"""Integration tests for /api/stats/dashboard aggregation."""

import pytest
from fastapi.testclient import TestClient
from sqlmodel import Session, SQLModel, create_engine

from agenteval.models import (
    Case, CaseType, ChannelType, EvalRun, EvalTarget, PlatformType,
    RunStatus, RunTrigger, Scenario, TargetStatus,
)
from agenteval.storage.repository import RunRepository, ScenarioRepository, TargetRepository
from agenteval.web.app import app
from agenteval.web.deps import get_db


@pytest.fixture()
def client_with_db(tmp_path):
    from agenteval.storage.db import (  # noqa: F401
        EvalResultDB, EvalRunDB, EvalTargetDB, ModelConfigDB, ScenarioDB, TurnDB,
    )
    engine = create_engine(
        f"sqlite:///{tmp_path / 'stats_api.db'}",
        connect_args={"check_same_thread": False},
    )
    SQLModel.metadata.create_all(engine)
    session = Session(engine)

    def override_get_db():
        try:
            yield session
        finally:
            pass

    app.dependency_overrides[get_db] = override_get_db
    client = TestClient(app)
    yield client, session
    app.dependency_overrides.clear()
    session.close()


def _seed(session: Session) -> None:
    target = TargetRepository(session).create(EvalTarget(
        name="对象A", platform=PlatformType.AI_DIGITAL_EMPLOYEE,
        channel_type=ChannelType.TUTU_API, channel_config={}, status=TargetStatus.ACTIVE,
    ))
    scenario = ScenarioRepository(session).create(Scenario(
        name="场景A", cases=[Case(id="c1", type=CaseType.SINGLE, messages=["hi"])],
    ))
    repo = RunRepository(session)
    for pass_rate, trigger in [(1.0, RunTrigger.MANUAL), (0.5, RunTrigger.AI_ASSISTANT)]:
        run = repo.create(EvalRun(
            target_id=target.id, scenario_id=scenario.id,
            status=RunStatus.COMPLETED, triggered_by=trigger,
        ))
        run.summary = {"total_cases": 2, "passed_cases": 1, "failed_cases": 1,
                       "total_rules": 2, "passed_rules": 1, "pass_rate": pass_rate}
        repo.update(run)
    repo.create(EvalRun(
        target_id=target.id, scenario_id=scenario.id,
        status=RunStatus.RUNNING, triggered_by=RunTrigger.MANUAL,
    ))


def test_dashboard_aggregates(client_with_db):
    client, session = client_with_db
    _seed(session)

    data = client.get("/api/stats/dashboard").json()
    assert data["targets_count"] == 1
    assert data["scenarios_count"] == 1
    assert data["runs_count"] == 3
    assert data["model_configs_count"] == 0
    assert data["running_count"] == 1
    assert data["today_runs"] == 3
    assert data["overall_pass_rate"] == pytest.approx(0.75)
    assert data["trigger_breakdown"] == {"manual": 2, "ai_assistant": 1}

    assert len(data["scenario_stats"]) == 1
    stat = data["scenario_stats"][0]
    assert stat["scenario_name"] == "场景A"
    assert stat["run_count"] == 2
    assert stat["avg_pass_rate"] == pytest.approx(0.75)
    assert stat["last_run_at"] is not None

    assert len(data["recent_runs"]) == 3
    assert data["recent_runs"][0]["scenario_name"] == "场景A"
    assert data["recent_runs"][0]["target_name"] == "对象A"
    assert "triggered_by" in data["recent_runs"][0]


def test_dashboard_empty_db(client_with_db):
    client, _ = client_with_db
    data = client.get("/api/stats/dashboard").json()
    assert data["runs_count"] == 0
    assert data["overall_pass_rate"] is None
    assert data["scenario_stats"] == []
    assert data["recent_runs"] == []


def test_trend_returns_daily_points(client_with_db):
    client, session = client_with_db
    _seed(session)
    points = client.get("/api/stats/trend").json()
    assert len(points) == 1
    assert points[0]["run_count"] == 2
    assert points[0]["pass_rate"] == pytest.approx(75.0)


def test_dashboard_follows_adr_0004(client_with_db):
    """故障 run 计 0.0 进分母；用户取消的 run 整体排除（ADR-0004）。"""
    client, session = client_with_db
    _seed(session)  # two completed runs: 1.0 and 0.5
    repo = RunRepository(session)
    target_id = repo.list_all()[0].target_id
    scenario_id = repo.list_all()[0].scenario_id

    faulted = repo.create(EvalRun(
        target_id=target_id, scenario_id=scenario_id, status=RunStatus.FAILED,
    ))
    faulted.summary = {"error": "channel exploded"}
    repo.update(faulted)

    cancelled = repo.create(EvalRun(
        target_id=target_id, scenario_id=scenario_id, status=RunStatus.FAILED,
    ))
    cancelled.summary = {"error": {"code": "cancelled_by_user", "message": "stop"}}
    repo.update(cancelled)

    data = client.get("/api/stats/dashboard").json()
    # (1.0 + 0.5 + 0.0[fault]) / 3 — cancelled run out of the denominator
    assert data["overall_pass_rate"] == pytest.approx(0.5)