text_summarizer / app.py
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Create app.py
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import streamlit as st
from model import Abstractive_Summarization_Model
# initialize model object
# @st.cache
def load_model():
return Abstractive_Summarization_Model()
# Main app engine
if __name__ == "__main__":
# display title and description
st.title("AI Text Summarizer")
st.header("Get AI generated paraphrased summaries of text!")
st.write("You might need to wait a couple of seconds for the model to load because i'm using a tiny cpu 🥲")
st.write("email me at darveenvijayan.27@gmail.com")
#load model
ASM = load_model()
# display topic input slot
text = st.text_input("Paste a paragraph of text in the text box below and hit ENTER!", "")
# display article paragraph
article_paragraph = st.empty()
if text:
# load wikipedia summary of topic
summary = ASM.summarize(text)
# display article summary in paragraph
article_paragraph.markdown(summary)