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https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-08-14 09:43:22 -03:00
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10 Commits
v1.1.7
..
7f51812c1e
| Author | SHA1 | Date | |
|---|---|---|---|
| 7f51812c1e | |||
| a9dc4d7b9d | |||
| 5d50ddb5d4 | |||
| f86198d234 | |||
| ffe65d983c | |||
| b0b5be913c | |||
| 01efcbc584 | |||
| 02c249917a | |||
| 419bbc90b2 | |||
| b0c4510fdb |
@@ -15,6 +15,8 @@ try: # pragma: no cover - import fallback for pytest collection
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from .py.nodes.lora_pool import LoraPoolLM
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from .py.nodes.lora_randomizer import LoraRandomizerLM
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from .py.nodes.lora_cycler import LoraCyclerLM
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from .py.nodes.lora_info import LoraInfoLM
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from .py.nodes.lora_syntax_to_path import LoraSyntaxToPath
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from .py.metadata_collector import init as init_metadata_collector
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except (
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ImportError
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@@ -56,6 +58,10 @@ except (
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"py.nodes.lora_randomizer"
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).LoraRandomizerLM
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LoraCyclerLM = importlib.import_module("py.nodes.lora_cycler").LoraCyclerLM
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LoraInfoLM = importlib.import_module("py.nodes.lora_info").LoraInfoLM
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LoraSyntaxToPath = importlib.import_module(
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"py.nodes.lora_syntax_to_path"
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).LoraSyntaxToPath
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init_metadata_collector = importlib.import_module("py.metadata_collector").init
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NODE_CLASS_MAPPINGS = {
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@@ -75,6 +81,8 @@ NODE_CLASS_MAPPINGS = {
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LoraPoolLM.NAME: LoraPoolLM,
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LoraRandomizerLM.NAME: LoraRandomizerLM,
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LoraCyclerLM.NAME: LoraCyclerLM,
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LoraInfoLM.NAME: LoraInfoLM,
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LoraSyntaxToPath.NAME: LoraSyntaxToPath,
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}
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WEB_DIRECTORY = "./web/comfyui"
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+6
-4
@@ -208,6 +208,12 @@ class Config:
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if not isinstance(library_config, dict):
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return
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# Always read recipes_path — it is independent of extra folder paths
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# and must be set before any early returns below.
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recipes_path = library_config.get("recipes_path", "")
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if isinstance(recipes_path, str) and recipes_path:
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self.recipes_path = recipes_path
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extra_folder_paths = library_config.get("extra_folder_paths")
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if not isinstance(extra_folder_paths, dict):
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return
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@@ -233,10 +239,6 @@ class Config:
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extra_embedding
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)
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recipes_path = library_config.get("recipes_path", "")
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if isinstance(recipes_path, str) and recipes_path:
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self.recipes_path = recipes_path
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if self.extra_loras_roots:
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logger.info(
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"Found extra LoRA roots:"
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@@ -0,0 +1,45 @@
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"""Lora Info display node — pure frontend node for showing selected LoRA info.
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This node does NOT participate in workflow execution. Its single optional
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"lora_source" input exists solely as a wire-connection anchor so that the
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frontend can traverse the graph and push selection data to connected info nodes.
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"""
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from __future__ import annotations
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class LoraInfoLM:
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"""Display node that shows filename and notes for the selected LoRA."""
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NAME = "Lora Info (LoraManager)"
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CATEGORY = "Lora Manager/utils"
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DESCRIPTION = (
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"Displays information (filename, notes) about the currently selected "
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"LoRA. Connect any output from a LoRA Loader or Stacker to the "
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"lora_source input, then select a LoRA in the source widget — the "
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"info updates automatically. Does not affect workflow execution."
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)
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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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}
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RETURN_TYPES = ()
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RETURN_NAMES = ()
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OUTPUT_NODE = False
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FUNCTION = "noop"
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def noop(self, **kwargs):
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# This node is display-only — no workflow execution needed.
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return ()
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NODE_CLASS_MAPPINGS = {
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LoraInfoLM.NAME: LoraInfoLM,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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LoraInfoLM.NAME: "Lora Info (LoraManager)",
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}
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+2
-17
@@ -1,6 +1,5 @@
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import importlib
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import logging
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import re
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import comfy.sd # type: ignore
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import comfy.utils # type: ignore
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@@ -14,6 +13,7 @@ from .utils import (
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extract_lora_name,
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get_loras_list,
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nunchaku_load_lora,
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parse_lora_syntax,
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)
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logger = logging.getLogger(__name__)
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@@ -189,25 +189,10 @@ class LoraTextLoaderLM:
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RETURN_NAMES = ("MODEL", "CLIP", "trigger_words", "loaded_loras")
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FUNCTION = "load_loras_from_text"
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def parse_lora_syntax(self, text):
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"""Parse LoRA syntax from text input."""
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pattern = r"<lora:([^:>]+):([^:>]+)(?::([^:>]+))?>"
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matches = re.findall(pattern, text, re.IGNORECASE)
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loras = []
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for match in matches:
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model_strength = float(match[1])
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loras.append({
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"name": match[0],
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"model_strength": model_strength,
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"clip_strength": float(match[2]) if match[2] else model_strength,
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})
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return loras
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def load_loras_from_text(self, model, lora_syntax, clip=None, lora_stack=None):
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"""Load LoRAs based on text syntax input."""
