app.py

import gradio as gr
from faster_whisper import WhisperModel

# Load the model (adjust as needed: tiny, base, small, etc.)
model = WhisperModel("base", compute_type="int8")  # Optimized for CPU

# Transcription function
def transcribe(audio_file):
    if audio_file is None:
        return "No file provided."

    # Run transcription
    segments, _ = model.transcribe(audio_file)
    transcript = " ".join([segment.text for segment in segments])
    return transcript

# Gradio Interface
iface = gr.Interface(
    fn=transcribe,
    inputs=gr.File(type="filepath", label="Upload Audio (MP3, WAV, FLAC, etc.)"),
    outputs=gr.Textbox(label="Transcript"),
    title="Whisper Transcriber (Multi-Format)",
    description="Upload an audio file in any format (MP3, WAV, FLAC, etc.) to transcribe using Faster-Whisper."
)

# Launch the app
iface.launch()