mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-01-09 13:50:49 +08:00
98ae55b059
backends and other changes - remove uv.lock since it will not be used in most cases for installation - add cli args to prevent some custom nodes from installing packages at runtime - temp directories can now be shared between workers without being deleted - propcache yanked is now in the dependencies - fix configuration arguments loading in some tests
64 lines
2.8 KiB
Python
64 lines
2.8 KiB
Python
import importlib.resources
|
|
import json
|
|
import logging
|
|
from importlib.abc import Traversable
|
|
|
|
import pytest
|
|
|
|
from comfy.api.components.schema.prompt import Prompt
|
|
from comfy.client.embedded_comfy_client import Comfy
|
|
from comfy.model_downloader import add_known_models, KNOWN_LORAS
|
|
from comfy.model_downloader_types import CivitFile, HuggingFile
|
|
from comfy_extras.nodes.nodes_audio import TorchAudioNotFoundError
|
|
from . import workflows
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
@pytest.fixture(scope="function", autouse=False)
|
|
async def client(tmp_path_factory) -> Comfy:
|
|
async with Comfy() as client:
|
|
yield client
|
|
|
|
|
|
def _prepare_for_workflows() -> dict[str, Traversable]:
|
|
add_known_models("loras", KNOWN_LORAS, CivitFile(13941, 16576, "epi_noiseoffset2.safetensors"))
|
|
add_known_models("checkpoints", HuggingFile("autismanon/modeldump", "cardosAnime_v20.safetensors"))
|
|
|
|
return {f.name: f for f in importlib.resources.files(workflows).iterdir() if f.is_file() and f.name.endswith(".json")}
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
@pytest.mark.parametrize("workflow_name, workflow_file", _prepare_for_workflows().items())
|
|
async def test_workflow(workflow_name: str, workflow_file: Traversable, has_gpu: bool, client: Comfy):
|
|
if not has_gpu:
|
|
pytest.skip("requires gpu")
|
|
|
|
workflow = json.loads(workflow_file.read_text(encoding="utf8"))
|
|
|
|
prompt = Prompt.validate(workflow)
|
|
# todo: add all the models we want to test a bit m2ore elegantly
|
|
outputs = {}
|
|
try:
|
|
outputs = await client.queue_prompt(prompt)
|
|
except TorchAudioNotFoundError:
|
|
pytest.skip("requires torchaudio")
|
|
|
|
if any(v.class_type == "SaveImage" for v in prompt.values()):
|
|
save_image_node_id = next(key for key in prompt if prompt[key].class_type == "SaveImage")
|
|
assert outputs[save_image_node_id]["images"][0]["abs_path"] is not None
|
|
elif any(v.class_type == "SaveAudio" for v in prompt.values()):
|
|
save_audio_node_id = next(key for key in prompt if prompt[key].class_type == "SaveAudio")
|
|
assert outputs[save_audio_node_id]["audio"][0]["filename"] is not None
|
|
elif any(v.class_type == "SaveAnimatedWEBP" for v in prompt.values()):
|
|
save_video_node_id = next(key for key in prompt if prompt[key].class_type == "SaveAnimatedWEBP")
|
|
assert outputs[save_video_node_id]["images"][0]["filename"] is not None
|
|
elif any(v.class_type == "PreviewString" for v in prompt.values()):
|
|
save_image_node_id = next(key for key in prompt if prompt[key].class_type == "PreviewString")
|
|
output_str = outputs[save_image_node_id]["string"][0]
|
|
assert output_str is not None
|
|
assert len(output_str) > 0
|
|
else:
|
|
assert len(outputs) > 0
|
|
logger.warning(f"test {workflow_name} did not have a node that could be checked for output")
|