"""
Animetrix AI - Gradio Interface for Hugging Face Spaces
Educational Animation Generator powered by AI and Manim
"""

import gradio as gr
import os
import sys
from pathlib import Path
import asyncio
import shutil

# Add backend to path
backend_path = Path(__file__).parent / "backend"
sys.path.insert(0, str(backend_path))

from dotenv import load_dotenv
load_dotenv()

# Configure FFmpeg for Hugging Face Spaces (already available in system PATH)
if shutil.which('ffmpeg') is None:
    print("⚠️ FFmpeg not found - installing...")
    os.system("apt-get update && apt-get install -y ffmpeg")

# Import backend functions
from teacher import generate_outline
from compiler import generate_manim_code
from runner import render_scene
from narrator import generate_narration_audio, merge_audio_video

async def generate_animation(prompt, progress=gr.Progress()):
    """Generate educational animation from text prompt"""
    try:
        # Validate input
        if not prompt or len(prompt.strip()) < 10:
            return None, "❌ Please enter a more detailed prompt (at least 10 characters)"
        
        progress(0, desc="🎯 Initializing...")
        
        # Step 1: Generate outline
        progress(0.1, desc="📚 Planning animation structure...")
        outline = await generate_outline(prompt)
        
        # Step 2: Generate per-step narration
        progress(0.3, desc="🎙️ Generating narration audio...")
        steps = outline.get("steps", [])
        step_audio_paths = []
        
        for idx, step in enumerate(steps):
            narration = step.get("narration", "")
            if narration:
                audio_filename = f"step_{idx+1}_narration.mp3"
                audio_path = generate_narration_audio(narration, filename=audio_filename)
                step_audio_paths.append(audio_path)
                progress(0.3 + (0.1 * (idx+1) / len(steps)), desc=f"🎙️ Narration {idx+1}/{len(steps)}...")
            else:
                step_audio_paths.append(None)
        
        # Step 3: Generate Manim code
        progress(0.5, desc="💻 Generating animation code...")
        code = await generate_manim_code(outline, step_audio_paths=step_audio_paths)
        
        # Step 4: Render video
        progress(0.7, desc="🎬 Rendering video (this takes 30-60s)...")
        video_path = await render_scene(code)
        
        # Step 5: Merge audio
        progress(0.9, desc="🔊 Finalizing with audio...")
        if any(step_audio_paths):
            # For now, merge the first available audio
            first_audio = next((a for a in step_audio_paths if a), None)
            if first_audio and os.path.exists(first_audio):
                video_path = merge_audio_video(video_path, first_audio)
        
        progress(1.0, desc="✅ Complete!")
        
        # Return video and success message
        if os.path.exists(video_path):
            return video_path, f"✅ Animation generated successfully!\n\n📊 Stats:\n- Steps: {len(steps)}\n- Topic: {outline.get('topic', 'N/A')}"
        else:
            return None, "❌ Video file not found after rendering"
        
    except Exception as e:
        error_msg = f"❌ Error: {str(e)}\n\nPlease try:\n1. A simpler prompt\n2. Check if GEMINI_API_KEY is set\n3. Report this issue on GitHub"
        print(f"Error in generate_animation: {e}")
        import traceback
        traceback.print_exc()
        return None, error_msg

def generate_sync(prompt):
    """Synchronous wrapper for Gradio"""
    return asyncio.run(generate_animation(prompt))

# Example prompts
EXAMPLES = [
    ["Explain the Pythagorean theorem with a right triangle and show a^2 + b^2 = c^2"],
    ["Show how binary search algorithm works with a sorted array"],
    ["Visualize the structure of an atom with nucleus and orbiting electrons"],
    ["Demonstrate how compound interest grows over time with a graph"],
    ["Explain Newton's first law of motion with a simple example"],
    ["Show bubble sort algorithm sorting an array step by step"],
]

# Custom CSS
custom_css = """
.gradio-container {
    font-family: 'Inter', sans-serif;
}
.contain {
    max-width: 1200px;
    margin: auto;
}
footer {
    display: none !important;
}
"""

# Create Gradio interface
with gr.Blocks(
    theme=gr.themes.Soft(
        primary_hue="orange",
        secondary_hue="gray",
        neutral_hue="slate",
    ),
    css=custom_css,
    title="Animetrix AI - Educational Animation Generator"
) as demo:
    
    gr.Markdown(
        """
        # 🎬 Animetrix AI
        ## AI-Powered Educational Animation Generator
        
        Transform your ideas into professional educational animations using AI and Manim.
        Powered by Google Gemini and Manim Community Edition.
        """
    )
    
    with gr.Row():
        with gr.Column(scale=3):
            prompt_input = gr.Textbox(
                label="💡 Describe the concept you want to animate",
                placeholder="e.g., Explain how photosynthesis works in plants...",
                lines=4,
                max_lines=6
            )
            
            with gr.Row():
                clear_btn = gr.ClearButton([prompt_input])
                submit_btn = gr.Button("🎬 Generate Animation", variant="primary", size="lg")
        
        with gr.Column(scale=2):
            gr.Markdown(
                """
                ### 💡 Tips for Best Results
                
                - **Be specific**: Include what you want to see
                - **Use simple language**: Avoid complex jargon
                - **Mention visuals**: Circles, arrows, graphs, etc.
                - **Keep it focused**: One concept per animation
                
                ### ⏱️ Processing Time
                - Planning: ~5 seconds
                - Narration: ~10 seconds  
                - Rendering: ~30-60 seconds
                
                **Total: 1-2 minutes**
                """
            )
    
    video_output = gr.Video(label="📹 Generated Animation", height=400)
    status_output = gr.Textbox(label="Status", lines=4, show_label=True)
    
    gr.Markdown("### 📚 Example Prompts (Click to try)")
    gr.Examples(
        examples=EXAMPLES,
        inputs=[prompt_input],
        label="Try these examples:"
    )
    
    gr.Markdown(
        """
        ---
        ### 🛠️ Tech Stack
        - **AI**: Google Gemini 2.0 Flash
        - **Animation**: Manim Community Edition
        - **Narration**: gTTS (Google Text-to-Speech)
        - **Video Processing**: MoviePy + FFmpeg
        
        ### 🔗 Links
        - [GitHub Repository](https://github.com/SayedZahur786/Animetrix_AI)
        - [Report Issues](https://github.com/SayedZahur786/Animetrix_AI/issues)
        - [Documentation](https://github.com/SayedZahur786/Animetrix_AI#readme)
        
        **Made with ❤️ by Sayed Zahur**
        """
    )
    
    # Event handlers
    submit_btn.click(
        fn=generate_sync,
        inputs=[prompt_input],
        outputs=[video_output, status_output],
        api_name="generate"
    )

# Launch configuration
if __name__ == "__main__":
    demo.queue(max_size=5).launch(
        server_name="0.0.0.0",
        server_port=7860,
        show_error=True
    )