app.py

import streamlit as st
from streamlit import session_state
import tempfile
from pathlib import Path

st.set_page_config(
    page_title="Speech Recognision",
    page_icon="📈",
)
from openai import OpenAI
client = OpenAI()
uploaded_file = st.file_uploader("Choose a file")

if uploaded_file is not None:
        # Make temp file path from uploaded file
    with tempfile.NamedTemporaryFile(delete=False) as tmp_file:
        fp = Path(tmp_file.name)
        fp.write_bytes(uploaded_file.getvalue())
        print(tmp_file.name,"path_")
    audio_file= open(tmp_file.name, "rb")
    transcript_english = client.audio.translations.create(
                 model="whisper-1", 
                 file=audio_file,temperature = 0)
    st.text_area("Transcription", value=transcript_english.text)