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https://github.com/willmiao/ComfyUI-Lora-Manager.git
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feat(metadata): enhance primary sampler detection and workflow tracing
- Add support for `basic_pipe` nodes in metadata processor to handle pipeline nodes like FromBasicPipe - Optimize `find_primary_checkpoint` by accepting optional `primary_sampler_id` to avoid redundant calculations - Update `get_workflow_trace` to pass known primary sampler ID for improved efficiency
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98
tests/metadata_collector/test_pipe_tracer.py
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98
tests/metadata_collector/test_pipe_tracer.py
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import pytest
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from types import SimpleNamespace
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from py.metadata_collector.metadata_processor import MetadataProcessor
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from py.metadata_collector.constants import MODELS, SAMPLING, IS_SAMPLER
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class TestPipeTracer:
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@pytest.fixture
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def pipe_workflow_metadata(self):
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"""
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Creates a mock metadata structure matching the one provided in refs/tmp.
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Structure:
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Load Checkpoint(28) -> Lora Loader(52) -> ToBasicPipe(69) -> FromBasicPipe(71) -> KSampler(32)
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"""
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original_prompt = {
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'28': {
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'inputs': {'ckpt_name': 'Illustrious\\bananaSplitzXL_vee5PointOh.safetensors'},
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'class_type': 'CheckpointLoaderSimple'
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},
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'52': {
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'inputs': {
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'model': ['28', 0],
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'clip': ['28', 1]
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},
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'class_type': 'Lora Loader (LoraManager)'
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},
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'69': {
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'inputs': {
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'model': ['52', 0],
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'clip': ['52', 1],
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'vae': ['28', 2],
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'positive': ['75', 0],
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'negative': ['30', 0]
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},
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'class_type': 'ToBasicPipe'
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},
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'71': {
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'inputs': {'basic_pipe': ['69', 0]},
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'class_type': 'FromBasicPipe'
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},
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'32': {
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'inputs': {
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'seed': 131755205602911,
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'steps': 5,
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'cfg': 8.0,
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'sampler_name': 'euler_ancestral',
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'scheduler': 'karras',
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'denoise': 1.0,
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'model': ['71', 0],
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'positive': ['71', 3],
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'negative': ['71', 4],
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'latent_image': ['76', 0]
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},
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'class_type': 'KSampler'
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},
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'75': {'inputs': {'text': 'positive', 'clip': ['52', 1]}, 'class_type': 'CLIPTextEncode'},
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'30': {'inputs': {'text': 'negative', 'clip': ['52', 1]}, 'class_type': 'CLIPTextEncode'},
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'76': {'inputs': {'width': 832, 'height': 1216, 'batch_size': 1}, 'class_type': 'EmptyLatentImage'}
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}
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metadata = {
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"current_prompt": SimpleNamespace(original_prompt=original_prompt),
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MODELS: {
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"28": {
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"type": "checkpoint",
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"name": "bananaSplitzXL_vee5PointOh.safetensors"
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}
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},
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SAMPLING: {
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"32": {
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IS_SAMPLER: True,
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"parameters": {
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"sampler_name": "euler_ancestral",
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"scheduler": "karras"
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}
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}
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}
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}
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return metadata
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def test_trace_model_path_through_pipe(self, pipe_workflow_metadata):
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"""Verify trace_model_path can follow: KSampler -> FromBasicPipe -> ToBasicPipe -> Lora -> Checkpoint."""
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prompt = pipe_workflow_metadata["current_prompt"]
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# Start trace from KSampler (32)
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ckpt_id = MetadataProcessor.trace_model_path(pipe_workflow_metadata, prompt, "32")
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assert ckpt_id == "28"
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def test_find_primary_checkpoint_with_pipe(self, pipe_workflow_metadata):
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"""Verify find_primary_checkpoint returns the correct name even with pipe nodes."""
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# Providing sampler_id to test the optimization as well
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name = MetadataProcessor.find_primary_checkpoint(pipe_workflow_metadata, primary_sampler_id="32")
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assert name == "bananaSplitzXL_vee5PointOh.safetensors"
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