app update

app.py

@@ -0,0 +1,89 @@
+import streamlit as st
+import streamlit.components.v1 as com
+#import libraries
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig
+import numpy as np
+#convert logits to probabilities
+from scipy.special import softmax
+from transformers import pipeline
+
+#Set the page configs
+st.set_page_config(page_title='Movie Sentiments Analysis',page_icon='🎬',layout='wide')
+
+# Movie Sentiment Analysis Animation
+st.markdown("<h1 style='text-align: center'> Movie Sentiment Analysis </h1>", unsafe_allow_html=True)
+st.image("https://media.istockphoto.com/id/1055587418/vector/banner-for-online-cinema-with-old-movie-projector.jpg?s=612x612&w=0&k=20&c=ZsMSmd6CZfuUVDAvUSTb9XHBqeg4ucb43n52xV5-y1c=", use_column_width=True)
+st.write("<h2 style='font-size: 24px;'> Analyze movie reviews and discover the sentiment of the audience </h2>", unsafe_allow_html=True)
+
+
+# Create a form to take user inputs
+with st.form(key='sentence', clear_on_submit = True):  
+    # Input text
+    text = st.text_area('Copy and paste a sentence(s) or type one',
+                        placeholder='I really enjoyed the movie, it was so entertaining.')
+    # Set examples related to movie sentiments
+    alt_text = st.selectbox("Can't Type? Select an Example below", (
+        'The movie was amazing, I loved every moment of it.',
+        'I found the acting in the movie to be quite impressive.',
+        'This film was a complete waste of my time, terrible.',
+        'The plot of the movie was confusing and hard to follow.',
+        'The cinematography in this film is outstanding.'))
+    # Select a model
+    models = {
+        'Bert': 'UholoDala/sentence_sentiments_analysis_bert',
+        'Distilbert': 'UholoDala/sentence_sentiments_analysis_distilbert',
+        'Roberta': 'UholoDala/sentence_sentiments_analysis_roberta'
+    }
+    model = st.selectbox('Which model would you want to Use?', ('Bert', 'Distilbert', 'Roberta'))
+    # Submit
+    submit = st.form_submit_button('Predict', 'Continue processing input')
+
+       
+# Clear button
+clear = st.button('Clear')
+
+
+    
+selected_model=models[model]
+
+
+#create columns to show outputs
+col1,col2,col3=st.columns(3)
+col1.write('<h2 style="font-size: 24px;"> Sentiment Emoji </h2>',unsafe_allow_html=True)
+col2.write('<h2 style="font-size: 24px;"> How this user feels about the movie </h2>',unsafe_allow_html=True)
+col3.write('<h2 style="font-size: 24px;"> Confidence of this prediction </h2>',unsafe_allow_html=True)
+
+if submit:
+    #Check text
+    if text=="":
+        text=alt_text
+        st.success(f"Input text is set to:  '{text}'")    
+    else:
+        st.success('Text received',icon='✅')
+        
+    #import the model
+    pipe=pipeline(model=selected_model)
+
+#pass text to model
+    output=pipe(text)
+    output_dict=output[0]
+    lable=output_dict['label']
+    score=output_dict['score']
+    
+        #output
+    if lable=='NEGATIVE' or lable=='LABEL_0':
+        with col1:
+            com.iframe("https://embed.lottiefiles.com/animation/125694")
+        col2.write('NEGATIVE')
+        col3.write(f'{score:.2%}')
+    else:
+        lable=='POSITIVE'or lable=='LABEL_2'
+        with col1:
+            com.iframe("https://embed.lottiefiles.com/animation/148485")
+        col2.write('POSITIVE')
+        col3.write(f'{score:.2%}')
+
+# Clear button action
+text = ""  # Clear the input text
+if clear:
+    st.success('Input fields cleared', icon='✅')