import streamlit as st
from search_utils import SemanticSearch
def main():
st.set_page_config(
page_title="Semantic Search Engine",
page_icon="🔍",
layout="wide"
)
# Initialize search system first
@st.cache_resource
def init_search_system():
system = SemanticSearch()
system.initialize_system()
return system
# Custom CSS moved outside cached function
st.markdown("""
""", unsafe_allow_html=True)
search_system = init_search_system()
# Main UI components
st.title("🔍 Semantic Search Engine")
query = st.text_input("Enter your search query:", placeholder="Search documents...")
if query:
with st.spinner("🔍 Searching through documents..."):
results = search_system.search(query, 5)
if not results.empty:
st.subheader("Top Results")
for _, row in results.iterrows():
with st.expander(f"{row['title']} (Similarity: {row['similarity']:.1%})"):
st.markdown(f"**Summary**: {row['summary']}")
st.markdown(f"View Source",
unsafe_allow_html=True)
else:
st.warning("No matching documents found")
# System status sidebar
with st.sidebar:
st.subheader("System Status")
st.metric("Total Documents", f"{search_system.metadata_mgr.total_docs:,}")
st.metric("FAISS Shards", len(search_system.index_shards))
st.metric("Metadata Shards", len(search_system.metadata_mgr.shard_map))
# Sidebar controls outside main query block
with st.sidebar:
if st.button("Clear Cache"):
st.cache_resource.clear()
st.rerun()
if __name__ == "__main__":
main()