✨ (CivitMetadataHelper): introduce CivitAI metadata helper node to collect and format metadata for submissions
📝 (init.py): add import statements for CivitMetadataHelper node and handle import errors ♻️ (swiss-army-knife.js): update node registration to include CivitMetadataHelper and add metadata preview functionality ⬆️ (pyproject.toml): bump version to 2.5.8 to reflect new features and updates
This commit is contained in:
Sam Kumar
+12
-1
@@ -13,6 +13,15 @@ except ImportError as e:
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CONTROL_PANEL_NODE_CLASS_MAPPINGS = {}
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CONTROL_PANEL_NODE_DISPLAY_NAME_MAPPINGS = {}
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# Import civit metadata helper node
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try:
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from .nodes.utils.civit_metadata_helper import CIVIT_METADATA_HELPER_NODE_CLASS_MAPPINGS
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from .nodes.utils.civit_metadata_helper import CIVIT_METADATA_HELPER_NODE_DISPLAY_NAME_MAPPINGS
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except ImportError as e:
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print(f"Warning: Could not import civit metadata helper node: {e}")
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CIVIT_METADATA_HELPER_NODE_CLASS_MAPPINGS = {}
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CIVIT_METADATA_HELPER_NODE_DISPLAY_NAME_MAPPINGS = {}
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# Import lora_manager nodes
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try:
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from .nodes.lora_manager import NODE_CLASS_MAPPINGS as LORA_MANAGER_NODE_CLASS_MAPPINGS
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@@ -68,11 +77,12 @@ def get_version():
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import time
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return str(int(time.time()))
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# Combine main nodes, helper nodes, control panel, lora_manager, and media_selection nodes
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# Combine main nodes, helper nodes, control panel, civit metadata helper, lora_manager, and media_selection nodes
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NODE_CLASS_MAPPINGS = {
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**MAIN_NODE_CLASS_MAPPINGS,
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**HELPER_NODE_CLASS_MAPPINGS,
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**CONTROL_PANEL_NODE_CLASS_MAPPINGS,
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**CIVIT_METADATA_HELPER_NODE_CLASS_MAPPINGS,
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**LORA_MANAGER_NODE_CLASS_MAPPINGS,
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**MEDIA_SELECTION_NODE_CLASS_MAPPINGS
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}
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@@ -80,6 +90,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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**MAIN_NODE_DISPLAY_NAME_MAPPINGS,
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**HELPER_NODE_DISPLAY_NAME_MAPPINGS,
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**CONTROL_PANEL_NODE_DISPLAY_NAME_MAPPINGS,
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**CIVIT_METADATA_HELPER_NODE_DISPLAY_NAME_MAPPINGS,
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**LORA_MANAGER_NODE_DISPLAY_NAME_MAPPINGS,
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**MEDIA_SELECTION_NODE_DISPLAY_NAME_MAPPINGS
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}
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@@ -0,0 +1,254 @@
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"""
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CivitAI Metadata Helper Node - Collects and formats metadata for CivitAI submissions
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"""
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import json
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from typing import Dict, Any
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class CivitMetadataHelper:
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"""
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A helper node that collects common generation parameters used for CivitAI model submissions.
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This node aggregates sampling parameters and prompts into a structured format.
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"""
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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"""
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Define input fields for common CivitAI metadata parameters.
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"""
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return {
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"required": {
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"steps": ("INT", {
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"default": 20,
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"min": 1,
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"max": 200,
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"step": 1,
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"tooltip": "Number of sampling steps"
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}),
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"cfg": ("FLOAT", {
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"default": 7.0,
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"min": 0.0,
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"max": 30.0,
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"step": 0.1,
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"tooltip": "CFG Scale (Classifier Free Guidance)"
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}),
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"high_sampler": ("STRING", {
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"default": "euler",
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"tooltip": "High resolution sampler name"
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}),
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"low_sampler": ("STRING", {
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"default": "euler",
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"tooltip": "Low resolution sampler name"
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}),
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"lora_high": ("STRING", {
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"default": "",
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"tooltip": "High resolution LoRA model name"
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}),
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"lora_low": ("STRING", {
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"default": "",
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"tooltip": "Low resolution LoRA model name"
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}),
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"positive_prompt": ("STRING", {
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"default": "",
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"multiline": True,
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"tooltip": "Positive prompt text"
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}),
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"negative_prompt": ("STRING", {
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"default": "",
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"multiline": True,
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"tooltip": "Negative prompt text"
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})
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}
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}
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RETURN_TYPES = ("STRING", "STRING", "STRING")
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RETURN_NAMES = ("formatted_metadata", "json_metadata", "summary")
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FUNCTION = "collect_metadata"
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CATEGORY = "Swiss Army Knife 🔪/Utils"
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OUTPUT_NODE = True # Makes this an output node that displays in the UI
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def collect_metadata(self, steps, cfg, high_sampler, low_sampler, lora_high, lora_low, positive_prompt, negative_prompt):
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"""
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Collect and format metadata for CivitAI submissions.
