Create app.py

app.py

@@ -0,0 +1,56 @@
+import numpy as np
+import streamlit as st
+from transformers import pipeline
+
+import torch
+
+def bertweet(data):
+    specific_model = pipeline(model="finiteautomata/bertweet-base-sentiment-analysis")
+    result = specific_model(data)
+    label = result[0]['label']
+    score = result[0]['score']
+
+    return label, score 
+
+def roberta(data):
+    specific_model = pipeline(model="cardiffnlp/twitter-roberta-base-sentiment")
+    result = specific_model(data)
+    label = result[0]['label']
+    score = result[0]['score']
+
+    if(label == 'LABEL_0'):
+        label = 'Negative'
+    elif(label == 'LABEL_1'):
+        label = 'Neutral'
+    else:
+        label = 'Positive'
+
+    return label, score 
+
+def getSent(data, model):
+    if(model == 'Bertweet'):
+        label,score = bertweet(data)
+        col1, col2 = st.columns(2)
+        col1.metric("Feeling",label,None)
+        col2.metric("Score",score,None)
+    elif(model == 'Roberta'):
+        label,score = roberta(data)
+        col1, col2 = st.columns(2)
+        col1.metric("Feeling",label,None)
+        col2.metric("Score",score,None)
+
+def rendPage():
+    st.title("Sentiment Analysis")
+    userText = st.text_input('User Input', "Hope you are having a great day!")
+    st.text("")
+    type = st.selectbox(
+        'Choose your model',
+        ('Bertweet','Roberta',))
+    st.text("")
+
+    if st.button('Calculate'):
+        if(userText!="" and type != None):
+            st.text("")
+            getSent(userText,type)
+
+rendPage()