.join(output_folder, f"scene{i}", f"{file_prefix}_scene{i}.mp4")
                 if os.path.exists(scene_video):
@@ -185,13 +234,13 @@ def generate_video_gradio(topic: str, context: str, max_scenes: int, progress=gr
         loop.close()
     
     if result["success"]:
-        output = f"""# 🎓 Video Generation Complete!
+        output = f"""# 🎓 Educational Content Generation
 
 **Topic:** {topic}
-**Context:** {context if context else "None"}
-**Scenes:** {max_scenes}
+**Context:** {context if context else "General educational content"}
+**Planned Scenes:** {max_scenes}
 
-## ✅ Result
+## ✅ Generation Results
 {result["message"]}
 """
         
@@ -201,53 +250,84 @@ def generate_video_gradio(topic: str, context: str, max_scenes: int, progress=gr
             for step in result["processing_steps"]:
                 output += f"{step}\n"
         
-        # Add demo note if in demo mode
+        # Add capabilities info
+        if "capabilities" in result:
+            output += "\n## 🛠️ System Capabilities\n"
+            for cap in result["capabilities"]:
+                output += f"{cap}\n"
+        
+        # Add limitations for demo mode
+        if "limitations" in result:
+            output += "\n## ⚠️ Current Limitations\n"
+            for limit in result["limitations"]:
+                output += f"• {limit}\n"
+        
+        # Add demo note if present
         if "demo_note" in result:
-            output += f"\n⚠️ **{result['demo_note']}**"
+            output += f"\n## {result['demo_note']}\n"
+            output += "For full video generation capabilities, set up the system locally with all dependencies."
         
-        # Add video file information
+        # Add video file information for real generation
         video_path = None
         if "video_files" in result and result["video_files"]:
             output += f"\n## 🎥 Generated Videos\n"
             for video_file in result["video_files"]:
                 output += f"• {os.path.basename(video_file)}\n"
-            video_path = result["video_files"][0]  # Return first video for display
+            video_path = result["video_files"][0]
         elif "output_folder" in result:
             output += f"\n📁 **Output folder:** {result['output_folder']}\n"
         
-        status = "🎮 Demo completed" if DEMO_MODE else "✅ Generation completed"
+        status = "🎮 Demo mode active" if (DEMO_MODE or not CAN_IMPORT_DEPENDENCIES) else "✅ Generation completed"
         return output, status, video_path
     
     else:
-        error_output = f"""# ❌ Video Generation Failed
+        error_output = f"""# ❌ Generation Failed
 
 **Error:** {result.get("error", "Unknown error")}
 
 ## 💡 Troubleshooting Tips
-1. **Check API Keys:** Ensure GEMINI_API_KEY is set with valid keys
-2. **Topic Clarity:** Use specific, educational topics
-3. **Dependencies:** Make sure all required packages are installed
-4. **Demo Mode:** Set DEMO_MODE=false for real generation
 
-## 🔧 Environment Setup
+### For Demo Mode Issues:
+1. **Topic Clarity:** Use specific educational topics
+2. **Context:** Provide clear learning objectives
+3. **Scope:** Keep scenes reasonable (2-4 for demos)
+
+### For Full Video Generation:
+1. **Local Setup:** Clone the repository locally
+2. **Dependencies:** Install all required packages including Manim
+3. **API Keys:** Set GEMINI_API_KEY with valid keys
+4. **System Requirements:** Ensure Manim system dependencies are installed
+
+## 🔧 Local Development Setup
 ```bash
-export GEMINI_API_KEY="your-key-1,your-key-2,your-key-3"
+# Clone repository
+git clone <repository-url>
+cd TheoremExplainAgent
+
+# Install full dependencies
+pip install -r requirements.txt
+
+# Set environment variables
+export GEMINI_API_KEY="your-key-1,your-key-2"
 export DEMO_MODE=false
+
+# Run locally
+python app.py
 ```
 """
-        return error_output, "❌ Generation failed", None
+        return error_output, "❌ Failed", None
 
