app.py

import streamlit as st
from search_utils import SemanticSearch
import logging
import time
import psutil
from urllib.parse import quote
import threading
import re
from pathlib import Path
from urllib.parse import urlparse

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
    handlers=[logging.StreamHandler()]
)
logger = logging.getLogger("SemanticSearchApp")

# Security validation functions
def is_valid_url(url):
    """Validate URL format and safety"""
    try:
        result = urlparse(url)
        return all([result.scheme, result.netloc])
    except:
        return False

def sanitize_query(query):
    """Sanitize user input to prevent injection attacks"""
    try:
        return re.sub(r'[^\w\s-]', '', query)[:256]
    except Exception as e:
        logger.error(f"Query sanitization failed: {str(e)}")
        return query[:256]

def add_diagnostics_ui(search_system):
    """Enhanced diagnostics with accurate path handling"""
    with st.sidebar.expander("🔧 Diagnostics", expanded=False):
        col1, col2 = st.columns(2)
        
        # Metadata validation
        with col1:
            st.subheader("📂 Metadata Validation")
            metadata_dir = search_system.metadata_mgr.metadata_path
            if metadata_dir.exists():
                parquet_files = list(metadata_dir)
                status = len(parquet_files) > 0
                st.write(f"Directory: `{metadata_dir}`")
                st.write(f"Parquet Files: {len(parquet_files)}")
                st.success("✅ Valid metadata" if status else "❌ No parquet files found")
            else:
                st.error("Metadata directory not found")

        # FAISS validation
        with col2:
            st.subheader("📚 FAISS Validation")
            faiss_path = search_system.shard_dir
            if faiss_path.exists():
                st.write(f"Index Path: `{faiss_path}`")
                st.success(f"✅ Index loaded")
                st.write(f"Vectors: {search_system.total_vectors}")
            else:
                st.error("FAISS index not found")

        # System resources
        st.subheader("💻 System Resources")
        col_res1, col_res2 = st.columns(2)
        with col_res1:
            mem_usage = psutil.Process().memory_info().rss // 1024 ** 2
            st.metric("Memory Usage", f"{mem_usage} MB")

        with col_res2:
            cpu_usage = psutil.cpu_percent()
            status_color = "#ff0000" if cpu_usage > 80 else "#00ff00"
            st.markdown(f"<span style='color:{status_color}'>CPU: {cpu_usage}%</span>", 
                       unsafe_allow_html=True)

def main():
    st.set_page_config(
        page_title="Semantic Search Engine",
        page_icon="🔍",
        layout="wide"
    )

    # Custom CSS styling
    st.markdown("""
    <style>
    .metric-box {
        padding: 15px;
        border-radius: 8px;
        background: #f8f9fa;
        margin: 10px 0;
        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
    }
    .result-card {
        padding: 15px;
        border-left: 4px solid #1e88e5;
        margin: 10px 0;
        background: #fff;
    }
    </style>
    """, unsafe_allow_html=True)

    # Initialize search system
    @st.cache_resource(ttl=3600)
    def init_search_system():
        try:
            system = SemanticSearch()
            system.initialize_system()
            logger.info("Search system initialized")
            return system
        except Exception as e:
            logger.error(f"Initialization failed: {str(e)}")
            st.error("System initialization error")
            st.stop()

    try:
        search_system = init_search_system()
    except Exception as e:
        st.error(f"Critical error: {str(e)}")
        st.stop()

    # Main UI components
    st.title("🔍 Research Paper Semantic Search Engine")
    query = st.text_input("Search knowledge base:", placeholder="Enter your query...")

    if query:
        clean_query = sanitize_query(query)
        if not clean_query:
            st.warning("Invalid query format")
            st.stop()

        with st.spinner("Analyzing documents..."):
            start_time = time.time()
            try:
                results = search_system.search(clean_query, 5)
                search_duration = time.time() - start_time
                
                if results.empty:
                    st.warning("No matches found")
                    st.info("Try refining your search terms")
                else:
                    st.subheader(f"Top Results ({search_duration:.2f}s)")
                    for index, res in results.iterrows():  # Use iterrows to iterate through rows if it's a DataFrame
                        logger.info(f"Results: {res}")
                        with st.expander(res["title"]):
                            st.markdown(f"**Summary**: {res['summary']}")
                            similarity = res['similarity']
                            st.progress(similarity)
                            st.markdown(f"**Confidence**: {similarity:.1%}")
                            st.markdown(f"**Authors**: {res['authors']}")
                            source = res['source']
                            st.write("**Sources**:")
                            for url in res['source']:
                                st.markdown(f"- [{url}]({url})")

                            st.write(f"[Google Scholar Search](https://scholar.google.com/scholar?q={quote(res['title'])})")
        
            except Exception as e:
                logger.error(f"Search error: {str(e)}")
                st.error("Search operation failed")

    # System status sidebar
    with st.sidebar:
        st.subheader("📊 System Health")
        
        col1, col2 = st.columns(2)
        with col1:
            st.metric("Documents", f"{search_system.metadata_mgr.total_docs:,}")
        
        with col2:
            vectors = search_system.total_vectors
            st.metric("Vectors", f"{vectors:,}")

        # Diagnostics section
        if st.checkbox("Show advanced diagnostics"):
            add_diagnostics_ui(search_system)

        # System monitoring
        st.subheader("⚙️ Monitoring")
        with st.expander("Performance"):
            mem = psutil.virtual_memory()
            st.write(f"Memory: {mem.percent}% used")
            st.write(f"CPU Cores: {psutil.cpu_count()}")
            st.write(f"Active threads: {threading.active_count()}")

        if st.button("🔄 Refresh System"):
            st.cache_resource.clear()
            st.rerun()

if __name__ == "__main__":
    main()