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from transformers import pipeline
import streamlit as st
import pandas as pd
# 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=150, min_length=120, 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 and data['Published'] != 'checked':
# 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()
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