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Args:
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steps: Number of sampling steps
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cfg: CFG scale value
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high_sampler: High resolution sampler name
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low_sampler: Low resolution sampler name
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lora_high: High resolution LoRA model name
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lora_low: Low resolution LoRA model name
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positive_prompt: Positive prompt text
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negative_prompt: Negative prompt text
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Returns:
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Tuple of (formatted_metadata, json_metadata, summary)
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"""
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# Create structured metadata
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metadata = {
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"generation_parameters": {
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"steps": steps,
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"cfg_scale": cfg,
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"samplers": {
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"high_res": high_sampler,
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"low_res": low_sampler
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},
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"loras": {
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"high_res": lora_high.strip(),
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"low_res": lora_low.strip()
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}
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},
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"prompts": {
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"positive": positive_prompt.strip(),
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"negative": negative_prompt.strip()
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},
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"prompt_lengths": {
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"positive_chars": len(positive_prompt.strip()),
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"negative_chars": len(negative_prompt.strip())
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}
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}
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# Create formatted text version for display
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formatted_metadata = self._format_for_display(metadata)
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# Create JSON version for data processing
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json_metadata = json.dumps(metadata, indent=2)
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# Create summary for quick reference
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lora_info = ""
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if lora_high.strip() or lora_low.strip():
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lora_info = f" | LoRAs: {lora_high.strip() or '(none)'}/{lora_low.strip() or '(none)'}"
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summary = (
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f"Steps: {steps} | CFG: {cfg} | "
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f"Samplers: {high_sampler}/{low_sampler}{lora_info} | "
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f"Pos: {len(positive_prompt.strip())} chars | "
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f"Neg: {len(negative_prompt.strip())} chars"
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)
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# Log summary to console
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print("\n" + "="*60)
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print("CIVITAI METADATA HELPER - Generation Parameters")
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print("="*60)
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print(f"📊 Steps: {steps}")
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print(f"📊 CFG Scale: {cfg}")
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print(f"📊 High Sampler: {high_sampler}")
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print(f"📊 Low Sampler: {low_sampler}")
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print(f"📊 High LoRA: {lora_high.strip() or '(none)'}")
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print(f"📊 Low LoRA: {lora_low.strip() or '(none)'}")
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print(f"📊 Positive Prompt ({len(positive_prompt.strip())} chars):")
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if positive_prompt.strip():
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print(f" {positive_prompt.strip()[:200]}...")
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else:
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print(" (empty)")
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print(f"📊 Negative Prompt ({len(negative_prompt.strip())} chars):")
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if negative_prompt.strip():
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print(f" {negative_prompt.strip()[:200]}...")
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else:
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print(" (empty)")
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print("="*60 + "\n")
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return (formatted_metadata, json_metadata, summary)
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def _format_for_display(self, metadata: Dict[str, Any]) -> str:
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"""
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Format metadata for human-readable display.
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Args:
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metadata: Structured metadata dictionary
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Returns:
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Formatted string for display
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"""
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lines = []
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# Header
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lines.append("=" * 50)
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lines.append("🎯 CIVITAI METADATA HELPER")
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lines.append("=" * 50)
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# Generation Parameters
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lines.append("\n📊 GENERATION PARAMETERS")
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lines.append("-" * 30)
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gen_params = metadata["generation_parameters"]
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lines.append(f"Steps: {gen_params['steps']}")
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lines.append(f"CFG Scale: {gen_params['cfg_scale']}")
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lines.append(f"High Sampler: {gen_params['samplers']['high_res']}")
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lines.append(f"Low Sampler: {gen_params['samplers']['low_res']}")
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lines.append(f"High LoRA: {gen_params['loras']['high_res'] or '(none)'}")
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lines.append(f"Low LoRA: {gen_params['loras']['low_res'] or '(none)'}")
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# Prompts
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lines.append("\n📝 PROMPTS")
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lines.append("-" * 30)
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prompts = metadata["prompts"]
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prompt_lengths = metadata["prompt_lengths"]
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lines.append(f"Positive ({prompt_lengths['positive_chars']} chars):")
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if prompts["positive"]:
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# Split long prompts into multiple lines
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pos_lines = self._wrap_text(prompts["positive"], 60)
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for line in pos_lines:
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lines.append(f" {line}")
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else:
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lines.append(" (empty)")
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lines.append(f"\nNegative ({prompt_lengths['negative_chars']} chars):")
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if prompts["negative"]:
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# Split long prompts into multiple lines
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neg_lines = self._wrap_text(prompts["negative"], 60)
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for line in neg_lines:
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lines.append(f" {line}")
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else:
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lines.append(" (empty)")
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lines.append("\n" + "=" * 50)
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return "\n".join(lines)
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def _wrap_text(self, text: str, width: int) -> list:
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"""
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Wrap text to specified width while preserving words.
