Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+# Load the sentiment analysis pipeline
+pipe = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis")
+
+# Define a function to perform sentiment analysis
+def analyze_sentiment(text):
+    results = pipe(text)
+    sentiment = results[0]['label']
+    confidence = results[0]['score']
+    return sentiment, confidence
+
+# Create a Streamlit app
+st.title("Sentiment Analysis App")
+
+# Get the user input
+text = st.text_input("Enter text for sentiment analysis")
+
+# Perform sentiment analysis
+sentiment, confidence = analyze_sentiment(text)
+
+# Display the output
+if sentiment == "POSITIVE":
+    st.success(f"Sentiment: Positive, Confidence: {confidence:.2f}")
+elif sentiment == "NEGATIVE":
+    st.error(f"Sentiment: Negative, Confidence: {confidence:.2f}")
+else:
+    st.info(f"Sentiment: Neutral, Confidence: {confidence:.2f}")