app.py

import os
import io
import streamlit as st
from audiorecorder import audiorecorder
from openai import OpenAI
import tempfile
import base64

# Set an environment variable for key
os.environ['OPENAI_API_KEY'] = os.environ.get('OPENAI_API_KEY')

def autoplay_audio(exported_audio):
    with exported_audio:
        data = exported_audio.read()
        b64 = base64.b64encode(data).decode()
        md = f"""
            <audio controls autoplay="true">
            <source src="data:audio/mp3;base64,{b64}" type="audio/mp3">
            </audio>
            """
        st.markdown(
            md,
            unsafe_allow_html=True,
        )

def transcribe_audio(filepath):
    client = OpenAI()
    audio_file = open(filepath, "rb")
    transcript = client.audio.transcriptions.create(
        model="whisper-1", 
        file=audio_file
    )   
    audio_file.close()
    return transcript
        
#model = whisper.load_model("base")
client = OpenAI()
st.title("Whisper App")
audio = audiorecorder("Click to record", "Click to stop recording")

if len(audio) > 0:
    temp_dir = tempfile.mkdtemp()
    temp_file_path = os.path.join(temp_dir, 'temp_audio.mp3')
    audio.export(temp_file_path, format="mp3")
    
    transcript = transcribe_audio(temp_file_path)
    st.write(transcript)