app.py

import gradio as gr
import whisper
import os

# Load Whisper model
model = whisper.load_model("base")

# Function to transcribe audio file using Whisper
def transcribe_audio(audio_file):
    # Check if the audio file exists and print the file path for debugging
    if audio_file is None:
        return "No audio file provided."
    
    # Debugging: Print the file path to check if Gradio passes the file path correctly
    print(f"Audio file path: {audio_file}")
    
    if not os.path.exists(audio_file):
        return "The audio file does not exist or is inaccessible."

    # Load and transcribe the audio file
    result = model.transcribe(audio_file)
    transcription = result['text']
    
    return transcription

# Gradio interface for transcription
iface = gr.Interface(
    fn=transcribe_audio,   # Function to process audio file
    inputs=gr.Audio(type="filepath"),  # Audio upload, pass file path
    outputs="text",       # Output the transcription as text
    title="Whisper Audio Transcription",
    description="Upload an audio file and get the transcription."
)

# Launch the Gradio interface with a shareable link (required for Colab)
iface.launch(share=True)