InterviewAnalyzer / 01_🏠_Home.py
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import whisper
import os
import pandas as pd
import plotly_express as px
import nltk
import plotly.graph_objects as go
from optimum.onnxruntime import ORTModelForSequenceClassification
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification, AutoModelForTokenClassification
from sentence_transformers import SentenceTransformer, CrossEncoder, util
import streamlit as st
import en_core_web_lg
nltk.download('punkt')
from nltk import sent_tokenize
auth_token = os.environ.get("auth_token")
st.sidebar.header("Home")
asr_model_options = ['tiny.en','base.en','small.en']
asr_model_name = st.sidebar.selectbox("Transcription model", options=asr_model_options, key="sbox")
st.markdown("## Interview analyzer")
st.markdown(
"""
**πŸ‘‡ Enter a YouTube URL below and navigate to the sidebar tabs**
"""
)
if 'sbox' not in st.session_state:
st.session_state.sbox = asr_model_name
if "earnings_passages" not in st.session_state:
st.session_state["earnings_passages"] = ''
if "sen_df" not in st.session_state:
st.session_state['sen_df'] = ''
url_input = st.text_input(
label="Enter YouTube URL, example below is McDonalds Earnings Call Q1 2023",
value="https://www.youtube.com/watch?v=4p6o5kkZYyA")
if 'url' not in st.session_state:
st.session_state['url'] = ""
st.session_state['url'] = url_input
st.markdown(
"<h3 style='text-align: center; color: red;'>OR</h3>",
unsafe_allow_html=True
)
upload_wav = st.file_uploader("Upload a .wav/.mp3/.mp4 audio file ",key="upload",type=['.wav','.mp3','.mp4'])