mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
177b20263d
- Import and register two new nodes: LoraDemoNode and LoraRandomizerNode - Update import exception handling for better readability with multi-line formatting - Add comprehensive documentation file `docs/custom-node-ui-output.md` for UI output usage in custom nodes - Ensure proper node registration in NODE_CLASS_MAPPINGS for ComfyUI integration - Maintain backward compatibility with existing node structure and import fallbacks
96 lines
2.8 KiB
Python
96 lines
2.8 KiB
Python
"""
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Lora Demo Node - Demonstrates LORAS custom widget type usage.
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This node accepts LORAS widget input and outputs a summary string.
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"""
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import logging
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import random
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logger = logging.getLogger(__name__)
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class LoraDemoNode:
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"""Demo node that uses LORAS custom widget type."""
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NAME = "Lora Demo (LoraManager)"
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CATEGORY = "Lora Manager/demo"
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"loras": ("LORAS", {}),
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}
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("summary",)
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FUNCTION = "process"
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OUTPUT_NODE = False
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async def process(self, loras):
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"""
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Process LoRAs input and return summary + UI data for widget.
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Args:
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loras: List of LoRA dictionaries with structure:
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[{'name': str, 'strength': float, 'clipStrength': float, 'active': bool, ...}]
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Returns:
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Dictionary with 'result' (for workflow) and 'ui' (for frontend display)
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"""
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from ..services.service_registry import ServiceRegistry
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# Get lora scanner to access available loras
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scanner = await ServiceRegistry.get_lora_scanner()
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# Get available loras from cache
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available_loras = []
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try:
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cache_data = await scanner.get_cached_data(force_refresh=False)
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if cache_data and hasattr(cache_data, "raw_data"):
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available_loras = cache_data.raw_data
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except Exception as e:
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logger.warning(f"[LoraDemoNode] Failed to get lora cache: {e}")
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# Randomly select 3-5 loras
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num_to_select = random.randint(3, 5)
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if len(available_loras) < num_to_select:
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num_to_select = len(available_loras)
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selected_loras = (
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random.sample(available_loras, num_to_select) if num_to_select > 0 else []
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)
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# Generate random loras data for widget
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widget_loras = []
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for lora in selected_loras:
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strength = round(random.uniform(0.1, 1.0), 2)
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widget_loras.append(
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{
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"name": lora.get("file_name", "Unknown"),
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"strength": strength,
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"clipStrength": strength,
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"active": True,
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"expanded": False,
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}
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)
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# Create summary string
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active_names = [l["name"] for l in widget_loras]
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summary = f"Randomized {len(active_names)} LoRAs: {', '.join(active_names)}"
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logger.info(f"[LoraDemoNode] {summary}")
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# Return format: result for workflow + ui for frontend
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return {"result": (summary,), "ui": {"loras": widget_loras}}
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# Node class mappings for ComfyUI
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NODE_CLASS_MAPPINGS = {"LoraDemoNode": LoraDemoNode}
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# Display name mappings
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NODE_DISPLAY_NAME_MAPPINGS = {"LoraDemoNode": "LoRA Demo"}
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