from __future__ import annotations

import sys
import types

import pytest

from kg_ocr.embeddings import create_and_index
from kg_ocr.rag import retrieve


class _FakeEmbeddings:
    instances: list[_FakeEmbeddings] = []

    def __init__(self, config):
        self.config = config
        self.indexed: list[str] | None = None
        _FakeEmbeddings.instances.append(self)

    def index(self, data):
        self.indexed = data


def _install_fake_txtai(monkeypatch: pytest.MonkeyPatch) -> None:
    fake_txtai = types.ModuleType("txtai")
    fake_embeddings_mod = types.ModuleType("txtai.embeddings")
    fake_embeddings_mod.Embeddings = _FakeEmbeddings  # type: ignore[attr-defined]
    monkeypatch.setitem(sys.modules, "txtai", fake_txtai)
    monkeypatch.setitem(sys.modules, "txtai.embeddings", fake_embeddings_mod)


def test_create_and_index_config_and_data(monkeypatch: pytest.MonkeyPatch) -> None:
    _install_fake_txtai(monkeypatch)
    emb = create_and_index(["alpha", "beta"], model="some-model")
    assert emb.config["path"] == "some-model"
    assert emb.config["content"] is True
    assert emb.config["hybrid"] is True
    assert emb.indexed == ["alpha", "beta"]


def test_create_and_index_raises_without_txtai(monkeypatch: pytest.MonkeyPatch) -> None:
    monkeypatch.setitem(sys.modules, "txtai", None)
    monkeypatch.setitem(sys.modules, "txtai.embeddings", None)
    with pytest.raises(ImportError, match="txtai"):
        create_and_index(["x"])


def test_retrieve_passes_through() -> None:
    class FakeEmb:
        def search(self, query, limit):
            return [{"text": f"{query}-{i}", "score": 1.0} for i in range(limit)]

    out = retrieve(FakeEmb(), "q", limit=2)
    assert out == [{"text": "q-0", "score": 1.0}, {"text": "q-1", "score": 1.0}]