app.py

import torch
from transformers import pipeline
import gradio as gr
def transcript_audio(audio_file):
    # Initialize the speech recognition pipeline
    pipe = pipeline(
  "automatic-speech-recognition",
  model="openai/whisper-tiny.en",
  chunk_length_s=30,
)    
    # Transcribe the audio file and return the result
    result = pipe(audio_file, batch_size=8)["text"]
    return result
audio_input = gr.Audio(sources="upload", type="filepath")  # Audio input
output_text = gr.Textbox()  # Text output

iface = gr.Interface(fn=transcript_audio, 
                     inputs=audio_input, outputs=output_text, 
                     title="Audio Transcription App: Summarize your audio - Created by Nabeel",
                     description="Upload the audio file")

iface.launch(server_name="0.0.0.0", server_port=7860,share=True)