Files
live-voice-chat/tests/unit/test_video_config.py
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2026-04-16 10:00:37 -04:00

139 lines
4.4 KiB
Python

"""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"