text-matching / app.py
Keane Moraes
changes for topic modelling and embeddings
28e14c5
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import streamlit as st
from topics import Insights
import time
st.title("Drop the first document")
file1 = st.file_uploader("Upload a file", type=["md", "txt"], key="first")
st.title("Drop the second document")
file2 = st.file_uploader("Upload a file", type=["md", "txt"], key="second")
if file1 is not None and file2 is not None:
st.title("Generating insights")
with st.spinner('Generating insights...'):
insight1 = Insights(file1.read().decode("utf-8"))
insight2 = Insights(file2.read().decode("utf-8"))
st.write(insight1.generate_topics())
st.write(insight2.generate_topics())
st.write(insight1.text)
st.write(insight2.text)
embed1 = insight1.generate_embeddings()
embed2 = insight2.generate_embeddings()
st.success('Done!')