# app.py
"""
The Studio v2.6 - Hugging Face Space Application
Streamlit interface for The Studio v2.6
"""

import streamlit as st
import asyncio
import os
import json
from pathlib import Path
from huggingface_deployment import StudioHFOrchestrator

# Streamlit configuration
st.set_page_config(
    page_title="The Studio v2.6 - AI Film Generator",
    page_icon="🎬",
    layout="wide",
    initial_sidebar_state="expanded"
)

def main():
    st.title("🎬 The Studio v2.6 - Autonomous Film Generator")
    st.markdown("""
    Transform your ideas into stunning videos with our AI-powered filmmaking system.
    Powered by Hugging Face models and advanced consistency protocols.
    """)
    
    # Sidebar configuration
    with st.sidebar:
        st.header("⚙️ Configuration")
        hf_token = st.text_input("Hugging Face Token", type="password", 
                                help="Get your token from https://huggingface.co/settings/tokens")
        
        if hf_token:
            os.environ["HF_API_TOKEN"] = hf_token
            st.success("Token set successfully!")
        
        st.divider()
        
        st.header("🎯 Sample Prompts")
        sample_prompts = [
            "A futuristic cityscape at sunset with flying cars and holographic advertisements",
            "A chef preparing gourmet food in a professional kitchen with dynamic camera movements",
            "Athletes competing in extreme sports with slow-motion action sequences",
            "Luxury travel vlog showing exotic locations and cultural experiences",
            "Fashion runway show with models showcasing designer clothing"
        ]
        
        selected_prompt = st.selectbox("Choose a sample prompt:", sample_prompts)
        
        if st.button("Use Selected Prompt"):
            st.session_state.prompt = selected_prompt
    
    # Main content area
    col1, col2 = st.columns([2, 1])
    
    with col1:
        st.header("📝 Enter Your Video Prompt")
        
        if 'prompt' not in st.session_state:
            st.session_state.prompt = ""
        
        prompt = st.text_area(
            "Describe the video you want to create:",
            value=st.session_state.prompt,
            height=200,
            placeholder="Example: A futuristic tech conference with holographic displays, showing the latest AI innovations, people interacting with virtual interfaces, dynamic camera movements capturing the excitement..."
        )
        
        title = st.text_input("Video Title:", "My AI Generated Video")
        
        if st.button("🎬 Generate Video", type="primary", disabled=not prompt or not hf_token):
            if not hf_token:
                st.error("Please enter your Hugging Face token in the sidebar!")
                return
            
            with st.spinner("🎨 Creating your video masterpiece... This may take a few minutes..."):
                try:
                    # Initialize orchestrator
                    orchestrator = StudioHFOrchestrator(hf_token)
                    
                    # Generate video
                    result = asyncio.run(
                        orchestrator.generate_video_from_prompt(prompt, title)
                    )
                    
                    if result['status'] == 'completed':
                        st.success("🎉 Video generation completed successfully!")
                        
                        # Display the generated video
                        video_file = open(result['video_path'], 'rb')
                        video_bytes = video_file.read()
                        st.video(video_bytes)
                        
                        # Show metadata
                        with st.expander("📋 Generation Details"):
                            st.json(result)
                            
                    else:
                        st.error(f"❌ Video generation failed: {result.get('error', 'Unknown error')}")
                        
                except Exception as e:
                    st.error(f"❌ An error occurred: {str(e)}")
    
    with col2:
        st.header("📈 Generation Stats")
        
        # Create some mock stats
        st.metric("Videos Generated", "247", "12+ today")
        st.metric("Success Rate", "94%", "+3% from last week")
        st.metric("Avg. Generation Time", "3.2 min", "-0.4 min from last week")
        
        st.divider()
        
        st.header("💡 Tips for Best Results")
        st.caption("• Be specific about visual elements and camera movements")
        st.caption("• Mention lighting, mood, and atmosphere")
        st.caption("• Include character descriptions if people are involved")
        st.caption("• Specify duration or number of scenes if needed")
        
        st.divider()
        
        st.header("🔧 Advanced Options")
        duration = st.slider("Estimated Duration (seconds)", 10, 60, 30)
        style = st.selectbox("Video Style", ["Cinematic", "Documentary", "Commercial", "Artistic", "Dynamic"])
        
        st.divider()
        
        if st.button("💾 Download Project"):
            # Create a project bundle
            project_data = {
                "title": title,
                "prompt": prompt,
                "style": style,
                "duration": duration,
                "generated_at": str(Path.home())
            }
            
            st.download_button(
                label="Download Project JSON",
                data=json.dumps(project_data, indent=2),
                file_name=f"{title.replace(' ', '_')}_project.json",
                mime="application/json"
            )

if __name__ == "__main__":
    main()