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Args:
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text: Text to wrap
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width: Maximum line width
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Returns:
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List of wrapped lines
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"""
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words = text.split()
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lines = []
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current_line = []
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current_length = 0
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for word in words:
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if current_length + len(word) + 1 <= width:
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current_line.append(word)
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current_length += len(word) + 1
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else:
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if current_line:
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lines.append(" ".join(current_line))
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current_line = [word]
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current_length = len(word)
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if current_line:
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lines.append(" ".join(current_line))
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return lines
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# Export node class mapping
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CIVIT_METADATA_HELPER_NODE_CLASS_MAPPINGS = {
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"CivitMetadataHelper": CivitMetadataHelper
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}
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# Export display name mapping
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CIVIT_METADATA_HELPER_NODE_DISPLAY_NAME_MAPPINGS = {
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"CivitMetadataHelper": "🏷️ CivitAI Metadata Helper"
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}
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+1
-1
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
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[project]
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name = "ComfyUI-SwissArmyKnife"
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version = "2.5.7"
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version = "2.5.8"
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description = "A collection of custom nodes for ComfyUI"
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authors = [
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{name = "Sam Kumar", email = "sam@skproductions.llc"}
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@@ -1096,6 +1096,128 @@ app.registerExtension({
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return result;
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};
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}
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// Handle CivitMetadataHelper node
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else if (nodeData.name === "CivitMetadataHelper") {
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debugLog("Registering CivitMetadataHelper node");
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const onNodeCreated = nodeType.prototype.onNodeCreated;
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nodeType.prototype.onNodeCreated = function () {
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const result = onNodeCreated?.apply(this, arguments);
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// Add a formatted display widget for metadata preview
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this.addWidget(
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"text",
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"metadata_preview",
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"🏷️ Metadata preview will appear here...",
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(value) => {
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// Read-only preview widget
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},
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{
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multiline: true,
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serialize: false, // Don't store in workflow JSON
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}
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);
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// Function to update the metadata preview
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this.updateMetadataPreview = function () {
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try {
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// Get input values
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const steps = this.widgets.find((w) => w.name === "steps")?.value || 20;
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const cfg = this.widgets.find((w) => w.name === "cfg")?.value || 7.0;
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const highSampler =
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this.widgets.find((w) => w.name === "high_sampler")?.value || "";
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const lowSampler =
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this.widgets.find((w) => w.name === "low_sampler")?.value || "";
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const loraHigh =
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this.widgets.find((w) => w.name === "lora_high")?.value || "";
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const loraLow =
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this.widgets.find((w) => w.name === "lora_low")?.value || "";
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const positivePrompt =
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this.widgets.find((w) => w.name === "positive_prompt")?.value || "";
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const negativePrompt =
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this.widgets.find((w) => w.name === "negative_prompt")?.value || "";
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// Create preview text
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let preview = "🏷️ CIVITAI METADATA PREVIEW\n";
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preview += "========================================\n\n";
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preview += `📊 Steps: ${steps}\n`;
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preview += `📊 CFG Scale: ${cfg}\n`;
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preview += `📊 High Sampler: ${highSampler || "(not set)"}\n`;
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preview += `📊 Low Sampler: ${lowSampler || "(not set)"}\n`;
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preview += `📊 High LoRA: ${loraHigh || "(not set)"}\n`;
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preview += `📊 Low LoRA: ${loraLow || "(not set)"}\n\n`;
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preview += `📝 Positive Prompt (${positivePrompt.length} chars):\n`;
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preview += positivePrompt
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? `${positivePrompt.substring(0, 100)}${positivePrompt.length > 100 ? "..." : ""}\n\n`
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: "(empty)\n\n";
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preview += `📝 Negative Prompt (${negativePrompt.length} chars):\n`;
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preview += negativePrompt
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? `${negativePrompt.substring(0, 100)}${negativePrompt.length > 100 ? "..." : ""}`
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: "(empty)";
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// Update the preview widget
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const previewWidget = this.widgets.find(
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(w) => w.name === "metadata_preview"
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);
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if (previewWidget) {
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previewWidget.value = preview;
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}
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} catch (error) {
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debugLog("Error updating metadata preview:", error);
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}
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};
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// Set up listeners for input changes
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this.widgets.forEach((widget) => {
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if (
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[
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"steps",
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"cfg",
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"high_sampler",
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"low_sampler",
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"lora_high",
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"lora_low",
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"positive_prompt",
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"negative_prompt",
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].includes(widget.name)
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) {
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const originalCallback = widget.callback;
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widget.callback = (value) => {
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if (originalCallback) originalCallback(value);
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this.updateMetadataPreview();
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};
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}
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});
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// Initial preview update
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setTimeout(() => {
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this.updateMetadataPreview();
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}, 100);
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return result;
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};
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// Handle execution results to update the display
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const origOnExecuted = nodeType.prototype.onExecuted;
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nodeType.prototype.onExecuted = function (message) {
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debugLog("[CivitMetadataHelper] onExecuted called with:", message);
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if (origOnExecuted) {
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origOnExecuted.call(this, message);
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}
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// Update preview if we have new output
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if (message?.output) {
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// The first output is the formatted metadata
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const formattedMetadata = message.output[0];
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const previewWidget = this.widgets.find((w) => w.name === "metadata_preview");
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if (previewWidget && formattedMetadata) {
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previewWidget.value = formattedMetadata;
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}
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}
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};
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}
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},
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// Hook to handle workflow loading
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Reference in New Issue
Block a user