app.py

import streamlit as st
from transformers import pipeline

# Load the sentiment analysis model
sentiment_analyzer = pipeline("sentiment-analysis", model="distilbert-base-uncased")

def main():
    st.title("Know your Writing Mood")
    
    # Text input area for the user's creative writing
    writing = st.text_area("Enter your creative writing:")

    if st.button("Go"):
        if writing:
            analyze_writing_feedback(writing)
        else:
            st.warning("Please enter some text.")

def analyze_writing_feedback(writing):
    sentiment_result = sentiment_analyzer(writing)
    sentiment_label = sentiment_result[0]['label']
    
    feedback = generate_feedback(sentiment_label)
    
    st.subheader("Feedback for Creative Writing:")
    st.write(feedback)

def generate_feedback(sentiment_label):
    if sentiment_label == "LABEL_1":
        feedback = "Your writing has a positive sentiment! It evokes a sense of optimism and positivity."
    elif sentiment_label == "LABEL_0":
        feedback = "Your writing has a negative sentiment. It might be helpful to focus on brighter and more uplifting themes."
    else:
        feedback = "Your writing is neutral. Consider adding more emotional depth to enhance the impact."
    
    return feedback

if __name__ == "__main__":
    main()