"""Search API routes — keyword + semantic search."""

from __future__ import annotations

from fastapi import APIRouter, Query

from core import restaurant, vector, cache
from core.db import conn

router = APIRouter()


@router.get("")
def search_restaurants(
    q: str = Query(..., min_length=1),
    mode: str = Query("keyword", pattern="^(keyword|semantic|hybrid)$"),
    limit: int = Query(20, le=100),
):
    """Search restaurants by keyword, semantic similarity, or hybrid."""
    key = cache.make_key("search", f"q={q}", f"m={mode}", f"l={limit}")
    cached = cache.get(key)
    if cached is not None:
        return cached

    if mode == "semantic":
        result = _semantic_search(q, limit)
        cache.set(key, result)
        return result
    elif mode == "hybrid":
        kw = _keyword_search(q, limit)
        sem = _semantic_search(q, limit)
        # merge: keyword results first, then semantic results not already in keyword
        seen = {r["id"] for r in kw}
        merged = list(kw)
        for r in sem:
            if r["id"] not in seen:
                merged.append(r)
                seen.add(r["id"])
        result = merged[:limit]
        cache.set(key, result)
        return result
    else:
        result = _keyword_search(q, limit)
        cache.set(key, result)
        return result


def _keyword_search(q: str, limit: int) -> list[dict]:
    # JOIN video_restaurants to also search foods_mentioned and video title
    sql = """
        SELECT DISTINCT r.id, r.name, r.address, r.region, r.latitude, r.longitude,
               r.cuisine_type, r.price_range, r.google_place_id,
               r.business_status, r.rating, r.rating_count
        FROM restaurants r
        JOIN video_restaurants vr ON vr.restaurant_id = r.id
        JOIN videos v ON v.id = vr.video_id
        WHERE r.latitude IS NOT NULL
          AND (UPPER(r.name) LIKE UPPER(:q)
               OR UPPER(r.address) LIKE UPPER(:q)
               OR UPPER(r.region) LIKE UPPER(:q)
               OR UPPER(r.cuisine_type) LIKE UPPER(:q)
               OR UPPER(vr.foods_mentioned) LIKE UPPER(:q)
               OR UPPER(v.title) LIKE UPPER(:q))
        FETCH FIRST :lim ROWS ONLY
    """
    pattern = f"%{q}%"
    with conn() as c:
        cur = c.cursor()
        cur.execute(sql, {"q": pattern, "lim": limit})
        cols = [d[0].lower() for d in cur.description]
        rows = [dict(zip(cols, row)) for row in cur.fetchall()]

    # Attach channel names
    if rows:
        _attach_channels(rows)
    return rows


def _semantic_search(q: str, limit: int) -> list[dict]:
    similar = vector.search_similar(q, top_k=max(30, limit * 3))
    if not similar:
        return []

    # Deduplicate by restaurant_id, preserving distance order (best first)
    seen: set[str] = set()
    ordered_ids: list[str] = []
    for s in similar:
        rid = s["restaurant_id"]
        if rid not in seen:
            seen.add(rid)
            ordered_ids.append(rid)

    results = []
    for rid in ordered_ids[:limit]:
        r = restaurant.get_by_id(rid)
        if r and r.get("latitude"):
            results.append(r)

    if results:
        _attach_channels(results)
    return results


def _attach_channels(rows: list[dict]):
    """Attach channel names to each restaurant dict."""
    ids = [r["id"] for r in rows]
    placeholders = ", ".join(f":id{i}" for i in range(len(ids)))
    sql = f"""
        SELECT DISTINCT vr.restaurant_id, c.channel_name
        FROM video_restaurants vr
        JOIN videos v ON v.id = vr.video_id
        JOIN channels c ON c.id = v.channel_id
        WHERE vr.restaurant_id IN ({placeholders})
    """
    params = {f"id{i}": rid for i, rid in enumerate(ids)}
    ch_map: dict[str, list[str]] = {}
    with conn() as c:
        cur = c.cursor()
        cur.execute(sql, params)
        for row in cur.fetchall():
            ch_map.setdefault(row[0], []).append(row[1])
    for r in rows:
        r["channels"] = ch_map.get(r["id"], [])