"""Shared synthesis fixtures — keep DB/LLM/embed fully mocked."""

from __future__ import annotations

from pathlib import Path
from typing import Any
from unittest.mock import MagicMock

import pytest

# Shared corpus fixture used across the test suite.
FIXTURE_CHUNKS: list[dict[str, Any]] = [
    {
        "id": 1,
        "paper_id": "springborn-2008",
        "ord": 16,
        "content": (
            "For an ideal tetrahedron with dihedral angles the hyperbolic volume is "
            "V = L(gamma1) + L(gamma2) + L(gamma3). "
            "The volume function V0 is strictly concave on the angle domain."
        ),
        "bibkey": "Springborn2008",
    },
    {
        "id": 2,
        "paper_id": "bps-2015",
        "ord": 3,
        "content": (
            "A discrete conformal map is defined by logarithmic scale factors u_i "
            "at each vertex such that the edge lengths satisfy a compatibility condition."
        ),
        "bibkey": "BobenkoPinkallSpringborn2015",
    },
    {
        "id": 3,
        "paper_id": "luo-2004",
        "ord": 0,
        "content": (
            "The combinatorial Yamabe flow drives the edge lengths towards a target "
            "curvature on a triangulated surface."
        ),
        "bibkey": "Luo2004",
    },
]


class StubLLM:
    """Deterministic mock LLM that returns a preset response."""

    def __init__(self, response: str | list[str]) -> None:
        if isinstance(response, str):
            self._responses = [response]
        else:
            self._responses = list(response)
        self._calls: list[tuple[str, str]] = []

    def generate(self, prompt: str, model: str) -> str:
        self._calls.append((prompt, model))
        if not self._responses:
            return ""
        if len(self._responses) == 1:
            return self._responses[0]
        return self._responses.pop(0)

    @property
    def calls(self) -> list[tuple[str, str]]:
        return list(self._calls)


@pytest.fixture
def stub_llm() -> StubLLM:
    """Default stub returning empty string (override per test as needed)."""
    return StubLLM("")


@pytest.fixture
def fixture_chunks() -> list[dict[str, Any]]:
    return [dict(c) for c in FIXTURE_CHUNKS]


@pytest.fixture
def mock_retrieve(monkeypatch: pytest.MonkeyPatch) -> None:
    """Patch _retrieve_chunks to return deterministic fixture chunks (no DB)."""
    monkeypatch.setattr(
        "codex.synthesis._retrieve_chunks",
        lambda queries, top_k: [dict(c) for c in FIXTURE_CHUNKS],
    )


@pytest.fixture
def mock_paper_titles(monkeypatch: pytest.MonkeyPatch) -> None:
    """Patch _list_paper_titles to return a deterministic three-paper corpus."""
    monkeypatch.setattr(
        "codex.synthesis._list_paper_titles",
        lambda db_conn: [
            ("Springborn2008", "A variational principle for weighted Delaunay triangulations"),
            (
                "BobenkoPinkallSpringborn2015",
                "Discrete conformal maps and ideal hyperbolic polyhedra",
            ),
            ("Luo2004", "Combinatorial Yamabe Flow on Surfaces"),
        ],
    )


@pytest.fixture
def mock_settings(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> Path:
    """Settings stub pointing leads_dir at tmp_path/leads."""
    from codex.config import Settings

    leads_path = tmp_path / "leads"

    mock = MagicMock(spec=Settings)
    mock.leads_dir = str(leads_path)
    mock.synthesis_llm_model = "test-model"
    mock.synthesis_llm_url = None
    mock.ollama_base_url = "http://localhost:11434"
    mock.synthesis_top_k = 6
    mock.synthesis_min_grounded_ratio = 0.5
    mock.synthesis_gap_min_coverage = 2
    mock.wiki_dir = str(tmp_path / "wiki")

    monkeypatch.setattr("codex.synthesis.get_settings", lambda: mock)
    return leads_path