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lora_entries = _collect_stack_entries(lora_stack)
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for lora in self.parse_lora_syntax(lora_syntax):
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for lora in parse_lora_syntax(lora_syntax):
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lora_path, trigger_words = get_lora_info_absolute(lora["name"])
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lora_entries.append({
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"name": lora["name"],
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@@ -0,0 +1,62 @@
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"""Node to resolve `<lora:name:strength>` syntax to absolute file system paths.
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Takes the loaded_loras / active_loras STRING output from LoraLoaderLM or
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LoraStackerLM and resolves each lora name to its absolute path on disk via
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the scanner cache. Unknown names are returned as-is.
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"""
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import logging
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from ..utils.utils import get_lora_info_absolute
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from .utils import parse_lora_syntax
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logger = logging.getLogger(__name__)
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class LoraSyntaxToPath:
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NAME = "LoRA Syntax → Path (LoraManager)"
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CATEGORY = "Lora Manager/utils"
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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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"lora_syntax": (
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"STRING",
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{
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"forceInput": True,
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"multiline": True,
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"tooltip": (
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"<lora:name:strength> formatted text from "
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"loaded_loras / active_loras output"
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),
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},
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),
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},
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("paths",)
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FUNCTION = "resolve"
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def resolve(self, lora_syntax: str) -> tuple[str]:
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"""Parse <lora:...> syntax and resolve each name to its absolute path."""
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if not lora_syntax or not lora_syntax.strip():
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logger.info("Received empty lora_syntax input")
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return ("",)
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parsed = parse_lora_syntax(lora_syntax)
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if not parsed:
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logger.info("No valid <lora:...> entries found in input")
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return ("",)
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paths: list[str] = []
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for entry in parsed:
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try:
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absolute_path, _ = get_lora_info_absolute(entry["name"])
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paths.append(absolute_path)
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except Exception:
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logger.warning("Failed to resolve lora '%s', skipping", entry["name"])
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continue
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return ("\n".join(paths),)
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@@ -36,6 +36,7 @@ any_type = AnyType("*")
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# Common methods extracted from lora_loader.py and lora_stacker.py
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import os
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import re
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||||
import logging
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import copy
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import sys
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@@ -69,6 +70,25 @@ def extract_lora_name(lora_path):
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return apply_lora_syntax_format(name_no_ext)
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def parse_lora_syntax(text: str) -> list[dict]:
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"""Parse <lora:name:strength> syntax from text input into a list of dicts.
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Each entry contains: name, model_strength, clip_strength.
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Supports both ``<lora:name:strength>`` and ``<lora:name:model_strength:clip_strength>``.
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"""
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||||
pattern = r"<lora:([^:>]+):([^:>]+)(?::([^:>]+))?>"
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||||
matches = re.findall(pattern, text, re.IGNORECASE)
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||||
loras = []
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||||
for match in matches:
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||||
model_strength = float(match[1])
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||||
loras.append({
|
||||
"name": match[0],
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||||
"model_strength": model_strength,
|
||||
"clip_strength": float(match[2]) if match[2] else model_strength,
|
||||
})
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||||
return loras
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||||
|
||||
|
||||
def get_loras_list(kwargs):
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||||
"""Helper to extract loras list from either old or new kwargs format"""
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||||
if "loras" not in kwargs:
|
||||
|
||||
@@ -1784,6 +1784,124 @@ class LoraCodeHandler:
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logger.error("Failed to update lora code: %s", exc, exc_info=True)
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return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
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async def get_update_lora_code(self, request: web.Request) -> web.Response:
|
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"""GET version of update_lora_code — reads parameters from query string.
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||||
|
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Query params:
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||||
lora_code (required) — the LoRA syntax to send
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||||
mode (optional) — "append" (default) or "replace"
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||||
node_id (repeatable) — target node id(s), e.g. node_id=3&node_id=5
|
||||
node_ids (optional) — JSON-encoded array for complex references with graph_id:
|
||||
[{"node_id":3,"graph_id":"g1"}, ...]
