app.py

import streamlit as st
from transformers import pipeline

# sentiment_pipeline = pipeline("sentiment-analysis")

# st.title("Financial Sentiment Analysis Using HuggingFace")
# st.write("Enter a Sentence to Analyze the Sentiment:")

# user_input = st.text_input("")
# if user_input:
#     result = sentiment_pipeline(user_input)
#     sentiment = result[0]["label"]
#     confidence = result[0]["score"]

#     st.write(f"Sentiment: {sentiment}")
#     st.write(f"Confidence: {confidence:.2f}")

def analyze_sentiment(text):
    sentiment_analyzer = pipeline("sentiment-analysis")
    result = sentiment_analyzer(text)
    return result[0]['label'], result[0]['score']

def main():
    st.title("Financial Sentiment Analysis")

    # User input
    text_input = st.text_area("Enter financial news or tweet:", "")

    if st.button("Analyze Sentiment"):
        if text_input:
            # Analyze sentiment
            label, score = analyze_sentiment(text_input)

            # Display results
            st.write(f"Sentiment: {label}")
            st.write(f"Confidence Score: {score:.2%}")
        else:
            st.warning("Please enter some text for analysis.")

if __name__ == "__main__":
    main()