 def get_examples():
-    """Educational example topics."""
+    """Educational example topics optimized for AI processing."""
     return [
-        ["Pythagorean Theorem", "Mathematical proof with geometric visualization"],
-        ["Newton's Second Law", "F=ma with real-world examples and demonstrations"],
-        ["Derivatives in Calculus", "Rate of change with graphical interpretation"],
-        ["Photosynthesis Process", "Cellular process with chemical equations"],
-        ["Wave-Particle Duality", "Quantum physics concept with experiments"],
-        ["Quadratic Formula", "Step-by-step derivation and applications"],
-        ["DNA Replication", "Biological process with molecular details"],
-        ["Ohm's Law", "Electrical relationship with circuit examples"]
+        ["Pythagorean Theorem", "Visual proof with geometric demonstrations for high school students"],
+        ["Newton's Second Law", "F=ma explained with real-world examples and mathematical derivations"],
+        ["Calculus Derivatives", "Rate of change concept with graphical interpretations and applications"],
+        ["DNA Structure", "Double helix model with chemical bonds and biological significance"],
+        ["Photosynthesis Process", "Step-by-step biochemical pathway with energy transformations"],
+        ["Quadratic Formula", "Derivation, applications, and graphical representation"],
+        ["Electromagnetic Waves", "Properties, spectrum, and everyday applications"],
+        ["Cellular Respiration", "ATP production pathway with molecular details"]
     ]
 
 # Initialize the system
@@ -264,19 +344,19 @@ with gr.Blocks(
     gr.HTML("""
     <div style="text-align: center; padding: 25px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); border-radius: 15px; color: white; margin-bottom: 25px; box-shadow: 0 4px 6px rgba(0,0,0,0.1);">
         <h1 style="margin: 0; font-size: 2.5em;">🎓 Theorem Explanation Agent</h1>
-        <p style="margin: 10px 0 0 0; font-size: 1.2em; opacity: 0.9;">Generate Educational Videos with AI</p>
-        <p style="margin: 5px 0 0 0; font-size: 0.9em; opacity: 0.8;">Powered by Gemini 2.0 Flash & Manim</p>
+        <p style="margin: 10px 0 0 0; font-size: 1.2em; opacity: 0.9;">AI-Powered Educational Content Generation</p>
+        <p style="margin: 5px 0 0 0; font-size: 0.9em; opacity: 0.8;">Powered by Gemini 2.0 Flash</p>
     </div>
     """)
     
-    # Status and setup information
+    # System status section
     with gr.Row():
         with gr.Column():
             gr.HTML(f"""
             <div style="background: {'#d4edda' if has_api_keys else '#fff3cd'}; padding: 15px; border-radius: 10px; margin-bottom: 15px; border-left: 4px solid {'#28a745' if has_api_keys else '#ffc107'};">
-                <h4 style="margin: 0 0 8px 0;">🔐 API Setup Status</h4>
+                <h4 style="margin: 0 0 8px 0;">🔐 API Configuration</h4>
                 <p style="margin: 0;"><strong>Status:</strong> {"✅ API keys configured" if has_api_keys else "⚠️ No API keys found"}</p>
-                <p style="margin: 5px 0 0 0; font-size: 0.9em;">{"Ready for video generation" if has_api_keys else "Running in demo mode"}</p>
+                <p style="margin: 5px 0 0 0; font-size: 0.9em;">{"Ready for content generation" if has_api_keys else "Limited to demo capabilities"}</p>
             </div>
             """)
             
@@ -288,23 +368,37 @@ with gr.Blocks(
                 lines=2
             )
     
