app.py

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

# Load 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")

# Function to translate and summarize text





def translate_and_summarize(text):
    translated_text = translator(text)[0]['translation_text']
    summary = summarizer(translated_text, max_length=140, min_length=110, do_sample=False)[0]['summary_text']
    return summary






# Streamlit interface
def main():
    st.title("CSV Translator and Summarizer")

    # File uploader
    uploaded_file = st.file_uploader("Choose a CSV file", type="csv")
    if uploaded_file is not None:
        # Read data
        data = pd.read_csv(uploaded_file)

        # Check if 'Description' column exists

        if 'Description' in data.columns:
            # Apply translation and summarization

            data['Summary'] = data['Description'].apply(translate_and_summarize)

            # Display data in a table
            st.write(data[['ID', 'Title', 'Summary']])

        else:
            st.error("Uploaded CSV does not contain 'Description' column.")

if __name__ == "__main__":
    main()