streamlit - mp3-to-transcription

transcribeMp3.py

import streamlit as st
from streamlit_extras.stylable_container import stylable_container
from dotenv import load_dotenv
from deepgram import (
    DeepgramClient,
    ClientOptionsFromEnv,
    PrerecordedOptions,
)
import os
st.title('audioToText+🫶')
if "url" in st.query_params:
    AUDIO_URL = {"url": st.query_params["url"]}
    st.text_input('transcribe:',AUDIO_URL)
else:
    url_input = st.text_input('url of mp3 to transcribe ')
    AUDIO_URL = {"url": url_input}   
load_dotenv() #DEEPGRAM_API_KEY
def fetch(url):
    try:
        # STEP 1 Create a Deepgram client using the API key from environment variables
        deepgram: DeepgramClient = DeepgramClient("", ClientOptionsFromEnv())
        # STEP 2 Call the transcribe_url method on the prerecorded class
        options: PrerecordedOptions = PrerecordedOptions(
            model="nova-2",
            smart_format=True,
            paragraphs=True,
            punctuate=True,
        )
        return  deepgram.listen.prerecorded.v("1").transcribe_url(url, options)
        # response['results']['channels'][0]['alternatives'][0]['paragraphs']['transcript']

    except Exception as e:
        print(f"Exception: {e}")
        return("Error")

def text_layout(msg):
  return f'<textarea cols="56" rows="20">{bucket}</textarea>'
# call dpgrm API, display the transcript in text-area using layout, markdown
if st.button('Enter'):
    with st.spinner("Transcribing..."):
        try:   
            data = fetch(AUDIO_URL)
            bucket = data['results']['channels'][0]['alternatives'][0]['paragraphs']['transcript']
            st.markdown( text_layout(bucket), unsafe_allow_html=True)
        except Exception as e:
            st.error(f"Error executing the query: {e}")

runs the server.
streamlit run transcribeMp3.py
Install
pip install the dependencies + streamlit
create an api key using the Deepgram Console
edit .env file with DEEPGRAM_API_KEY={your key}