app.py

import streamlit as st
import time
from whisper_processor import process_audio

def process_audio_streamlit(audio_file, model_name, lang):
    start_time = time.time()
    result = process_audio(audio_file, model_name=model_name, lang=lang)
    end_time = time.time()
    elapsed_time = end_time - start_time
    st.write("Time taken:", elapsed_time, "seconds")
    return result

st.title("Audio Transcription")

# Upload audio file
uploaded_file = st.file_uploader("Choose an audio file")

# Select model and language
model_name = st.selectbox("Select model", ["tiny", "base", "small", "medium", "large"])
lang = st.selectbox("Select language", ["en", "hi", "fr", "de", "es", "it", "pt", "ru", "zh", "ja", "ko", "ar", "tr"])

if uploaded_file is not None:
    # Save the uploaded file to a temporary location
    with open("temp.wav", "wb") as f:
        f.write(uploaded_file.read())

    # Process the audio file
    result = process_audio_streamlit("temp.wav", model_name, lang)

    # Display the transcription result
    st.write("Transcription:")
    st.text_area("", value=result, height=300)