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||||
"""
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||||
try:
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node_ids_raw = request.query.get("node_ids")
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node_id_list = request.query.getall("node_id", [])
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lora_code = request.query.get("lora_code", "")
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||||
mode = request.query.get("mode", "append")
|
||||
|
||||
if not lora_code:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Missing lora_code parameter"},
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||||
status=400,
|
||||
)
|
||||
|
||||
node_ids = None
|
||||
if node_ids_raw:
|
||||
try:
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||||
node_ids = json.loads(node_ids_raw)
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
return web.json_response(
|
||||
{"success": False, "error": "node_ids must be a valid JSON array"},
|
||||
status=400,
|
||||
)
|
||||
if not isinstance(node_ids, list) or not node_ids:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "node_ids must be a non-empty JSON array"},
|
||||
status=400,
|
||||
)
|
||||
elif node_id_list:
|
||||
node_ids = node_id_list
|
||||
|
||||
results = []
|
||||
if node_ids is None:
|
||||
try:
|
||||
self._prompt_server.instance.send_sync(
|
||||
"lora_code_update",
|
||||
{"id": -1, "lora_code": lora_code, "mode": mode},
|
||||
)
|
||||
results.append({"node_id": "broadcast", "success": True})
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
logger.error("Error broadcasting lora code: %s", exc)
|
||||
results.append(
|
||||
{"node_id": "broadcast", "success": False, "error": str(exc)}
|
||||
)
|
||||
else:
|
||||
for entry in node_ids:
|
||||
node_identifier = entry
|
||||
graph_identifier = None
|
||||
if isinstance(entry, dict):
|
||||
node_identifier = entry.get("node_id")
|
||||
graph_identifier = entry.get("graph_id")
|
||||
|
||||
if node_identifier is None:
|
||||
results.append(
|
||||
{
|
||||
"node_id": node_identifier,
|
||||
"graph_id": graph_identifier,
|
||||
"success": False,
|
||||
"error": "Missing node_id parameter",
|
||||
}
|
||||
)
|
||||
continue
|
||||
|
||||
try:
|
||||
parsed_node_id = int(node_identifier)
|
||||
except (TypeError, ValueError):
|
||||
parsed_node_id = node_identifier
|
||||
|
||||
payload = {
|
||||
"id": parsed_node_id,
|
||||
"lora_code": lora_code,
|
||||
"mode": mode,
|
||||
}
|
||||
|
||||
if graph_identifier is not None:
|
||||
payload["graph_id"] = str(graph_identifier)
|
||||
|
||||
try:
|
||||
self._prompt_server.instance.send_sync(
|
||||
"lora_code_update",
|
||||
payload,
|
||||
)
|
||||
results.append(
|
||||
{
|
||||
"node_id": parsed_node_id,
|
||||
"graph_id": payload.get("graph_id"),
|
||||
"success": True,
|
||||
}
|
||||
)
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
logger.error(
|
||||
"Error sending lora code to node %s (graph %s): %s",
|
||||
parsed_node_id,
|
||||
graph_identifier,
|
||||
exc,
|
||||
)
|
||||
results.append(
|
||||
{
|
||||
"node_id": parsed_node_id,
|
||||
"graph_id": payload.get("graph_id"),
|
||||
"success": False,
|
||||
"error": str(exc),
|
||||
}
|
||||
)
|
||||
|
||||
return web.json_response({"success": True, "results": results})
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
logger.error("Failed to update lora code (GET): %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
|
||||
class TrainedWordsHandler:
|
||||
async def get_trained_words(self, request: web.Request) -> web.Response:
|
||||
@@ -3431,6 +3549,130 @@ class NodeRegistryHandler:
|
||||
logger.error("Failed to update node widget: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_update_node_widget(self, request: web.Request) -> web.Response:
|
||||
"""GET version of update_node_widget — reads parameters from query string.
|
||||
|
||||
Query params:
|
||||
widget_name (optional) — the widget name to update (required unless action is set)
|
||||
action (optional) — alternative action, e.g. "inject_text" (required unless widget_name is set)
|
||||
value (required) — the value to set
|
||||
mode (optional) — "replace" (default) or "append"
|
||||
node_id (repeatable) — target node id(s), e.g. node_id=3&node_id=5
|
||||
node_ids (optional) — JSON-encoded array for complex references:
|
||||
[{"node_id":3,"graph_id":"g1"}, ...]
|
||||
"""
|
||||
try:
|
||||
widget_name = request.query.get("widget_name")
|
||||
action = request.query.get("action")
|
||||
value = request.query.get("value")
|
||||
mode = request.query.get("mode", "replace")
|
||||
node_ids_raw = request.query.get("node_ids")
|
||||
node_id_list = request.query.getall("node_id", [])
|
||||
|
||||
if not action and (not isinstance(widget_name, str) or not widget_name):
|
||||
return web.json_response(
|
||||
{
|
||||
"success": False,
|
||||
"error": "Missing parameter: provide either 'action' or 'widget_name'",
|
||||
},
|
||||
status=400,
|
||||
)
|
||||
|
||||
if not isinstance(value, str) or not value:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Missing value parameter"}, status=400
|
||||
)
|
||||
|
||||
node_ids = None
|
||||
if node_ids_raw:
|
||||
try:
|
||||
node_ids = json.loads(node_ids_raw)
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
return web.json_response(
|
||||
{"success": False, "error": "node_ids must be a valid JSON array"},
|
||||
status=400,
|
||||
)
|
||||
if not isinstance(node_ids, list) or not node_ids:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "node_ids must be a non-empty JSON array"},
|
||||
status=400,
|
||||
)
|
||||
elif node_id_list:
|
||||
node_ids = node_id_list
|
||||
|
||||
if not isinstance(node_ids, list) or not node_ids:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "node_ids must be a non-empty list"},
|
||||
status=400,
|
||||
)
|
||||
|
||||
results = []
|
||||
for entry in node_ids:
|
||||
node_identifier = entry
|
||||
graph_identifier = None
|
||||
if isinstance(entry, dict):
|
||||
node_identifier = entry.get("node_id")
|
||||
graph_identifier = entry.get("graph_id")
|
||||
|
||||
if node_identifier is None:
|
||||
results.append(
|
||||
{
|
||||
"node_id": node_identifier,
|
||||
"graph_id": graph_identifier,
|
||||
"success": False,
|
||||
"error": "Missing node_id parameter",
|
||||
}
|
||||
)
|
||||
continue
|
||||
|
||||
try:
|
||||
parsed_node_id = int(node_identifier)
|
||||
except (TypeError, ValueError):
|
||||
parsed_node_id = node_identifier
|
||||
|
||||
payload: dict = {
|
||||
"id": parsed_node_id,
|
||||
"value": value,
|
||||
"mode": mode,
|
||||
}
|
||||
if action:
|
||||
payload["action"] = action
|
||||
if widget_name:
|
||||
payload["widget_name"] = widget_name
|
||||
|
||||
if graph_identifier is not None:
|
||||
payload["graph_id"] = str(graph_identifier)
|
||||
|
||||
try:
|
||||
self._prompt_server.instance.send_sync("lm_widget_update", payload)
|
||||
results.append(
|
||||
{
|
||||
"node_id": parsed_node_id,
|
||||
"graph_id": payload.get("graph_id"),
|
||||
"success": True,
|
||||
}
|
||||
)
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
logger.error(
|
||||
"Error sending widget update to node %s (graph %s): %s",
|
||||
parsed_node_id,
|
||||
graph_identifier,
|
||||
exc,
|
||||
)
|
||||
results.append(
|
||||
{
|
||||
"node_id": parsed_node_id,
|
||||
"graph_id": payload.get("graph_id"),
|
||||
"success": False,
|
||||
"error": str(exc),
|
||||
}
|
||||
)
|
||||
|
||||
return web.json_response({"success": True, "results": results})
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
logger.error("Failed to update node widget (GET): %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
|
||||
class MiscHandlerSet:
|
||||
"""Aggregate handlers into a lookup compatible with the registrar."""
