app.py

import streamlit as st

from transformers import pipeline
from transformers import PegasusForConditionalGeneration, PegasusTokenizer


def summarize(data, modelname):
    if (modelname == 'Bart'):
        summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
        print("world")
        output = summarizer(data, max_length=300, min_length=30, do_sample=False)
        return output[0]["summary_text"]
    elif (modelname == 'Pegasus'):
        model = PegasusForConditionalGeneration.from_pretrained("google/pegasus-xsum")
        tokenizer = PegasusTokenizer.from_pretrained("google/pegasus-xsum")
    else:
        summarizer = pipeline("summarization", model="lidiya/bart-large-xsum-samsum")
        print("world")
        output = summarizer(data, max_length=300, min_length=30, do_sample=False)
        return output[0]["summary_text"]

        # Create tokens - number representation of our text
        tokens = tokenizer(data, truncation=True, padding="longest", return_tensors="pt")
        summary = model.generate(**tokens)
        return tokenizer.decode(summary[0])



uploaded_file = st.file_uploader("Choose a file",help=" you can choose .txt file")
data = ""
output = ""
if uploaded_file is not None:
    # To read file as bytes:
    bytes_data = uploaded_file.getvalue()

    data = bytes_data.decode("utf-8")
modelname = st.radio("Choose your model",
                             ["Bart", "Pegasus" ,"Meeting summary(bart-large-cnn-samsum)"],
                             help=" you can choose between 3 models  to summarize your text. More to come!", )
col1, col2 = st.columns(2)

with col1:
    st.header("Copy paste your text or Upload file")
    if (uploaded_file is not None):
        with st.expander("Text to summarize", expanded=True):
            st.write(
                data
            )
    else:
        with st.expander("Text to summarize", expanded=True):
            data = st.text_area("Paste your text below (max 500 words)", height=100, )

        MAX_WORDS = 500
        import re

        res = len(re.findall(r"\w+", data))
        
    Summarizebtn = st.button("Summarize")
    if (Summarizebtn):
        output = summarize(data, modelname)

with col2:
    st.header("Summary")
    
    if (len(output) > 0):
        with st.expander("", expanded=True):
            st.write(output)
    elif(Summarizebtn):
        st.balloons()