app.py

import gradio as gr
from transformers import pipeline
import traceback

# 1) Load ASR pipeline
asr = pipeline(
    "automatic-speech-recognition",
    model="tacab/ASR_SOMALI",
    chunk_length_s=30,   # kala jar haddii audio-ga dheer yahay
    device=-1            # CPU; haddii GPU doorato, u beddel 0
)

def transcribe(audio_filepath):
    """
    audio_filepath: jidka faylka WAV ee la duubay.
    Haddii user-ku duubin waayo, soo celi fariin.
    """
    if not audio_filepath:
        return "Fadlan marka hore duub cod, ka dibna riix ‘Turjun’."
    try:
        result = asr(audio_filepath)
        return result.get("text", "Qoraal lama helin.")
    except Exception as e:
        traceback.print_exc()
        return f"Khalad inta lagu turjunayo:\n{e}"

with gr.Blocks() as demo:
    gr.Markdown("## Qalabka Tacab ASR ee Af-Soomaaliga")
    with gr.Row():
        mic = gr.Audio(
            sources=["microphone"],    
            type="filepath",           
            label="Duub Cod Af-Soomaali ah"
        )
        btn = gr.Button("Turjun")
    txt_out = gr.Textbox(
        label="Qoraalka Turjumaadda",
        interactive=False,
        placeholder="Halkaan ayuu qoraalkaaga ka soo muuqan doonaa…"
    )

    btn.click(fn=transcribe, inputs=[mic], outputs=[txt_out])

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