import streamlit as st
import pandas as pd
from textblob import TextBlob


def load_data(csv_file):
    df = pd.read_csv(csv_file)
    return df


def convert_to_rating(sentiment):
    if sentiment > 0:
        return 5
    elif sentiment == 0:
        return 3
    else:
        return 1


def main():
    st.title("Review to Rating Converter")

    # Upload CSV file
    uploaded_file = st.file_uploader("Upload a CSV file", type="csv")

    if uploaded_file is not None:
        # Load the CSV file
        df = load_data(uploaded_file)

        # Perform sentiment analysis and convert to ratings
        df['Sentiment'] = df['Reviews'].apply(lambda x: TextBlob(x).sentiment.polarity)
        df['Rating'] = df['Sentiment'].apply(convert_to_rating)

        # Display the converted ratings
        st.subheader("Converted Ratings:")
        st.dataframe(df[['Reviews', 'Rating']])

        # Download the converted ratings as CSV
        st.download_button(
            label="Download Converted Ratings",
            data=df[['Reviews', 'Rating']].to_csv(index=False),
            file_name="converted_ratings.csv",
            mime="text/csv"
        )


if __name__ == '__main__':
    main()