import gradio as gr

def process_video(video, language):
    # Sample subtitles
    subtitles = [
        ["00:00:01", "00:00:04", "Hello and welcome"],
        ["00:00:05", "00:00:08", "This is video OCR test"],
        ["00:00:09", "00:00:12", f"Selected language: {language}"],
    ]
    
    # Create SRT content
    srt_content = ""
    for i, sub in enumerate(subtitles, 1):
        srt_content += f"{i}\n{sub[0]},000 --> {sub[1]},000\n{sub[2]}\n\n"
    
    # Save SRT file
    with open("subtitles.srt", "w", encoding="utf-8") as f:
        f.write(srt_content)
    
    return subtitles, "subtitles.srt"

# Create interface
with gr.Blocks(title="Video OCR", theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🎬 Video Hardsub OCR")
    gr.Markdown("Upload video and extract hardcoded subtitles")
    
    with gr.Row():
        with gr.Column():
            video_input = gr.Video(label="Upload Video")
            language = gr.Dropdown(
                choices=["English", "Japanese", "Thai", "Chinese"],
                label="OCR Language"
            )
            process_btn = gr.Button("Process Video", variant="primary")
        
        with gr.Column():
            subtitle_output = gr.Dataframe(
                headers=["Start", "End", "Text"],
                label="Extracted Subtitles"
            )
            file_output = gr.File(label="Download SRT")
    
    process_btn.click(
        fn=process_video,
        inputs=[video_input, language],
        outputs=[subtitle_output, file_output]
    )

demo.launch()