app.py

import streamlit as st
from transformers import pipeline


import os
import io
import tempfile
import base64
from audiorecorder import audiorecorder
from openai import OpenAI
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")
    


########################     models
# model = pipeline("sentiment-analysis")
# st.title("Hugging Face Model Demo")
# input_text = st.text_input("Enter your text", "")
# if st.button("Analyze"):
#     # Perform inference using the loaded model
#     result = model(input_text)
#     st.write("Prediction:", result[0]['label'], "| Score:", result[0]['score'])