"""
app.py — Streamlit search interface for Enabley RAG.
Run: streamlit run app.py
"""

import streamlit as st
from rag import RAGIndex

st.set_page_config(page_title="🔍 Enabley Smart Search", layout="wide")

st.title("🔍 Enabley Smart Search")
st.caption("Semantic search over training course content — Hebrew / English / Russian")


@st.cache_resource
def load_index():
    rag = RAGIndex()
    rag.load()
    return rag


try:
    rag = load_index()
    st.success(f"Index loaded: {rag.index.ntotal} chunks indexed")
except Exception as e:
    st.error(f"No index found. Run `python rag.py build` first.\n\nError: {e}")
    st.stop()


query = st.text_input(
    "Search query / שאילתת חיפוש",
    placeholder="e.g. מתי נגמר הרישום? / what documents do I need?",
)

top_k = st.slider("Number of results", 1, 10, 5)

if query:
    results = rag.search(query, top_k=top_k)

    st.markdown(f"### Results for: *{query}*")

    for i, r in enumerate(results, 1):
        score = r["score"]
        source = r.get("source", "unknown")
        text = r["text"]

        # Color-code relevance
        if score > 0.85:
            badge = "🟢"
        elif score > 0.70:
            badge = "🟡"
        else:
            badge = "🔴"

        with st.expander(f"{badge} Result {i} — score: {score:.3f} — [{source}]", expanded=(i <= 3)):
            st.markdown(text)
            if "slide" in r:
                st.caption(f"📄 Slide {r['slide']}")
            if "page" in r:
                st.caption(f"📄 Page {r['page']}")