"""Shared fixtures for EvoScientist tests."""

from pathlib import Path

import pytest

_NONEXISTENT_DOTENV = str(Path(__file__).with_name(".pytest-dotenv-does-not-exist"))


@pytest.fixture
def sample_tool_call():
    """A minimal tool call dict."""
    return {"id": "tc_001", "name": "execute", "args": {"command": "ls -la"}}


@pytest.fixture
def sample_tool_result():
    """A minimal tool result dict."""
    return {
        "id": "tc_001",
        "name": "execute",
        "content": "[OK] file1.py file2.py",
        "success": True,
    }


@pytest.fixture
def sample_events():
    """A sequence of stream event dicts covering common types."""
    return [
        {"type": "thinking", "content": "Let me think..."},
        {"type": "text", "content": "Here is the answer."},
        {
            "type": "tool_call",
            "id": "tc_001",
            "name": "execute",
            "args": {"command": "ls"},
        },
        {
            "type": "tool_result",
            "id": "tc_001",
            "name": "execute",
            "content": "[OK] done",
            "success": True,
        },
        {
            "type": "subagent_start",
            "name": "research-agent",
            "description": "Find papers",
            "instance_id": "task:research",
            "tool_call_id": "tc_task_001",
        },
        {
            "type": "subagent_tool_call",
            "subagent": "research-agent",
            "instance_id": "task:research",
            "name": "tavily_search",
            "args": {"query": "test"},
            "id": "tc_sa_001",
        },
        {
            "type": "subagent_tool_result",
            "subagent": "research-agent",
            "instance_id": "task:research",
            "name": "tavily_search",
            "content": "Results...",
            "success": True,
            "id": "tc_sa_001",
        },
        {
            "type": "subagent_end",
            "name": "research-agent",
            "instance_id": "task:research",
        },
        {"type": "done", "response": "Here is the answer."},
    ]


@pytest.fixture
def tmp_workspace(tmp_path):
    """Provide a temporary workspace directory path."""
    ws = tmp_path / "workspace"
    ws.mkdir()
    return str(ws)


@pytest.fixture
def runtime_paths(tmp_path, monkeypatch):
    """Isolate ``langgraph_dev.manager.RUNTIME`` under a temp directory.

    Replaces the module-level ``RUNTIME`` with a fully temp-rooted bundle
    so every path (``pid_dir``, ``pid_file``, ``log_file``,
    ``workspace_sidecar``, ``lock_file``) is contained under ``tmp_path``.

    Tests that need a variant of a single field can still call
    ``dataclasses.replace(runtime_paths, log_file=…)`` etc. — the
    baseline is already isolated, so forgetting a field just keeps it
    under ``tmp_path``, never ``~/.config/evoscientist``.
    """
    from EvoScientist.langgraph_dev import manager

    runtime = manager.LanggraphRuntimePaths.for_directory(tmp_path / "runtime")
    monkeypatch.setattr(manager, "RUNTIME", runtime)
    return runtime


# Capture deepagents tool factories at conftest load time — BEFORE any test
# imports EvoScientist, which can trigger ``_patch_deepagents_model_passthrough``
# during agent construction. Once captured here, the ``restore_model_passthrough_patch``
# fixture has a stable "truly unpatched" baseline to reset to between tests, even
# if upstream code paths apply the patch as a side effect.
try:
    from deepagents.middleware import async_subagents as _ds_async_subagents

    _DEEPAGENTS_ORIGINAL_BUILD_START = _ds_async_subagents._build_start_tool
    _DEEPAGENTS_ORIGINAL_BUILD_UPDATE = _ds_async_subagents._build_update_tool
except Exception:
    _ds_async_subagents = None
    _DEEPAGENTS_ORIGINAL_BUILD_START = None
    _DEEPAGENTS_ORIGINAL_BUILD_UPDATE = None


@pytest.fixture
def restore_model_passthrough_patch():
    """Reset deepagents internals + ``_model_passthrough_patched`` to unpatched.

    The model-passthrough patch wraps ``deepagents.middleware.async_subagents``
    module-level functions in place. The originals are captured at conftest
    load time (above) so this fixture can always start each test from a
    known-unpatched state regardless of what other tests / agent fixtures
    did to the module before.
    """
    from EvoScientist.llm import patches as patches_mod

    if _ds_async_subagents is None:
        # deepagents not importable — fixture is a no-op (the patch fn itself
        # returns early in that case).
        yield
        return

    def _reset() -> None:
        _ds_async_subagents._build_start_tool = _DEEPAGENTS_ORIGINAL_BUILD_START
        _ds_async_subagents._build_update_tool = _DEEPAGENTS_ORIGINAL_BUILD_UPDATE
        patches_mod._model_passthrough_patched = False

    _reset()
    try:
        yield
    finally:
        _reset()


@pytest.fixture(autouse=True)
def _isolate_dotenv(monkeypatch):
    """Keep the developer's real .env out of the test environment.

    ``get_effective_config`` runs ``load_dotenv(find_dotenv(usecwd=True),
    override=True)``, so any test that loads config injects the repo's
    real .env into ``os.environ`` for the rest of the pytest process.
    An empty-valued line like ``MINIMAX_BASE_URL=`` then makes
    ``os.environ.get(key, default)`` return "" instead of the default,
    breaking unrelated tests later in the run (see issue #322).

    Pointing ``find_dotenv`` at a fixed path that does not exist makes
    ``load_dotenv`` a no-op without creating a temporary directory for
    every test.
    """
    monkeypatch.setattr(
        "EvoScientist.config.settings.find_dotenv",
        lambda *args, **kwargs: _NONEXISTENT_DOTENV,
    )