|
||||
@@ -3497,10 +3739,12 @@ class MiscHandlerSet:
|
||||
"update_usage_stats": self.usage_stats.update_usage_stats,
|
||||
"get_usage_stats": self.usage_stats.get_usage_stats,
|
||||
"update_lora_code": self.lora_code.update_lora_code,
|
||||
"get_update_lora_code": self.lora_code.get_update_lora_code,
|
||||
"get_trained_words": self.trained_words.get_trained_words,
|
||||
"get_model_example_files": self.model_examples.get_model_example_files,
|
||||
"register_nodes": self.node_registry.register_nodes,
|
||||
"update_node_widget": self.node_registry.update_node_widget,
|
||||
"get_update_node_widget": self.node_registry.get_update_node_widget,
|
||||
"get_registry": self.node_registry.get_registry,
|
||||
"check_model_exists": self.model_library.check_model_exists,
|
||||
"check_models_exist": self.model_library.check_models_exist,
|
||||
|
||||
@@ -1275,9 +1275,13 @@ class ModelQueryHandler:
|
||||
text=f"{self._service.model_type.capitalize()} file name is required",
|
||||
status=400,
|
||||
)
|
||||
notes = await self._service.get_model_notes(model_name)
|
||||
if notes is not None:
|
||||
return web.json_response({"success": True, "notes": notes})
|
||||
result = await self._service.get_model_notes(model_name)
|
||||
if result is not None:
|
||||
return web.json_response({
|
||||
"success": True,
|
||||
"notes": result["notes"],
|
||||
"file_path": result["file_path"],
|
||||
})
|
||||
return web.json_response(
|
||||
{
|
||||
"success": False,
|
||||
|
||||
@@ -39,10 +39,12 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition("POST", "/api/lm/update-usage-stats", "update_usage_stats"),
|
||||
RouteDefinition("GET", "/api/lm/get-usage-stats", "get_usage_stats"),
|
||||
RouteDefinition("POST", "/api/lm/update-lora-code", "update_lora_code"),
|
||||
RouteDefinition("GET", "/api/lm/update-lora-code", "get_update_lora_code"),
|
||||
RouteDefinition("GET", "/api/lm/trained-words", "get_trained_words"),
|
||||
RouteDefinition("GET", "/api/lm/model-example-files", "get_model_example_files"),
|
||||
RouteDefinition("POST", "/api/lm/register-nodes", "register_nodes"),
|
||||
RouteDefinition("POST", "/api/lm/update-node-widget", "update_node_widget"),
|
||||
RouteDefinition("GET", "/api/lm/update-node-widget", "get_update_node_widget"),
|
||||
RouteDefinition("GET", "/api/lm/get-registry", "get_registry"),
|
||||
RouteDefinition("GET", "/api/lm/check-model-exists", "check_model_exists"),
|
||||
RouteDefinition("GET", "/api/lm/check-models-exist", "check_models_exist"),
|
||||
|
||||
@@ -955,13 +955,21 @@ class BaseModelService(ABC):
|
||||
|
||||
return unified_tree
|
||||
|
||||
async def get_model_notes(self, model_name: str) -> Optional[str]:
|
||||
"""Get notes for a specific model file"""
|
||||
async def get_model_notes(self, model_name: str) -> Optional[dict]:
|
||||
"""Get notes and file_path for a specific model file.
|
||||
|
||||
Supports both simple names (``OWSMianne_ANIMA_V1``) and full-path
|
||||
syntax (``Anima/character/OWSMianne_ANIMA_V1``).
