import streamlit as st
import pandas as pd
from transformers import pipeline

# Initialize the translation and summarization pipelines
translator = pipeline("translation_ru_to_en", model="Helsinki-NLP/opus-mt-ru-en")


summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

# Load your CSV file
@st.cache
def load_data(filepath):
    return pd.read_csv(filepath)

# Translate and summarize text
def translate_and_summarize(text):
    try:
        # Translate the text
        translated_text = translator(text)[0]['translation_text']
        # Summarize the translated text
        summary = summarizer(translated_text, max_length=140, min_length=110, do_sample=False)[0]['summary_text']
        return summary
    except Exception as e:
        return f"Error in processing: {str(e)}"

# Streamlit interface
def main():
    st.title('Text Summarization Tool')
    file_path = st.text_input('Enter the path to your CSV file:', '')

    if file_path:
        data = load_data(file_path)
        if 'Description' in data.columns:
            st.write("Summaries:")
            # Create a new column for summaries
            data['Summary'] = data['Description'].apply(translate_and_summarize)
            st.table(data[['ID', 'Title', 'Summary']])
        else:
            st.error("The CSV file does not have a 'Description' column.")

if __name__ == "__main__":
    main()