app.py

import streamlit as st
from streamlit_player import st_player
from transformers import pipeline
from IPython.display import YouTubeVideo


def tester(text):
  #classifier = pipeline("sentiment-analysis", model='arpanghoshal/EmoRoBERTa')
  #classifier = pipeline("sentiment-analysis", model='cardiffnlp/twitter-roberta-base-emotion')
  #classifier = pipeline("sentiment-analysis", 'j-hartmann/emotion-english-distilroberta-base')
  classifier = pipeline("sentiment-analysis", model='bhadresh-savani/distilbert-base-uncased-emotion')
  
 
  results = classifier(text)
  st.write(results[0]['label'])
  
  if (results[0]['label']=="anger"):
    st_player("https://www.youtube.com/watch?v=kh0BWQ4Uo6w")
    
  elif (results[0]['label']=="disgust"):
    st_player("https://www.youtube.com/watch?v=zWq2TT3ieGE")
    
  elif (results[0]['label']=="fear"):
    st_player("https://www.youtube.com/watch?v=iyEUvUcMHgE")
    
  elif (results[0]['label']=="joy"):
    st_player("https://www.youtube.com/watch?v=1k8craCGpgs")
    
  elif (results[0]['label']=="sadness"):
    video = YouTubeVideo("1k8craCGpgs")
    display(video)
    #st_player("https://www.youtube.com/embed/BZsXcc_tC-o?autoplay=1")
    
  elif (results[0]['label']=="surprise"):
    st_player("https://youtu.be/CmSKVW1v0xM")
  
  
  return results[0]['label']
  #return results

emo = st.text_input('This application detects the emotion in your text input and suggests a song that matches it. Please enter text below to try:')
tester(emo)