app.py

import gradio as gr
import os

def build_interface():
    """
    Builds an enhanced Gradio interface for Bambara speech recognition.
    """
    example_files = get_example_files()
    
    custom_css = """
    .gr-button-primary {
        background-color: #2c5282 !important;
        color: white !important;
        border-radius: 8px !important;
        font-weight: bold !important;
    }
    .gr-button-secondary {
        background-color: #e2e8f0 !important;
        color: #2d3748 !important;
        border-radius: 8px !important;
    }
    .example-container {
        background-color: #f7fafc;
        padding: 16px;
        border-radius: 8px;
        margin-top: 16px;
    }
    .gr-textbox {
        border-radius: 8px !important;
        border: 1px solid #cbd5e0 !important;
    }
    .gr-audio {
        border-radius: 8px !important;
    }
    .header {
        text-align: center;
        color: #2d3748;
    }
    .info-section {
        background-color: #edf2f7;
        padding: 16px;
        border-radius: 8px;
        margin-top: 16px;
    }
    """

    with gr.Blocks(title="Bambara Speech Recognition", css=custom_css) as demo:
        # Header
        gr.Markdown(
            """
            <h1 class="header">🎤 Bambara Speech Recognition</h1>
            <p style="text-align: center; color: #4a5568;">
                Powered by <b>MALIBA-AI</b> | Convert Bambara speech to text effortlessly
            </p>
            """
        )

        # Main interaction section
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("### 🎙️ Record or Upload Audio")
                audio_input = gr.Audio(
                    label="Record or Upload Audio",
                    type="filepath",
                    sources=["microphone", "upload"],
                    show_label=False
                )
                audio_preview = gr.Audio(
                    label="Preview Your Audio",
                    interactive=False,
                    visible=False
                )

                with gr.Row():
                    transcribe_btn = gr.Button(
                        "🔄 Transcribe Audio",
                        variant="primary",
                        size="lg"
                    )
                    clear_btn = gr.Button(
                        "🗑️ Clear",
                        variant="secondary",
                        size="lg"
                    )

            with gr.Column(scale=1):
                gr.Markdown("### 📝 Transcription Output")
                output_text = gr.Textbox(
                    label="Transcribed Text (Bambara)",
                    lines=6,
                    placeholder="Your transcribed Bambara text will appear here...",
                    interactive=False,
                    show_copy_button=True
                )
                status_message = gr.Markdown(
                    value="",
                    visible=False
                )

        # Example audio section
        if example_files:
            gr.Markdown("## 🎵 Try Example Audio Files")
            with gr.Group(elem_classes="example-container"):
                gr.Markdown(
                    """
                    Listen to these sample Bambara audio files and transcribe them with one click.
                    """
                )
                for idx, file in enumerate(example_files):
                    with gr.Row():
                        gr.Audio(
                            value=file,
                            label=f"Example {idx + 1}: {os.path.basename(file)}",
                            interactive=False,
                            show_label=True
                        )
                        gr.Button(
                            f"Transcribe Example {idx + 1}",
                            variant="primary",
                            size="sm"
                        ).click(
                            fn=transcribe_audio,
                            inputs=gr.State(value=file),
                            outputs=[output_text, status_message],
                            show_progress=True,
                            _js="() => {return {show_progress: true}}"
                        )

        gr.Markdown(
            """
            <div class="info-section">
            ## ℹ️ How to Use
            
            1. **Record**: Click the microphone to speak in Bambara.
            2. **Upload**: Select an audio file (WAV, MP3, M4A, FLAC, OGG).
            3. **Transcribe**: Click "Transcribe Audio" or try an example.
            4. **View**: See the transcribed text in Bambara.
            
            ## 📊 Model Details
            
            - **Model**: [sudoping01/maliba-asr-v1](https://huggingface.co/sudoping01/maliba-asr-v1)
            - **Language**: Bambara (bm)
            - **Sample Rate**: 16kHz (auto-resampled)
            - **Best for**: Clear speech with minimal background noise
            </div>
            """
        )


        def update_audio_preview(audio_file):
            return gr.update(value=audio_file, visible=True), ""

        def clear_inputs():
            return None, "", gr.update(visible=False), ""

        def transcribe_with_status(audio_file):
            if not audio_file:
                return "", "**Error**: Please provide an audio file."
            result = transcribe_audio(audio_file)
            if "Error" in result:
                return result, f"**Error**: {result}"
            return result, "**Success**: Transcription completed!"


        audio_input.change(
            fn=update_audio_preview,
            inputs=audio_input,
            outputs=[audio_preview, status_message]
        ).then(
            fn=transcribe_with_status,
            inputs=audio_input,
            outputs=[output_text, status_message],
            show_progress=True
        )

        transcribe_btn.click(
            fn=transcribe_with_status,
            inputs=audio_input,
            outputs=[output_text, status_message],
            show_progress=True
        )

        clear_btn.click(
            fn=clear_inputs,
            outputs=[audio_input, output_text, audio_preview, status_message]
        )

    return demo