streamlit_app.py

import configparser
import streamlit as st
from text_search_engine import TextSearchEngine

config = configparser.ConfigParser()
config.read('config.cfg')
embeddings_csv_path = config['SERVER']['embeddings_csv_path']

text_search_engine_manager = TextSearchEngine(embeddings_csv_path)
df, model = text_search_engine_manager.load_data_and_model()
text_search_engine_manager.generate_embeddings(df, model, overwrite=False)

st.title("Text Search Engine")
text_search = st.text_input("Search movie reviews by query", value="")

if (text_search):
    results = text_search_engine_manager.semantic_search(text_search, model)

    for current_result in results['text'].values:
        st.markdown("%s"%current_result)
        st.divider()