"""Routes retrieval requests to the appropriate retriever based on source_hint.

Cross-retriever merging uses Reciprocal Rank Fusion (RRF) on per-retriever
ranked lists — score scales differ across retrievers (RRF, cosine, distance)
and aren't directly comparable, so we rank-merge instead of score-merge.
"""

import asyncio
import hashlib
import json
from dataclasses import asdict
from typing import Literal

from src.db.redis.connection import get_redis
from src.middlewares.logging import get_logger
from src.rag.base import BaseRetriever, RetrievalResult

logger = get_logger("retrieval_router")

_CACHE_TTL = 3600  # 1 hour
_CACHE_KEY_PREFIX = "retrieval"
_RRF_K = 60  # standard RRF constant
SourceHint = Literal["document", "schema", "both"]


def _result_dedup_key(r: RetrievalResult) -> tuple:
    """Cross-retriever dedup key — distinguishes DB columns vs DB tables vs
    tabular columns vs prose chunks vs sheet-level chunks."""
    data = r.metadata.get("data", {})
    return (
        r.source_type,
        data.get("table_name"),
        data.get("column_name"),
        data.get("filename"),
        data.get("sheet_name"),
        data.get("chunk_index"),  # disambiguates multiple prose chunks per doc
        r.metadata.get("chunk_level"),  # distinguishes sheet vs column chunks
    )


def _rrf_merge(
    ranked_lists: list[list[RetrievalResult]],
    top_k: int,
    k_rrf: int = _RRF_K,
) -> list[RetrievalResult]:
    """Reciprocal Rank Fusion across retriever batches.

    Each input list is treated as already best-first ordered. Items are
    deduped via _result_dedup_key and re-ranked by aggregated reciprocal
    rank across all lists. Score on the returned RetrievalResult is the
    aggregated RRF score (uniform scale across legs).
    """
    scores: dict[tuple, float] = {}
    index: dict[tuple, RetrievalResult] = {}

    for ranked in ranked_lists:
        for rank, result in enumerate(ranked):
            key = _result_dedup_key(result)
            scores[key] = scores.get(key, 0.0) + 1.0 / (k_rrf + rank + 1)
            # Keep the first occurrence; metadata is identical for the same
            # key across lists, so any copy is fine.
            if key not in index:
                index[key] = result

    merged = sorted(index.values(), key=lambda r: scores[_result_dedup_key(r)], reverse=True)
    # Overwrite score with RRF score so downstream consumers see a uniform scale.
    for r in merged:
        r.score = scores[_result_dedup_key(r)]
    return merged[:top_k]


async def invalidate_retrieval_cache(user_id: str) -> int:
    """Delete every cached retrieval entry for `user_id`.

    Called by ingest/upload/delete API handlers after a successful write so
    the next retrieval picks up the new data instead of stale cached top-k.
    Returns the number of keys removed.
    """
    redis = await get_redis()
    pattern = f"{_CACHE_KEY_PREFIX}:{user_id}:*"
    keys = [key async for key in redis.scan_iter(match=pattern)]
    if not keys:
        return 0
    deleted = await redis.delete(*keys)
    logger.info("retrieval cache invalidated", user_id=user_id, deleted=deleted)
    return int(deleted)


class RetrievalRouter:
    def __init__(
        self,
        schema_retriever: BaseRetriever,
        document_retriever: BaseRetriever,
    ):
        self._retrievers: dict[str, BaseRetriever] = {
            "schema": schema_retriever,
            "document": document_retriever,
        }

    def _route(self, source_hint: SourceHint) -> list[tuple[str, BaseRetriever]]:
        if source_hint == "schema":
            return [("schema", self._retrievers["schema"])]
        if source_hint == "document":
            return [("document", self._retrievers["document"])]
        return list(self._retrievers.items())

    async def retrieve(
        self,
        query: str,
        user_id: str,
        source_hint: SourceHint = "both",
        k: int = 10,
    ) -> list[RetrievalResult]:
        redis = await get_redis()
        query_hash = hashlib.md5(query.encode()).hexdigest()
        cache_key = f"{_CACHE_KEY_PREFIX}:{user_id}:{source_hint}:{query_hash}:{k}"

        cached = await redis.get(cache_key)
        if cached:
            try:
                raw = json.loads(cached)
                logger.info("returning cached retrieval results", source_hint=source_hint)
                return [RetrievalResult(**r) for r in raw]
            except Exception:
                logger.warning("corrupted retrieval cache, fetching fresh", cache_key=cache_key)

        results = await self._retrieve_uncached(query, user_id, source_hint, k)

        # Empty-result fallback: orchestrator may have misclassified intent.
        # Retry once with "both" before giving up. No-op when source_hint is
        # already "both".
        if not results and source_hint != "both":
            logger.warning(
                "empty retrieval, falling back to source_hint='both'",
                original_source_hint=source_hint,
            )
            results = await self._retrieve_uncached(query, user_id, "both", k)

        await redis.setex(
            cache_key,
            _CACHE_TTL,
            json.dumps([asdict(r) for r in results]),
        )
        return results

    async def _retrieve_uncached(
        self,
        query: str,
        user_id: str,
        source_hint: SourceHint,
        k: int,
    ) -> list[RetrievalResult]:
        routed = self._route(source_hint)
        batches = await asyncio.gather(
            *[r.retrieve(query, user_id, k) for _, r in routed],
            return_exceptions=True,
        )

        valid_lists: list[list[RetrievalResult]] = []
        per_retriever: dict[str, int | str] = {}
        for (name, _), batch in zip(routed, batches):
            if isinstance(batch, Exception):
                logger.error("retriever failed", retriever=name, error=str(batch))
                per_retriever[name] = "error"
                continue
            valid_lists.append(batch)
            per_retriever[name] = len(batch)

        results = _rrf_merge(valid_lists, top_k=k)

        logger.info(
            "router result",
            source_hint=source_hint,
            per_retriever=per_retriever,
            final_count=len(results),
            top_score=results[0].score if results else None,
            bottom_score=results[-1].score if results else None,
        )
        return results