app.py

import gradio as gr
from transformers import pipeline

# Load your model from the Hub
pipe = pipeline("automatic-speech-recognition", model="uzair0/Katib-ASR")

def transcribe_audio(audio_filepath):
    if audio_filepath is None:
        return "⚠️ Please record some audio first!"
    result = pipe(
        audio_filepath, 
        generate_kwargs={"language": "pashto", "task": "transcribe"}
    )
    return result["text"]

demo = gr.Interface(
    fn=transcribe_audio,
    inputs=gr.Audio(sources=["microphone"], type="filepath", label="Record Pashto"),
    outputs=gr.Textbox(label="Katib ASR Transcription", lines=3),
    title="🎙️ Katib ASR: Pashto Speech Recognition",
    description="Click the Record button below, speak Pashto into your microphone, and see the result!"
)

demo.launch()