app.py

import streamlit as st
from txtai.pipeline import Summary, Textractor
from PyPDF2 import PdfReader
from deep_translator import GoogleTranslator

st.set_page_config(layout="wide")

@st.cache_resource
def text_summary(text, translate_fa, maxlength=None):
    if(len(text) > 2000):
        translatedtext1 = GoogleTranslator(source='auto', target='en').translate(text[0:2000])
        translatedtext2 = GoogleTranslator(source='auto', target='en').translate(text[2000:(len(text))])
        translatedtext = translatedtext1 + translatedtext2
        print(translatedtext1 + " .....WITH..... " + translatedtext2)
    else:
        translatedtext = GoogleTranslator(source='auto', target='en').translate(text)
        print(translatedtext)
    #create summary instance
    summary = Summary()
    result = summary(translatedtext)
    if translate_fa:
        result = GoogleTranslator(source='auto', target='fa').translate(result)
    return result

def extract_text_from_pdf(file_path):
    # Open the PDF file using PyPDF2
    with open(file_path, "rb") as f:
        reader = PdfReader(f)
        page = reader.pages[0]
        text = page.extract_text()
    return text

choice = st.selectbox("Select your choice", ["Summarize Text", "Summarize Document"])
translate_fa = st.toggle('Translate to Persian', value=True)

if choice == "Summarize Text":
    st.subheader("Summarize Text")
    input_text = st.text_area("Enter your text here")
    if input_text is not None:
        if st.button("Summarize Text"):
            col1, col2 = st.columns([1,1])
            with col1:
                st.markdown("**Summary Result**")
                result = text_summary(input_text, translate_fa)
                st.success(result)

elif choice == "Summarize Document":
    st.subheader("Summarize Document")
    input_file = st.file_uploader("Upload your document here", type=['pdf'])
    if input_file is not None:
        if st.button("Summarize Document"):
            with open("doc_file.pdf", "wb") as f:
                f.write(input_file.getbuffer())
            col1, col2 = st.columns([1,1])
            with col1:
                st.info("File uploaded successfully")
                extracted_text = extract_text_from_pdf("doc_file.pdf")
                st.markdown("**Extracted Text is Below:**")
                st.info(extracted_text)
            with col2:
                st.markdown("**Summary Result**")
                text = extract_text_from_pdf("doc_file.pdf")
                doc_summary = text_summary(text, translate_fa)
                st.success(doc_summary)