Update app.py

app.py

@@ -1,9 +1,26 @@
+import streamlit as st
 from transformers import pipeline
 
-# Create a text classification pipeline
-classifier = pipeline("sentiment-analysis", model="roberta-base-openai-detector")
+# Load the sentiment analysis pipeline
+sentiment_pipeline = pipeline("sentiment-analysis")
 
-# Use the pipeline to classify some text
-result = classifier("I love using Hugging Face Transformers!")
+# Streamlit interface
+st.title("Sentiment Analysis with Hugging Face Transformers")
+
+# Input text box
+user_input = st.text_area("Enter text to analyze sentiment:", "I love using Hugging Face transformers!")
+
+# Analyze sentiment button
+if st.button("Analyze Sentiment"):
+    # Perform sentiment analysis
+    result = sentiment_pipeline(user_input)
+    
+    # Display the result
+    sentiment = result[0]['label']
+    confidence = result[0]['score']
+    st.write(f"Sentiment: **{sentiment}**")
+    st.write(f"Confidence: **{confidence:.4f}**")
+
+# To run the Streamlit app, use the command:
+# streamlit run your_script_name.py
 
-print(result)