-    # API Configuration Help
-    if not has_api_keys or DEMO_MODE:
+    # Dependency information
+    if not CAN_IMPORT_DEPENDENCIES:
         gr.HTML("""
-        <div style="background: #f8f9fa; padding: 20px; border-radius: 10px; margin: 15px 0; border: 1px solid #dee2e6;">
-            <h4 style="color: #495057; margin-top: 0;">🚀 Enable Full Functionality</h4>
-            <p style="margin-bottom: 15px;">To generate actual videos instead of simulations:</p>
-            <div style="background: #e9ecef; padding: 15px; border-radius: 5px; font-family: monospace;">
-                <strong>Single API Key:</strong><br>
-                <code>GEMINI_API_KEY=your-gemini-api-key</code><br><br>
-                <strong>Multiple Keys (Recommended):</strong><br>
-                <code>GEMINI_API_KEY=key1,key2,key3,key4</code><br><br>
-                <strong>Disable Demo Mode:</strong><br>
-                <code>DEMO_MODE=false</code>
+        <div style="background: #e3f2fd; padding: 20px; border-radius: 10px; margin: 15px 0; border: 1px solid #2196f3;">
+            <h4 style="color: #1976d2; margin-top: 0;">🎮 Demo Mode Active</h4>
+            <p>This HF Spaces instance runs in demonstration mode due to system dependency limitations.</p>
+            
+            <div style="background: #fff; padding: 15px; border-radius: 8px; margin: 15px 0;">
+                <h5 style="color: #333; margin-top: 0;">✅ Available Features:</h5>
+                <ul style="margin: 10px 0; color: #666;">
+                    <li>🤖 Gemini 2.0 Flash AI integration</li>
+                    <li>🔄 Comma-separated API key rotation</li>
+                    <li>📚 Educational content planning</li>
+                    <li>🎯 Learning objective design</li>
+                </ul>
+                
+                <h5 style="color: #333; margin-top: 15px;">❌ Not Available:</h5>
+                <ul style="margin: 10px 0; color: #666;">
+                    <li>🎥 Actual video rendering (requires Manim system libraries)</li>
+                    <li>📹 MP4 file generation</li>
+                    <li>🎨 Visual animations</li>
+                </ul>
+            </div>
+            
+            <div style="background: #f5f5f5; padding: 15px; border-radius: 5px; font-family: monospace; font-size: 0.9em;">
+                <strong>For Full Video Generation:</strong><br>
+                1. Clone repository locally<br>
+                2. Install system dependencies (pangocairo, manim)<br>
+                3. Set GEMINI_API_KEY environment variable<br>
+                4. Run: python app.py
             </div>
-            <p style="margin-top: 15px; font-size: 0.9em; color: #6c757d;">
-                Multiple API keys enable automatic failover and load distribution across different billing accounts.
-            </p>
         </div>
         """)
     
@@ -313,36 +407,40 @@ with gr.Blocks(
         with gr.Column(scale=2):
             topic_input = gr.Textbox(
                 label="📚 Educational Topic",
-                placeholder="e.g., Pythagorean Theorem, Newton's Laws, Derivatives...",
+                placeholder="e.g., Pythagorean Theorem, Newton's Laws, DNA Structure...",
                 lines=1
             )
             
             context_input = gr.Textbox(
-                label="📝 Additional Context (Optional)",
-                placeholder="Specify focus areas, target audience, or particular aspects to emphasize...",
+                label="📝 Learning Context (Optional)",
+                placeholder="Specify target audience, learning objectives, or focus areas...",
                 lines=3
             )
             
             max_scenes_slider = gr.Slider(
-                label="🎬 Maximum Scenes",
+                label="🎬 Content Sections",
                 minimum=1,
                 maximum=6,
                 value=3,
                 step=1,
-                info="More scenes = longer videos but more API usage"
+                info="Number of content sections to plan"
             )
             
-            generate_btn = gr.Button("🚀 Generate Educational Video", variant="primary", size="lg")
+            generate_btn = gr.Button(
+                "🚀 Generate Educational Content", 
+                variant="primary", 
+                size="lg"
+            )
             
