Create app.py

app.py

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+import streamlit as st
+from nltk.sentiment.vader import SentimentIntensityAnalyzer
+import nltk
+
+# Ensure the VADER lexicon is downloaded
+nltk.download('vader_lexicon')
+
+
+class SentimentAnalyzer:
+    def __init__(self):
+        self.analyzer = SentimentIntensityAnalyzer()
+
+    def analyze_sentiment(self, sentence):
+        return self.analyzer.polarity_scores(sentence)
+
+
+def fool():
+    analyzer = SentimentAnalyzer()
+
+    st.title("Sentiment Analysis App")
+    st.write("Enter a sentence to analyze its sentiment:")
+
+    # Input text box for user input
+    sentence = st.text_input("Input sentence:")
+
+    if st.button("Analyze"):
+        if sentence:
+            # Perform sentiment analysis
+            result = analyzer.analyze_sentiment(sentence)
+
+            # Interpret sentiment label
+            compound_score = result['compound']
+            if compound_score >= 0.05:
+                sentiment_type = 'Positive'
+            elif compound_score <= -0.05:
+                sentiment_type = 'Negative'
+            else:
+                sentiment_type = 'Neutral'
+
+            # Display sentiment analysis result
+            st.write(f"Sentiment: {sentiment_type}, Score: {compound_score:.4f}")
+
+
+# Call fool function directly if the script is executed
+fool()