Spaces:
Sleeping
Sleeping
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() | |