|
||||
"""
|
||||
cache = await self.scanner.get_cached_data()
|
||||
|
||||
for model in cache.raw_data:
|
||||
if model["file_name"] == model_name:
|
||||
return model.get("notes", "")
|
||||
file_name = model.get("file_name", "")
|
||||
if file_name == model_name or model_name.endswith("/" + file_name) or model_name.endswith("\\" + file_name):
|
||||
return {
|
||||
"notes": model.get("notes", ""),
|
||||
"file_path": model.get("file_path", ""),
|
||||
}
|
||||
|
||||
return None
|
||||
|
||||
|
||||
@@ -154,13 +154,23 @@ class DownloadQueueService:
|
||||
"""Insert a new download into the queue.
|
||||
|
||||
Returns the inserted row as a dict (or an empty dict if the
|
||||
download_id already exists).
|
||||
download_id already exists in the queue or has a terminal
|
||||
record in history).
|
||||
"""
|
||||
now = time.time()
|
||||
file_params_json = json.dumps(file_params) if file_params is not None else None
|
||||
|
||||
async with self._lock:
|
||||
conn = self._get_conn()
|
||||
|
||||
# Reject download_ids that already have a terminal record in history.
|
||||
history_row = conn.execute(
|
||||
"SELECT 1 FROM download_history WHERE download_id = ? LIMIT 1",
|
||||
(download_id,),
|
||||
).fetchone()
|
||||
if history_row is not None:
|
||||
return {}
|
||||
|
||||
conn.execute(
|
||||
"""
|
||||
INSERT OR IGNORE INTO download_queue (
|
||||
|
||||
@@ -271,12 +271,16 @@ class LoraService(BaseModelService):
|
||||
return letters
|
||||
|
||||
async def get_lora_trigger_words(self, lora_name: str) -> List[str]:
|
||||
"""Get trigger words for a specific LoRA file"""
|
||||
"""Get trigger words for a specific LoRA file.
|
||||
|
||||
Supports both simple names and full-path syntax.
|
||||
"""
|
||||
cache = await self.scanner.get_cached_data()
|
||||
|
||||
for lora in cache.raw_data:
|
||||
if lora["file_name"] == lora_name:
|
||||
civitai_data = lora.get("civitai", {})
|
||||
file_name = lora.get("file_name", "")
|
||||
if file_name == lora_name or lora_name.endswith("/" + file_name) or lora_name.endswith("\\" + file_name):
|
||||
civitai_data = lora.get("civitai") or {}
|
||||
return civitai_data.get("trainedWords", [])
|
||||
|
||||
return []
|
||||
|
||||
@@ -227,6 +227,11 @@ class ModelScanner:
|
||||
|
||||
entry: Dict[str, Any] = {
|
||||
'file_path': normalized_path,
|
||||
# file_name is always stored WITHOUT extension (e.g. "OWSMianne_ANIMA_V1",
|
||||
# not "OWSMianne_ANIMA_V1.safetensors"). All upstream population points
|
||||
# (MetadataManager, from_civitai_info, download manager, etc.) strip the
|
||||
# extension via os.path.splitext before writing. Code consuming this field
|
||||
# should match against names that are likewise extension-free.
|
||||
'file_name': get_value('file_name', '') or '',
|
||||
'model_name': get_value('model_name', '') or '',
|
||||
'folder': normalized_folder,
|
||||
|
||||
@@ -152,7 +152,9 @@ export class LoraContextMenu extends BaseContextMenu {
|
||||
sendLoraToWorkflow(replaceMode) {
|
||||
const card = this.currentCard;
|
||||
const usageTips = JSON.parse(card.dataset.usage_tips || '{}');
|
||||
const loraSyntax = buildLoraSyntax(card.dataset.file_name, usageTips);
|
||||
const folder = card.dataset.folder || '';
|
||||
const loraName = folder ? `${folder}/${card.dataset.file_name}` : card.dataset.file_name;
|
||||
const loraSyntax = buildLoraSyntax(loraName, usageTips);
|
||||
|
||||
sendLoraToWorkflow(loraSyntax, replaceMode, 'lora');
|
||||
}
|
||||
|
||||
@@ -397,6 +397,7 @@ export class BulkManager {
|
||||
const updated = {
|
||||
...existing,
|
||||
fileName: card.dataset.file_name ?? existing.fileName,
|
||||
folder: card.dataset.folder ?? existing.folder,
|
||||
usageTips: card.dataset.usage_tips ?? existing.usageTips,
|
||||
modelName: card.dataset.name ?? existing.modelName,
|
||||
};
|
||||
@@ -494,7 +495,8 @@ export class BulkManager {
|
||||
|
||||
if (metadata) {
|
||||
const usageTips = JSON.parse(metadata.usageTips || '{}');
|
||||
loraSyntaxes.push(buildLoraSyntax(metadata.fileName, usageTips));
|
||||
const loraName = metadata.folder ? `${metadata.folder}/${metadata.fileName}` : metadata.fileName;
|
||||
loraSyntaxes.push(buildLoraSyntax(loraName, usageTips));
|
||||
} else {
|
||||
missingLoras.push(filepath);
|
||||
}
|
||||
@@ -537,7 +539,8 @@ export class BulkManager {
|
||||
|
||||
if (metadata) {
|
||||
const usageTips = JSON.parse(metadata.usageTips || '{}');
|
||||
loraSyntaxes.push(buildLoraSyntax(metadata.fileName, usageTips));
|
||||
const loraName = metadata.folder ? `${metadata.folder}/${metadata.fileName}` : metadata.fileName;
