from __future__ import annotations

from typing import Any

from qdrant_client.http import models as qm

from app.config import get_settings
from app.rag import embeddings
from app.rag.store import COLLECTION_DOC_CHUNKS, COLLECTION_FACTS, search


def _document_filter(user_id: int, document_id: int | None = None) -> qm.Filter:
    must: list[qm.FieldCondition] = [
        qm.FieldCondition(key="user_id", match=qm.MatchValue(value=user_id))
    ]
    if document_id is not None:
        must.append(qm.FieldCondition(key="document_id", match=qm.MatchValue(value=document_id)))
    return qm.Filter(
        must=must
    )


async def retrieve_memory_facts(
    query: str, *, user_id: int, top_k: int | None = None
) -> list[dict[str, Any]]:
    settings = get_settings()
    if not settings.rag_enabled or not query.strip():
        return []
    k = top_k or settings.rag_top_k
    vectors = await embeddings.embed_texts([query])
    if not vectors:
        return []
    hits = search(COLLECTION_FACTS, vectors[0], limit=k, query_filter=_document_filter(user_id))
    results: list[dict[str, Any]] = []
    for hit in hits:
        payload = hit.payload or {}
        results.append(
            {
                "id": payload.get("fact_id") or hit.id,
                "category": payload.get("category", "fact"),
                "content": payload.get("content", ""),
                "score": hit.score,
            }
        )
    return results


async def retrieve_document_chunks(
    query: str, *, user_id: int, top_k: int = 6, document_id: int | None = None
) -> list[dict[str, Any]]:
    settings = get_settings()
    if not settings.rag_enabled or not query.strip():
        return []
    vectors = await embeddings.embed_texts([query])
    if not vectors:
        return []
    hits = search(
        COLLECTION_DOC_CHUNKS,
        vectors[0],
        limit=top_k,
        query_filter=_document_filter(user_id, document_id),
    )
    out: list[dict[str, Any]] = []
    for hit in hits:
        payload = hit.payload or {}
        out.append(
            {
                "document_id": payload.get("document_id"),
                "chunk_id": payload.get("chunk_id"),
                "chunk_index": payload.get("chunk_index"),
                "title": payload.get("title", ""),
                "filename": payload.get("filename", ""),
                "mime_type": payload.get("mime_type", ""),
                "page_start": payload.get("page_start"),
                "page_end": payload.get("page_end"),
                "section_title": payload.get("section_title", ""),
                "section_path": payload.get("section_path", ""),
                "source_ref": payload.get("source_ref", ""),
                "content": payload.get("content", ""),
                "score": hit.score,
            }
        )
    return out