"""Unit tests for VideoConfig parsing and LoRASpec validation.

Pure-python, no model imports, no CUDA, no ffmpeg. Safe for Windows CI.
"""
import pytest

from server.video import VideoConfig, LoRASpec


def test_defaults_when_raw_is_empty():
    cfg = VideoConfig.from_dict({})
    assert cfg.enabled is False
    assert cfg.backend == "lightx2v"
    assert cfg.mode == "reflective"
    assert cfg.resolution == 480
    assert cfg.fps == 16
    assert cfg.library_base_clip_count == 4
    assert cfg.reflective_prompt_reply_words == 18
    assert cfg.loras == []


def test_defaults_when_raw_is_none():
    cfg = VideoConfig.from_dict(None)  # type: ignore[arg-type]
    assert cfg.enabled is False


def test_library_section_override():
    cfg = VideoConfig.from_dict(
        {"enabled": True, "mode": "library", "library": {"base_clip_count": 7, "base_clip_seconds": 3}}
    )
    assert cfg.enabled is True
    assert cfg.mode == "library"
    assert cfg.library_base_clip_count == 7
    assert cfg.library_base_clip_seconds == 3


def test_reflective_section_override():
    cfg = VideoConfig.from_dict(
        {
            "reflective": {
                "clip_seconds": 9,
                "clip_prompt_template": "my template: {reply_hint}",
                "prompt_reply_words": 5,
            }
        }
    )
    assert cfg.reflective_clip_seconds == 9
    assert cfg.reflective_prompt_template == "my template: {reply_hint}"
    assert cfg.reflective_prompt_reply_words == 5


def test_lora_parse_minimal():
    cfg = VideoConfig.from_dict({"loras": [{"path": "/tmp/a.safetensors"}]})
    assert len(cfg.loras) == 1
    lora = cfg.loras[0]
    assert lora.path == "/tmp/a.safetensors"
    assert lora.weight == 1.0
    assert lora.target == "both"
    assert lora.name is None


def test_lora_parse_full():
    cfg = VideoConfig.from_dict(
        {
            "loras": [
                {
                    "path": "/tmp/a.safetensors",
                    "weight": 0.7,
                    "target": "both",
                    "name": "style-a",
                },
                {
                    "path": "/tmp/b.safetensors",
                    "weight": 0.4,
                    "target": "both",
                    "name": "style-b",
                },
            ]
        }
    )
    assert len(cfg.loras) == 2
    assert cfg.loras[0].target == "both"
    assert cfg.loras[0].name == "style-a"
    assert cfg.loras[1].target == "both"
    assert cfg.loras[1].weight == 0.4


def test_lora_legacy_moe_target_coerced_to_both():
    """Legacy MoE configs with target='high_noise'/'low_noise' get coerced."""
    cfg = VideoConfig.from_dict(
        {
            "loras": [
                {"path": "/tmp/hi.safetensors", "target": "high_noise"},
                {"path": "/tmp/lo.safetensors", "target": "low_noise"},
                {"path": "/tmp/x.safetensors", "target": "bogus"},
            ]
        }
    )
    assert all(l.target == "both" for l in cfg.loras)


def test_lora_entries_without_path_are_dropped():
    cfg = VideoConfig.from_dict(
        {"loras": [{"weight": 0.5}, {"path": "/tmp/ok.safetensors"}, None]}
    )
    assert len(cfg.loras) == 1
    assert cfg.loras[0].path == "/tmp/ok.safetensors"


def test_models_section_override():
    cfg = VideoConfig.from_dict(
        {
            "models": {
                "wan22_base_repo": "/local/weights/wan22",
                "wan22_dit_repo": "/local/weights/wan22-dit",
                "wan22_dit_quant_scheme": "gguf-Q4_K_M",
                "wan22_config_json": "/local/cfg/turbo.json",
                "wan22_model_cls": "wan2.2",
                "musetalk_path": "/local/weights/musetalk",
            }
        }
    )
    assert cfg.wan22_base_repo == "/local/weights/wan22"
    assert cfg.wan22_dit_repo == "/local/weights/wan22-dit"
    assert cfg.wan22_dit_quant_scheme == "gguf-Q4_K_M"
    assert cfg.wan22_config_json == "/local/cfg/turbo.json"
    assert cfg.wan22_model_cls == "wan2.2"
    assert cfg.musetalk_model_path == "/local/weights/musetalk"


def test_models_section_defaults_to_5b_turbo():
    cfg = VideoConfig.from_dict({})
    assert cfg.wan22_base_repo == "Wan-AI/Wan2.2-TI2V-5B"
    assert cfg.wan22_dit_repo == "hum-ma/Wan2.2-TI2V-5B-Turbo-GGUF"
    assert cfg.wan22_dit_quant_scheme == "gguf-Q8_0"
    assert cfg.wan22_t5_quantized is True
    assert cfg.wan22_model_cls == "wan2.2"
    assert cfg.wan22_config_json == "/app/configs/lightx2v/wan22_i2v_gguf_5b_turbo.json"