|
||||
loraSyntaxes.push(buildLoraSyntax(loraName, usageTips));
|
||||
} else {
|
||||
missingLoras.push(filepath);
|
||||
}
|
||||
@@ -553,7 +556,8 @@ export class BulkManager {
|
||||
return;
|
||||
}
|
||||
|
||||
await sendLoraToWorkflow(loraSyntaxes.join(', '), replaceMode, 'lora');
|
||||
const exitBulkMode = () => { if (state.bulkMode) this.toggleBulkMode(); };
|
||||
await sendLoraToWorkflow(loraSyntaxes.join(', '), replaceMode, 'lora', exitBulkMode);
|
||||
}
|
||||
|
||||
async _sendAllEmbeddingsToWorkflow() {
|
||||
@@ -575,7 +579,8 @@ export class BulkManager {
|
||||
}
|
||||
|
||||
const joinedCode = embeddingCodes.join(', ');
|
||||
await sendEmbeddingToWorkflow(joinedCode);
|
||||
const exitBulkMode = () => { if (state.bulkMode) this.toggleBulkMode(); };
|
||||
await sendEmbeddingToWorkflow(joinedCode, exitBulkMode);
|
||||
}
|
||||
|
||||
showBulkDeleteModal() {
|
||||
@@ -674,6 +679,7 @@ export class BulkManager {
|
||||
const modelId = this.parseModelId(item?.civitai?.modelId);
|
||||
metadataCache.set(item.file_path, {
|
||||
fileName: item.file_name,
|
||||
folder: item.folder || '',
|
||||
usageTips: item.usage_tips || '{}',
|
||||
modelName: item.name || item.file_name,
|
||||
...(modelId !== null ? { modelId } : {})
|
||||
|
||||
@@ -656,7 +656,7 @@ async function ensureRelativeModelPath(modelPath, collectionType) {
|
||||
* @param {string} syntaxType - The type of syntax ('lora' or 'recipe')
|
||||
* @returns {Promise<boolean>} - Whether the operation was successful
|
||||
*/
|
||||
export async function sendLoraToWorkflow(loraSyntax, replaceMode = false, syntaxType = 'lora') {
|
||||
export async function sendLoraToWorkflow(loraSyntax, replaceMode = false, syntaxType = 'lora', onComplete = null) {
|
||||
const registry = await fetchWorkflowRegistry();
|
||||
if (!registry) {
|
||||
return false;
|
||||
@@ -681,7 +681,9 @@ export async function sendLoraToWorkflow(loraSyntax, replaceMode = false, syntax
|
||||
}
|
||||
|
||||
if (nodeKeys.length === 1) {
|
||||
return await sendLoraToNodes([nodeKeys[0]], loraNodes, loraSyntax, replaceMode, syntaxType);
|
||||
const result = await sendLoraToNodes([nodeKeys[0]], loraNodes, loraSyntax, replaceMode, syntaxType);
|
||||
if (result && typeof onComplete === 'function') onComplete();
|
||||
return result;
|
||||
}
|
||||
|
||||
const actionType =
|
||||
@@ -695,8 +697,11 @@ export async function sendLoraToWorkflow(loraSyntax, replaceMode = false, syntax
|
||||
showNodeSelector(loraNodes, {
|
||||
actionType,
|
||||
actionMode,
|
||||
onSend: (selectedNodeIds) =>
|
||||
sendLoraToNodes(selectedNodeIds, loraNodes, loraSyntax, replaceMode, syntaxType),
|
||||
onSend: async (selectedNodeIds) => {
|
||||
const result = await sendLoraToNodes(selectedNodeIds, loraNodes, loraSyntax, replaceMode, syntaxType);
|
||||
if (result && typeof onComplete === 'function') onComplete();
|
||||
return result;
|
||||
},
|
||||
});
|
||||
return true;
|
||||
}
|
||||
@@ -967,7 +972,7 @@ async function sendTextToNodes(nodeIds, nodesMap, text, mode, messages = {}) {
|
||||
}
|
||||
}
|
||||
|
||||
export async function sendEmbeddingToWorkflow(embeddingCode) {
|
||||
export async function sendEmbeddingToWorkflow(embeddingCode, onComplete = null) {
|
||||
const registry = await fetchWorkflowRegistry();
|
||||
if (!registry) {
|
||||
return false;
|
||||
@@ -995,8 +1000,11 @@ export async function sendEmbeddingToWorkflow(embeddingCode) {
|
||||
missingTargetMessage: translate('uiHelpers.workflow.noTargetNodeSelected', {}, 'No target node selected'),
|
||||
};
|
||||
|
||||
const handleSend = (selectedNodeIds) =>
|
||||
sendTextToNodes(selectedNodeIds, textNodes, embeddingCode, 'append', messages);
|
||||
const handleSend = async (selectedNodeIds) => {
|
||||
const result = await sendTextToNodes(selectedNodeIds, textNodes, embeddingCode, 'append', messages);
|
||||
if (result && typeof onComplete === 'function') onComplete();
|
||||
return result;
|
||||
};
|
||||
|
||||
if (nodeKeys.length === 1) {
|
||||
return await handleSend([nodeKeys[0]]);
|
||||
|
||||
@@ -0,0 +1,245 @@
|
||||
<template>
|
||||
<div class="lora-info-widget">
|
||||
<template v-if="loraName">
|
||||
<div class="info-field">
|
||||
<label class="info-label">Filename</label>
|
||||
<div class="lora-filename">{{ loraName }}</div>
|
||||
</div>
|
||||
<div class="info-field notes-field">
|
||||
<label class="info-label">Notes</label>
|
||||
<textarea
|
||||
v-model="notes"
|
||||
class="lora-notes"
|
||||
placeholder="Add notes about this LoRA..."