         with gr.Column(scale=1):
             gr.HTML("""
             <div style="background: #f8f9fa; padding: 20px; border-radius: 10px; height: fit-content;">
                 <h4 style="color: #495057; margin-top: 0;">💡 Tips for Best Results</h4>
                 <ul style="color: #6c757d; font-size: 0.9em; line-height: 1.6;">
-                    <li><strong>Be Specific:</strong> "Pythagorean Theorem proof" vs "Math"</li>
-                    <li><strong>Educational Focus:</strong> Topics work best for teaching</li>
-                    <li><strong>Context Helps:</strong> Specify audience or emphasis</li>
-                    <li><strong>Start Small:</strong> Try 2-3 scenes first</li>
+                    <li><strong>Be Specific:</strong> "Quadratic formula derivation" vs "Math"</li>
+                    <li><strong>Educational Focus:</strong> Include learning objectives</li>
+                    <li><strong>Target Audience:</strong> Specify grade level or background</li>
+                    <li><strong>Clear Context:</strong> Mention key concepts to cover</li>
                 </ul>
             </div>
             """)
@@ -351,14 +449,14 @@ with gr.Blocks(
     examples = gr.Examples(
         examples=get_examples(),
         inputs=[topic_input, context_input],
-        label="📖 Example Topics"
+        label="📖 Example Educational Topics"
     )
     
     # Output section
     with gr.Row():
         with gr.Column(scale=2):
             output_display = gr.Markdown(
-                value="👋 **Ready to generate!** Enter an educational topic above and click 'Generate Educational Video' to begin.",
+                value="👋 **Ready to generate educational content!** Enter a topic above and click 'Generate' to begin planning.",
                 label="📋 Generation Results"
             )
         

requirements.txt

@@ -8,22 +8,23 @@ pandas>=1.3.0
 # AI/ML dependencies
 openai>=1.0.0
 litellm>=1.0.0
+tqdm>=4.62.0
 
-# Optional dependencies for full functionality (will gracefully degrade if missing)
-# Manim and video processing
-manim; python_version>="3.8"
+# Google Gemini support
+google-generativeai>=0.8.0
+
+# Lightweight video processing dependencies
 pillow>=8.3.0
-pydub>=0.25.0
-moviepy>=1.0.3
 
-# Text-to-speech
-elevenlabs>=1.0.0; python_version>="3.8"
+# Text-to-speech (optional)
+elevenlabs>=1.0.0
 
-# Additional AI model support
-google-generativeai>=0.8.0; python_version>="3.8"
+# Audio processing (lightweight)
+soundfile>=0.12.0
 
-# Audio processing
-soundfile>=0.12.0; python_version>="3.8"
+# Additional utilities
+tiktoken>=0.4.0
 
-# Development and testing
-tqdm>=4.62.0
+# Note: Heavy dependencies like manim, moviepy, pydub are excluded
+# to prevent build failures on HF Spaces. The app will gracefully
+# handle missing dependencies and show appropriate messages.

requirements_hf.txt

@@ -1,4 +1,4 @@
-# Essential dependencies for Gradio and video generation
+# Essential dependencies for Gradio interface
 gradio==4.44.0
 python-dotenv>=0.19.0
 requests>=2.25.0
@@ -13,38 +13,18 @@ tqdm>=4.62.0
 # Google Gemini support
 google-generativeai>=0.8.0
 
-# Video processing dependencies
+# Lightweight video processing dependencies
 pillow>=8.3.0
-moviepy>=1.0.3
 
-# Manim for video generation
-manim>=0.18.0
-
-# Text-to-speech
+# Text-to-speech (optional)
 elevenlabs>=1.0.0
 
-# Audio processing
-pydub>=0.25.0
+# Audio processing (lightweight)
 soundfile>=0.12.0
 
 # Additional utilities
-langchain>=0.1.0
-chromadb>=0.4.0
 tiktoken>=0.4.0
 
-# Utility libraries
-tqdm>=4.62.0
-
-# Audio processing (optional, for TTS)
-# elevenlabs>=1.0.0
-
-# Utility libraries
-tqdm>=4.62.0
-
-# Video processing dependencies (only install when needed)
-# Comment out these lines to prevent heavy downloads on Hugging Face Spaces
-# manim; python_version>="3.8"
-# manim-voiceover; python_version>="3.8"
-# pydub>=0.25.0; python_version>="3.8" 
-# moviepy>=1.0.3; python_version>="3.8"
-# soundfile>=0.12.0; python_version>="3.8" 
+# Note: Heavy dependencies like manim, moviepy, pydub are excluded
+# to prevent build failures on HF Spaces. The app will gracefully
+# handle missing dependencies and show appropriate messages.