app.py

from transformers import pipeline
import gradio as gr

# Load Whisper model
print("Loading model...")
pipe = pipeline(model="jsbeaudry/whisper-medium-oswald")
print("Model loaded successfully.")

# Transcription function
def transcribe(audio_path):
    if audio_path is None:
        return "Please upload or record an audio file first."
    result = pipe(audio_path)
    return result["text"]

# Build Gradio interface
def create_interface():
    with gr.Blocks(title="Whisper Medium - Haitian Creole") as demo:
        gr.Markdown("# 🎙️ Whisper Medium Creole ASR")
        gr.Markdown(
            "Upload an audio file or record your voice in Haitian Creole. "
            "Then click **Transcribe** to see the result."
        )

        with gr.Row():
            with gr.Column():
                audio_input = gr.Audio(source="upload", type="filepath", label="🎧 Upload Audio")
                audio_input2 = gr.Audio(source="microphone", type="filepath", label="🎤 Record Audio")
            with gr.Column():
                transcribe_button = gr.Button("🔍 Transcribe")
                output_text = gr.Textbox(label="📝 Transcribed Text", lines=4)
                
    
        transcribe_button.click(fn=transcribe, inputs=audio_input, outputs=output_text)
        transcribe_button.click(fn=transcribe, inputs=audio_input2, outputs=output_text)

    return demo

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