|
||||
:disabled="saving"
|
||||
></textarea>
|
||||
</div>
|
||||
<button
|
||||
class="save-btn"
|
||||
:disabled="notes === originalNotes || saving"
|
||||
@click="saveNotes"
|
||||
>
|
||||
{{ saving ? 'Saving...' : 'Save' }}
|
||||
</button>
|
||||
</template>
|
||||
<div v-else class="placeholder">No LoRA selected</div>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup lang="ts">
|
||||
import { onMounted, ref } from 'vue'
|
||||
|
||||
interface LoraInfoWidget {
|
||||
serializeValue?: () => Promise<unknown>
|
||||
value?: unknown
|
||||
onSetValue?: (v: unknown) => void
|
||||
callback?: unknown
|
||||
_setLoraInfo?: (data: { name: string; notes: string; filePath: string }) => void
|
||||
}
|
||||
|
||||
const props = defineProps<{
|
||||
widget: LoraInfoWidget
|
||||
node: { id: number }
|
||||
api: { fetchApi: (url: string, options?: RequestInit) => Promise<Response> }
|
||||
app: { extensionManager: { toast: { add: (opts: Record<string, unknown>) => void } } }
|
||||
}>()
|
||||
|
||||
const loraName = ref<string>('')
|
||||
const notes = ref<string>('')
|
||||
const originalNotes = ref<string>('')
|
||||
const filePath = ref<string>('')
|
||||
const saving = ref<boolean>(false)
|
||||
|
||||
async function saveNotes() {
|
||||
if (notes.value === originalNotes.value || saving.value) return
|
||||
if (!filePath.value) return
|
||||
|
||||
saving.value = true
|
||||
try {
|
||||
const response = await props.api.fetchApi('/lm/loras/save-metadata', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
body: JSON.stringify({ file_path: filePath.value, notes: notes.value })
|
||||
})
|
||||
const result = await response.json()
|
||||
if (result.success) {
|
||||
props.app.extensionManager.toast.add({
|
||||
severity: 'success',
|
||||
summary: 'Saved',
|
||||
detail: 'Notes updated successfully',
|
||||
life: 2000
|
||||
})
|
||||
originalNotes.value = notes.value
|
||||
} else {
|
||||
props.app.extensionManager.toast.add({
|
||||
severity: 'error',
|
||||
summary: 'Error',
|
||||
detail: result.message || result.error || 'Failed to save notes',
|
||||
life: 3000
|
||||
})
|
||||
}
|
||||
} catch (e) {
|
||||
console.error('[LoraInfoWidget] Failed to save notes:', e)
|
||||
props.app.extensionManager.toast.add({
|
||||
severity: 'error',
|
||||
summary: 'Error',
|
||||
detail: (e as Error).message || 'Failed to save notes',
|
||||
life: 3000
|
||||
})
|
||||
} finally {
|
||||
saving.value = false
|
||||
}
|
||||
}
|
||||
|
||||
onMounted(() => {
|
||||
// Display-only widget - return null on serialization to avoid saving to workflow
|
||||
props.widget.serializeValue = async () => null
|
||||
|
||||
// Handle external value updates (e.g., loading workflow, paste)
|
||||
props.widget.onSetValue = (v: unknown) => {
|
||||
if (v && typeof v === 'object') {
|
||||
const data = v as { name?: string; notes?: string; filePath?: string }
|
||||
if (data.name !== undefined) loraName.value = data.name
|
||||
if (data.notes !== undefined) {
|
||||
notes.value = data.notes
|
||||
originalNotes.value = data.notes
|
||||
}
|
||||
if (data.filePath !== undefined) filePath.value = data.filePath
|
||||
}
|
||||
}
|
||||
|
||||
// Restore from saved value if exists (for workflow loading)
|
||||
if (props.widget.value && typeof props.widget.value === 'object') {
|
||||
const data = props.widget.value as { name?: string; notes?: string; filePath?: string }
|
||||
if (data.name !== undefined) loraName.value = data.name
|
||||
if (data.notes !== undefined) {
|
||||
notes.value = data.notes
|
||||
originalNotes.value = data.notes
|
||||
}
|
||||
if (data.filePath !== undefined) filePath.value = data.filePath
|
||||
}
|
||||
|
||||
// Expose setLoraInfo on the widget object for external callers (e.g., lora_info.js).
|
||||
// Accepts null to clear the display (when selection is deselected).
