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app.py

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+
+# Libraries
+
+import streamlit as st
+import tensorflow as tf
+from transformers import pipeline
+
+# Milestone 2
+
+# title
+st.title("Sentiment Analysis App")
+st.write("Enter some text and I'll predict its sentiment!")
+
+# add a text input box
+text_input = st.text_input("Enter your text here:", value = "The weather is nice today.")
+
+# use a select box for pretrained models
+option = st.selectbox(
+    "Select a pretrained model for sentiment analysis",
+    ("siebert/sentiment-roberta-large-english", "yiyanghkust/finbert-tone", "finiteautomata/bertweet-base-sentiment-analysis"))
+
+# display selection
+st.write("You selected:", option)
+
+# run pipeline
+sentiment_pipeline = pipeline("sentiment-analysis", model = option)
+
+# run the model when the user clicks submit
+if st.button("Submit"):
+    sentiment = sentiment_pipeline(text_input)
+    
+    # split into sentiment and score
+    sen = sentiment[0]['label']
+    score = round(sentiment[0]['score'], 4)
+    
+    # get results
+    st.write(f"Sentiment: {sen}   ,   Confidence Score: {score}")