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import streamlit as st | |
from src.multimodelsearch import MultiModelSearch | |
st.set_page_config( | |
layout="wide", | |
page_title="Recommendation_engine" | |
) | |
def main(): | |
st.markdown("<h1 style = 'text-align:center; color:black;'>Recommendation_engine</h1>",unsafe_allow_html=True) | |
multimodelserch = MultiModelSearch() | |
query = st.text_input("Enter Your Query") | |
if st.button("Search") and len(query) > 0: | |
result = multimodelserch.search(query=query) | |
st.info(f"Your query : {query}") | |
st.subheader("Search Results") | |
col1,col2,col3 = st.columns(3) | |
with col1: | |
st.write(f"Score: {round(result[0].score*100)}%") | |
st.image(result[0].content,use_column_width=True) | |
with col2: | |
st.write(f"Score: {round(result[1].score*100)}%") | |
st.image(result[1].content,use_column_width=True) | |
with col3: | |
st.write(f"Score: {round(result[2].score*100)}%") | |
st.image(result[2].content,use_column_width=True) | |
else: | |
st.warning("Please Enter query.......") | |
if __name__ == "__main__": | |
main() |