import streamlit as st from streamlit_player import st_player from transformers import pipeline from IPython.display import YouTubeVideo import random import streamlit as st import streamlit.components.v1 as components 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']=="joy"): a = 1 if a == 1: components.html("""""",width=560,height=325) elif (results[0]['label']=="anger"): components.html("""""",width=560,height=325) 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?&autoplay=1") elif (results[0]['label']=="sadness"): #video = YouTubeVideo("1k8craCGpgs") #display(video) #st_player("https://www.youtube.com/watch?v=BZsXcc_tC-o") # embed streamlit docs in a streamlit app #components.html("""""",width=560,height=325) components.html("""""",width=560,height=325) elif (results[0]['label']=="surprise"): st_player("https://youtu.be/CmSKVW1v0xM") st.write("check out this [link](https://open.spotify.com/playlist/4yXfnhz0BReoVfwwYRtPBm)") elif (results[0]['label']=="love"): st_player("https://www.youtube.com/watch?v=XVhEm62Uqog") 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)