print("=" * 60)
print("HinglishCaps - Clean Version")
print("=" * 60)

import gradio as gr

print("Gradio imported successfully")

with gr.Blocks(title="HinglishCaps - Auto Captions", css="""
    .gradio-container { max-width: 900px !important; margin: auto; }
    .tab-nav { background: #f5f5f5; border-radius: 8px; padding: 10px; }
""") as app:
    
    gr.Markdown("""
    # 🎬 HinglishCaps - Auto Captions for Hindi/English Videos
    
    This is a demo interface for the HinglishCaps captioning tool.
    
    **Full AI transcription requires running the app locally** due to memory
    constraints on Hugging Face Spaces free tier.
    """)
    
    with gr.Tabs():
        with gr.TabItem("Single Video"):
            gr.Markdown("### Process a single video")
            video = gr.Video(label="Upload Video")
            btn = gr.Button("Generate Demo Captions", variant="primary")
            output = gr.File(label="Download Demo File")
            
            def create_demo(video_path):
                # Create a simple demo file
                import tempfile
                import os
                
                content = """1
00:00:00,000 --> 00:00:05,000
Demo caption file for HinglishCaps.

2
00:00:05,000 --> 00:00:10,000
To use the full AI transcription feature:

3
00:00:10,000 --> 00:00:15,000
Run the app locally on your machine."""
                
                temp_dir = tempfile.gettempdir()
                filepath = os.path.join(temp_dir, "demo_captions.srt")
                with open(filepath, "w", encoding="utf-8") as f:
                    f.write(content)
                
                return filepath
            
            btn.click(create_demo, inputs=[video], outputs=[output])
        
        with gr.TabItem("Batch Processing"):
            gr.Markdown("### Process multiple videos")
            videos = gr.File(label="Upload Videos", file_count="multiple")
            batch_btn = gr.Button("Generate Demo Batch", variant="primary")
            zip_output = gr.File(label="Download Demo ZIP")
            
            def create_batch(files):
                import tempfile
                import os
                import zipfile
                
                temp_dir = tempfile.gettempdir()
                zip_path = os.path.join(temp_dir, "demo_batch.zip")
                
                with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
                    for i in range(min(3, len(files) if files else 0)):
                        filename = f"video_{i+1}_captions.srt"
                        content = f"""1
00:00:00,000 --> 00:00:05,000
Demo captions for video {i+1}

2
00:00:05,000 --> 00:00:10,000
Batch processing demo

3
00:00:10,000 --> 00:00:15,000
Run locally for AI transcription"""
                        zipf.writestr(filename, content)
                
                return zip_path
            
            batch_btn.click(create_batch, inputs=[videos], outputs=[zip_output])
    
    gr.Markdown("---")
    gr.Markdown("""
    ### Getting the Full Version
    
    The full HinglishCaps app with AI transcription is available in the
    repository files. To use it:
    
    1. **Clone the repository** to your local machine
    2. **Install dependencies** from `requirements_full.txt`
    3. **Run `python app_full.py`**
    
    The full app uses the Oriserve/Whisper-Hindi2Hinglish-Apex model for
    accurate Hindi-English transcription.
    """)

print("Launching app...")
app.launch(share=True, server_name="0.0.0.0")