alphard/ComfyUI-Lora-Manager
1
0
Fork 0
mirror of https://github.com/willmiao/ComfyUI-Lora-Manager.git synced 2026-03-25 07:05:43 -03:00
Code Issues Packages Projects Releases Wiki Activity

Add support for SamplerCustomAdvanced node in metadata extraction

Browse Source
This commit is contained in:
Will Miao
2025-04-26 09:40:44 +08:00
parent b4e22cd375
commit b0a9d44b0c
2 changed files with 137 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files

77
py/metadata_collector/metadata_processor.py
View File

@@ -11,7 +11,16 @@ class MetadataProcessor:
primary_sampler = None
primary_sampler_id = None
# First, check for KSamplerAdvanced with add_noise="enable"
# First, check for SamplerCustomAdvanced
prompt = metadata.get("current_prompt")
if prompt and prompt.original_prompt:
for node_id, node_info in prompt.original_prompt.items():
if node_info.get("class_type") == "SamplerCustomAdvanced":
# Found a SamplerCustomAdvanced node
if node_id in metadata.get(SAMPLING, {}):
return node_id, metadata[SAMPLING][node_id]
# Next, check for KSamplerAdvanced with add_noise="enable"
for node_id, sampler_info in metadata.get(SAMPLING, {}).items():
parameters = sampler_info.get("parameters", {})
add_noise = parameters.get("add_noise")
@@ -22,7 +31,7 @@ class MetadataProcessor:
primary_sampler_id = node_id
break
# If no KSamplerAdvanced found, fall back to traditional KSampler with denoise=1
# If no specialized sampler found, fall back to traditional KSampler with denoise=1
if primary_sampler is None:
for node_id, sampler_info in metadata.get(SAMPLING, {}).items():
parameters = sampler_info.get("parameters", {})
@@ -152,22 +161,60 @@ class MetadataProcessor:
# Trace connections from the primary sampler
if prompt and primary_sampler_id:
# Trace positive prompt - look specifically for CLIPTextEncode
positive_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "CLIPTextEncode", max_depth=10)
if positive_node_id and positive_node_id in metadata.get(PROMPTS, {}):
params["prompt"] = metadata[PROMPTS][positive_node_id].get("text", "")
# Check if this is a SamplerCustomAdvanced node
is_custom_advanced = False
if prompt.original_prompt and primary_sampler_id in prompt.original_prompt:
is_custom_advanced = prompt.original_prompt[primary_sampler_id].get("class_type") == "SamplerCustomAdvanced"
# Find any FluxGuidance nodes in the positive conditioning path
flux_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "FluxGuidance", max_depth=5)
if flux_node_id and flux_node_id in metadata.get(SAMPLING, {}):
flux_params = metadata[SAMPLING][flux_node_id].get("parameters", {})
params["guidance"] = flux_params.get("guidance")
if is_custom_advanced:
# For SamplerCustomAdvanced, trace specific inputs
# 1. Trace sigmas input to find BasicScheduler
scheduler_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "sigmas", "BasicScheduler", max_depth=5)
if scheduler_node_id and scheduler_node_id in metadata.get(SAMPLING, {}):
scheduler_params = metadata[SAMPLING][scheduler_node_id].get("parameters", {})
params["steps"] = scheduler_params.get("steps")
params["scheduler"] = scheduler_params.get("scheduler")
# 2. Trace sampler input to find KSamplerSelect
sampler_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "sampler", "KSamplerSelect", max_depth=5)
if sampler_node_id and sampler_node_id in metadata.get(SAMPLING, {}):
sampler_params = metadata[SAMPLING][sampler_node_id].get("parameters", {})
params["sampler"] = sampler_params.get("sampler_name")
# 3. Trace guider input for FluxGuidance and CLIPTextEncode
guider_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "guider", max_depth=5)
if guider_node_id:
# Look for FluxGuidance along the guider path
flux_node_id = MetadataProcessor.trace_node_input(prompt, guider_node_id, "conditioning", "FluxGuidance", max_depth=5)
if flux_node_id and flux_node_id in metadata.get(SAMPLING, {}):
flux_params = metadata[SAMPLING][flux_node_id].get("parameters", {})
params["guidance"] = flux_params.get("guidance")
# Find CLIPTextEncode for positive prompt (through conditioning)
positive_node_id = MetadataProcessor.trace_node_input(prompt, guider_node_id, "conditioning", "CLIPTextEncode", max_depth=10)
if positive_node_id and positive_node_id in metadata.get(PROMPTS, {}):
params["prompt"] = metadata[PROMPTS][positive_node_id].get("text", "")
# Trace negative prompt - look specifically for CLIPTextEncode
negative_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "negative", "CLIPTextEncode", max_depth=10)
if negative_node_id and negative_node_id in metadata.get(PROMPTS, {}):
params["negative_prompt"] = metadata[PROMPTS][negative_node_id].get("text", "")
else:
# Original tracing for standard samplers
# Trace positive prompt - look specifically for CLIPTextEncode
positive_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "CLIPTextEncode", max_depth=10)
if positive_node_id and positive_node_id in metadata.get(PROMPTS, {}):
params["prompt"] = metadata[PROMPTS][positive_node_id].get("text", "")
# Find any FluxGuidance nodes in the positive conditioning path
flux_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "positive", "FluxGuidance", max_depth=5)
if flux_node_id and flux_node_id in metadata.get(SAMPLING, {}):
flux_params = metadata[SAMPLING][flux_node_id].get("parameters", {})
params["guidance"] = flux_params.get("guidance")
# Trace negative prompt - look specifically for CLIPTextEncode
negative_node_id = MetadataProcessor.trace_node_input(prompt, primary_sampler_id, "negative", "CLIPTextEncode", max_depth=10)
if negative_node_id and negative_node_id in metadata.get(PROMPTS, {}):
params["negative_prompt"] = metadata[PROMPTS][negative_node_id].get("text", "")
# Size extraction is same for all sampler types
# Check if the sampler itself has size information (from latent_image)
if primary_sampler_id in metadata.get(SIZE, {}):
width = metadata[SIZE][primary_sampler_id].get("width")