from pathlib import Path

from memabra.candidate_types import CandidateObject
from memabra.execution import ExecutionEngine, FileSystemSkillBackend, SkillExecutor
from memabra.retrieval import CandidateRetriever, InMemoryCandidateProvider
from memabra.router import RouteDecision, RuleBasedRouter, TaskContext
from memabra.runner import MemabraRunner


def test_filesystem_skill_backend_loads_skill_from_directory(tmp_path: Path):
    skill_dir = tmp_path / "category-a" / "skill-demo"
    skill_dir.mkdir(parents=True)
    skill_file = skill_dir / "SKILL.md"
    skill_file.write_text(
        "---\n"
        "name: skill-demo\n"
        "description: A demo skill for testing.\n"
        "version: 1.0.0\n"
        "---\n\n"
        "# Demo Skill\n\n"
        "This is the demo skill body.\n"
    )

    backend = FileSystemSkillBackend(search_paths=[tmp_path])
    payload = backend.load_skill("skill-demo")

    assert payload["skill_id"] == "skill-demo"
    assert payload["name"] == "skill-demo"
    assert payload["description"] == "A demo skill for testing."
    assert "This is the demo skill body." in payload["content"]


def test_filesystem_skill_backend_returns_error_for_missing_skill(tmp_path: Path):
    backend = FileSystemSkillBackend(search_paths=[tmp_path])
    payload = backend.load_skill("nonexistent")

    assert payload["skill_id"] == "nonexistent"
    assert payload["status"] == "error"
    assert "not found" in payload["error"].lower()


def test_skill_executor_uses_filesystem_backend_to_load_payload(tmp_path: Path):
    skill_dir = tmp_path / "ops" / "skill-deploy"
    skill_dir.mkdir(parents=True)
    skill_file = skill_dir / "SKILL.md"
    skill_file.write_text(
        "---\n"
        "name: skill-deploy\n"
        "description: Deploy workflow skill.\n"
        "---\n\n"
        "# Deploy Workflow\n\n"
        "1. Build\n2. Test\n3. Deploy\n"
    )

    backend = FileSystemSkillBackend(search_paths=[tmp_path])
    executor = SkillExecutor(backend=backend)
    decision = RouteDecision(decision_type="load_skill", selected_ids=["skill-deploy"])
    result = executor.execute(decision, TaskContext(user_input="deploy"), trajectory_id="traj-1")

    assert result.status == "executed"
    assert result.details["payloads"][0]["name"] == "skill-deploy"
    assert "1. Build" in result.details["payloads"][0]["content"]
    assert any(event.event_type == "skill_loaded" for event in result.events)


def test_execution_engine_runs_skill_path_end_to_end(tmp_path: Path):
    skill_dir = tmp_path / "ops" / "skill-deploy"
    skill_dir.mkdir(parents=True)
    (skill_dir / "SKILL.md").write_text(
        "---\n"
        "name: skill-deploy\n"
        "description: Deploy workflow skill.\n"
        "---\n\n"
        "Deploy steps here.\n"
    )

    retriever = CandidateRetriever(
        [
            InMemoryCandidateProvider(
                candidate_type="skill",
                candidates=[
                    CandidateObject(
                        id="skill-deploy",
                        type="skill",
                        title="deploy workflow",
                        summary="Reusable deployment procedure.",
                        triggers=["deploy", "workflow"],
                        confidence=0.9,
                        success_rate=0.95,
                        freshness=0.8,
                    )
                ],
            )
        ]
    )
    runner = MemabraRunner(
        retriever=retriever,
        router=RuleBasedRouter(),
        execution_engine=ExecutionEngine(skill_backend=FileSystemSkillBackend(search_paths=[tmp_path])),
    )

    trajectory = runner.run(context=TaskContext(user_input="Deploy this service with the usual workflow."))

    skill_events = [event for event in trajectory["events"] if event["event_type"] == "skill_loaded"]
    assert skill_events
    assert skill_events[0]["payload"]["name"] == "skill-deploy"
    assert "Deploy steps here." in skill_events[0]["payload"]["content"]