app.py

import gradio as gr
import numpy as np
import scipy.io.wavfile as wavfile
from datetime import datetime

def process_audio(sample_rate, audio_data):
    """Resample to 16kHz and save as .wav file"""
    if audio_data is None:
        return "No audio recorded", None
    
    target_sample_rate = 16000
    
    # Resample if needed
    if sample_rate != target_sample_rate:
        duration = len(audio_data) / sample_rate
        num_samples = int(duration * target_sample_rate)
        audio_data = np.interp(
            np.linspace(0, len(audio_data), num_samples),
            np.arange(len(audio_data)),
            audio_data
        )
        audio_data = audio_data.astype(np.float32)
    
    # Save to file with timestamp
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
    output_path = f"recording_{timestamp}.wav"
    audio_int16 = (audio_data * 32767).astype(np.int16)
    wavfile.write(output_path, target_sample_rate, audio_int16)
    
    status = f"Saved: {output_path} (16kHz, {len(audio_int16)/target_sample_rate:.2f}s)"
    return status, output_path

with gr.Blocks() as demo:
    gr.Markdown("# Voice Recorder")
    gr.Markdown("Record audio from microphone and save as 16kHz .wav file")
    
    audio_input = gr.Audio(sources=["microphone"], type="numpy")
    record_btn = gr.Button("Record")
    output_text = gr.Textbox(label="Status")
    output_file = gr.File(label="Download Recording", visible=True)
    
    record_btn.click(
        fn=lambda x: process_audio(16000, x) if x is not None else ("No audio", None),
        inputs=[audio_input],
        outputs=[output_text, output_file]
    )

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