app.py

import gradio as gr
from video_accent_analyzer import VideoAccentAnalyzer
import plotly.graph_objects as go
import pandas as pd

analyzer = VideoAccentAnalyzer()


def create_plotly_chart(probabilities):
    """Create an interactive Plotly bar chart for accent probabilities"""
    accents = [analyzer.accent_display_names.get(acc, acc.title()) for acc in probabilities.keys()]
    probs = list(probabilities.values())

    colors = ['#4CAF50' if p == max(probs) else '#2196F3' if p >= 20
    else '#FFC107' if p >= 10 else '#9E9E9E' for p in probs]

    fig = go.Figure(data=[
        go.Bar(
            x=accents,
            y=probs,
            marker_color=colors,
            text=[f'{p:.1f}%' for p in probs],
            textposition='auto',
        )
    ])

    fig.update_layout(
        title='Accent Probability Distribution',
        xaxis_title='Accent Type',
        yaxis_title='Probability (%)',
        template='plotly_white',
        yaxis_range=[0, 100],
    )

    return fig


def analyze_video(url=None, video_file=None, duration=30):
    """Analyze video from URL or file with enhanced output"""
    try:
        if not url and not video_file:
            return (
                "### ❌ Error\nPlease provide either a video URL or upload a video file.",
                None
            )

        if url:
            result = analyzer.analyze_video_url(url, max_duration=duration)
        else:
            result = analyzer.analyze_local_video(video_file, max_duration=duration)

        if 'error' in result:
            return (
                f"### ❌ Error\n{result['error']}",
                None
            )

        # Create markdown output
        markdown = f"""
    ### 🎯 Analysis Results
    
    **Primary Classification:**
    - 🗣️ Predicted Accent: {analyzer.accent_display_names.get(result['predicted_accent'])}
    - 📊 Confidence: {result['accent_confidence']:.1f}%
    - 🌍 English Confidence: {result['english_confidence']:.1f}%
    
    **Audio Analysis:**
    - ⏱️ Duration: {result['audio_duration']:.1f} seconds
    - 📊 Quality Score: {result.get('audio_quality_score', 'N/A')}
    - 🎵 Chunks Analyzed: {result.get('chunks_analyzed', 1)}
    
    **Assessment:**
    - {'✅ Strong English Speaker' if result['english_confidence'] >= 70 else '⚠️ Moderate English Confidence' if result['english_confidence'] >= 50 else '❓ Low English Confidence'}
    - {'🎯 High Accent Confidence' if result['accent_confidence'] >= 70 else '🤔 Moderate Accent Confidence' if result['accent_confidence'] >= 50 else '❓ Low Accent Confidence'}
    """

        # Create visualization
        fig = create_plotly_chart(result['all_probabilities'])

        return markdown, fig

    except Exception as e:
        return f"### ❌ Error\nAn unexpected error occurred: {str(e)}", None


# Create Gradio interface
css = """
    .gradio-container {
        font-family: 'IBM Plex Sans', sans-serif;
    }
    .gr-button {
        background: linear-gradient(45deg, #4CAF50, #2196F3);
        border: none;
    }
    .gr-button:hover {
        background: linear-gradient(45deg, #2196F3, #4CAF50);
        transform: scale(1.02);
    }
    """

with gr.Blocks(css=css) as interface:
    gr.Markdown("""
        # 🎧 Video Accent Analyzer
        
        Analyze English accents in videos from various sources:
        - MP4 videos
        - Loom recordings
        - Direct video links
        - Uploaded video files
        
        ### 💡 Tips
        - Keep videos under 2 minutes for best results
        - Ensure clear audio quality
        - Multiple speakers may affect accuracy
        """)

    with gr.Row():
        with gr.Column():
            url_input = gr.Textbox(
                label="Video URL",
                placeholder="Enter , Loom, or direct video URL"
            )
            video_input = gr.File(
                label="Or Upload Video",
                file_types=["video"]
            )
            duration = gr.Slider(
                minimum=10,
                maximum=120,
                value=30,
                step=10,
                label="Maximum Duration (seconds)"
            )
            analyze_btn = gr.Button("🔍 Analyze Video", variant="primary")

        with gr.Column():
            output_text = gr.Markdown(label="Analysis Results")
            output_plot = gr.Plot(label="Accent Distribution")

    analyze_btn.click(
        fn=analyze_video,
        inputs=[url_input, video_input, duration],
        outputs=[output_text, output_plot]
    )

    gr.Examples(
        examples=[
            ["https://www.loom.com/share/7b82b3e25ec8409a8e4b5568e95dca5c?sid=e0819070-d2ba-4236-a7a0-878c8739040f", None, 30],
        ],
        inputs=[url_input, video_input, duration],
        outputs=[output_text, output_plot],
        label="Example Videos"
    )


if __name__ == "__main__":
    interface.launch()