from pathlib import Path

from src.demo_service import DemoModelService


def test_demo_service_loads_local_dataset():
    service = DemoModelService(Path("data/demo_equipment_costs.csv"))

    summary = service.get_dataset_summary()

    assert summary["row_count"] >= 20
    assert "actual_cost" in summary["columns"]
    assert summary["target"] == "actual_cost"
    assert summary["preview"][0]["name"]
    assert summary["preview"][0]["type"] in {"巡飞弹", "火箭炮"}


def test_demo_service_returns_chinese_algorithm_names_with_english_notes():
    service = DemoModelService(Path("data/demo_equipment_costs.csv"))

    algorithms = service.get_algorithms()

    linear = next(item for item in algorithms if item["key"] == "linear")
    assert linear["name"] == "线性回归"
    assert linear["english_name"] == "Linear Regression"
    assert linear["family"] == "线性模型"


def test_demo_service_runs_multiple_algorithms():
    service = DemoModelService(Path("data/demo_equipment_costs.csv"))

    result = service.run_demo(["linear", "random_forest", "gradient_boosting"])

    assert result["source"] == "local-file"
    assert result["best_model"] in result["metrics"]
    assert len(result["metrics"]) == 3
    assert len(result["prediction_points"]) > 0
    assert len(result["sample_prediction"]["predictions"]) == 3
    for metrics in result["metrics"].values():
        assert {"r2", "mae", "rmse"}.issubset(metrics)


def test_demo_service_ignores_unavailable_algorithms():
    service = DemoModelService(Path("data/demo_equipment_costs.csv"))

    result = service.run_demo(["linear", "does_not_exist"])

    assert list(result["metrics"].keys()) == ["linear"]
    assert result["warnings"]