File size: 863 Bytes
6af6114
 
 
15f9a29
 
 
 
6af6114
15f9a29
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6af6114
15f9a29
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
import streamlit as st
from transformers import pipeline

# Load the sentiment analysis pipeline
@st.cache_resource
def load_model():
    return pipeline("sentiment-analysis")

def main():
    st.title("Sentiment Analysis App")
    
    # Create text input
    user_input = st.text_area("Enter text for sentiment analysis:")
    
    # Analyze button
    if st.button("Analyze Sentiment"):
        if user_input:
            # Load model
            sentiment_model = load_model()
            
            # Perform sentiment analysis
            result = sentiment_model(user_input)[0]
            
            # Display results
            st.write("Sentiment:", result['label'])
            st.write("Confidence Score:", f"{result['score']:.2%}")
        else:
            st.warning("Please enter some text to analyze.")

if __name__ == "__main__":
    main()