from __future__ import annotations

import pytest


def test_require_missing_raises():
    from argus.ray.models import _require

    with pytest.raises(ValueError, match="missing required field: x"):
        _require({}, "x")
    with pytest.raises(ValueError, match="missing required field: x"):
        _require({"x": ""}, "x")


def test_ray_config_from_dict_new_format_and_defaults():
    from argus.ray.models import RayConfig

    cfg = RayConfig.from_dict(
        {
            "ray": {
                "address": "http://127.0.0.1:8265",
                "shared_root": "/private",
                "entrypoint_resources": {"worker_node": 1},
                "runtime_env": {"env_vars": {"HF_ENDPOINT": "x"}},
            }
        }
    )
    assert cfg.address.endswith("8265")
    assert cfg.shared_root == "/private"
    assert cfg.entrypoint_num_cpus == 1.0
    assert cfg.entrypoint_resources["worker_node"] == 1.0
    assert cfg.runtime_env_env_vars["HF_ENDPOINT"] == "x"
    assert cfg.user_code_path == "/private/user/code"

    public = cfg.to_public_dict()
    assert public["runtime_env"]["env_vars"]["HF_ENDPOINT"] == "x"


def test_ray_config_from_dict_requires_mappings():
    from argus.ray.models import RayConfig

    with pytest.raises(ValueError, match="runtime_env\\.env_vars must be a mapping"):
        RayConfig.from_dict(
            {
                "address": "x",
                "shared_root": "/p",
                "entrypoint_resources": {},
                "runtime_env": {"env_vars": ["nope"]},
            }
        )
    with pytest.raises(ValueError, match="entrypoint_resources must be a mapping"):
        RayConfig.from_dict(
            {
                "address": "x",
                "shared_root": "/p",
                "entrypoint_resources": ["nope"],
            }
        )


def test_jobspec_validation_and_null_coercion():
    from argus.ray.models import JobSpec

    spec = JobSpec.from_dict(
        {
            "workload": "ppo",
            "code_path": "/code",
            "model_id": "m",
            "train_file": "train.jsonl",
            "val_file": "val.jsonl",
            "test_freq": "",
        }
    )
    assert spec.workload == "ppo"
    assert spec.val_file == "val.jsonl"
    assert spec.test_freq is None
    assert spec.total_training_steps is None
    assert spec.nnodes == 2
    assert spec.n_gpus_per_node == 4

    pub = spec.to_public_dict()
    assert pub["submission_id"] == ""
    assert "trainer_device" not in pub


def test_jobspec_sft_adds_trainer_device_default():
    from argus.ray.models import JobSpec

    spec = JobSpec.from_dict(
        {
            "workload": "sft",
            "code_path": "/code",
            "model_id": "m",
            "train_file": "train.jsonl",
            "val_file": "val.jsonl",
        }
    )
    pub = spec.to_public_dict()
    assert pub["trainer_device"] == "cpu"


def test_jobspec_unsupported_workload():
    from argus.ray.models import JobSpec

    with pytest.raises(ValueError, match="unsupported workload"):
        JobSpec.from_dict(
            {"workload": "nope", "code_path": "x", "model_id": "m", "train_file": "t", "val_file": "v"}
        )