|
||||
props.widget._setLoraInfo = (data: { name: string; notes: string; filePath: string } | null) => {
|
||||
if (data) {
|
||||
loraName.value = data.name
|
||||
notes.value = data.notes
|
||||
originalNotes.value = data.notes
|
||||
filePath.value = data.filePath
|
||||
} else {
|
||||
loraName.value = ''
|
||||
notes.value = ''
|
||||
originalNotes.value = ''
|
||||
filePath.value = ''
|
||||
}
|
||||
}
|
||||
|
||||
// Consume any data pushed before the Vue component mounted (race condition fix)
|
||||
if (props.widget.__pendingLoraInfo) {
|
||||
props.widget._setLoraInfo(props.widget.__pendingLoraInfo)
|
||||
delete props.widget.__pendingLoraInfo
|
||||
}
|
||||
})
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.lora-info-widget {
|
||||
padding: 12px;
|
||||
background: rgba(40, 44, 52, 0.6);
|
||||
border-radius: 4px;
|
||||
height: 100%;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
box-sizing: border-box;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.info-field {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 4px;
|
||||
}
|
||||
|
||||
.info-label {
|
||||
font-size: 10px;
|
||||
font-weight: 600;
|
||||
text-transform: uppercase;
|
||||
letter-spacing: 0.05em;
|
||||
color: var(--fg-color, #fff);
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.lora-filename {
|
||||
font-size: 13px;
|
||||
font-weight: 500;
|
||||
color: var(--fg-color, #fff);
|
||||
word-break: break-all;
|
||||
margin-bottom: 8px;
|
||||
}
|
||||
|
||||
.notes-field {
|
||||
flex: 1;
|
||||
min-height: 0;
|
||||
}
|
||||
|
||||
.lora-notes {
|
||||
width: 100%;
|
||||
flex: 1;
|
||||
min-height: 60px;
|
||||
padding: 8px;
|
||||
border-radius: 4px;
|
||||
border: 1px solid var(--border-color, #444);
|
||||
background: var(--comfy-input-bg, #333);
|
||||
color: var(--fg-color, #fff);
|
||||
font-size: 12px;
|
||||
resize: none;
|
||||
box-sizing: border-box;
|
||||
font-family: inherit;
|
||||
outline: none;
|
||||
}
|
||||
|
||||
.lora-notes:focus {
|
||||
border-color: var(--comfy-input-border, #444);
|
||||
}
|
||||
|
||||
.lora-notes:disabled {
|
||||
opacity: 0.6;
|
||||
cursor: not-allowed;
|
||||
}
|
||||
|
||||
.save-btn {
|
||||
width: 100%;
|
||||
margin-top: 8px;
|
||||
padding: 6px 12px;
|
||||
border-radius: 4px;
|
||||
border: 1px solid rgba(66, 153, 225, 0.4);
|
||||
background: rgba(66, 153, 225, 0.15);
|
||||
color: var(--fg-color, #fff);
|
||||
font-size: 12px;
|
||||
cursor: pointer;
|
||||
transition: all 0.2s;
|
||||
box-sizing: border-box;
|
||||
flex-shrink: 0;
|
||||
}
|
||||
|
||||
.save-btn:hover:not(:disabled) {
|
||||
background: rgba(66, 153, 225, 0.25);
|
||||
border-color: rgba(66, 153, 225, 0.6);
|
||||
}
|
||||
|
||||
.save-btn:disabled {
|
||||
opacity: 0.4;
|
||||
cursor: not-allowed;
|
||||
background: rgba(66, 153, 225, 0.05);
|
||||
border-color: rgba(226, 232, 240, 0.1);
|
||||
}
|
||||
|
||||
.placeholder {
|
||||
font-style: italic;
|
||||
color: rgba(226, 232, 240, 0.5);
|
||||
text-align: center;
|
||||
padding: 16px 0;
|
||||
font-size: 12px;
|
||||
}
|
||||
</style>
|
||||
+184
-23
@@ -5,6 +5,7 @@ import LoraRandomizerWidget from '@/components/LoraRandomizerWidget.vue'
|
||||
import LoraCyclerWidget from '@/components/LoraCyclerWidget.vue'
|
||||
import JsonDisplayWidget from '@/components/JsonDisplayWidget.vue'
|
||||
import AutocompleteTextWidget from '@/components/AutocompleteTextWidget.vue'
|
||||
import LoraInfoWidget from '@/components/LoraInfoWidget.vue'
|
||||
import { createVueWidgetCleanup } from './vue-widget-cleanup'
|
||||
import type { LoraPoolConfig, RandomizerConfig, CyclerConfig } from './composables/types'
|
||||
import {
|
||||
@@ -23,6 +24,8 @@ const LORA_CYCLER_WIDGET_MIN_HEIGHT = 408
|
||||
const LORA_CYCLER_WIDGET_MAX_HEIGHT = LORA_CYCLER_WIDGET_MIN_HEIGHT
|
||||
const JSON_DISPLAY_WIDGET_MIN_WIDTH = 300
|
||||
const JSON_DISPLAY_WIDGET_MIN_HEIGHT = 200
|
||||
const LORA_INFO_WIDGET_MIN_WIDTH = 300
|
||||
const LORA_INFO_WIDGET_MIN_HEIGHT = 200
|
||||
const AUTOCOMPLETE_TEXT_WIDGET_MIN_HEIGHT = 60
|
||||
const AUTOCOMPLETE_TEXT_WIDGET_MAX_HEIGHT = 100
|
||||
// Per-modelType min size hints for node initial sizing.
|
||||
@@ -71,7 +74,7 @@ function forwardMiddleMouseToCanvas(container: HTMLElement) {
|
||||
})
|
||||
}
|
||||
|
||||
const vueApps = new Map<number, VueApp>()
|
||||
const vueApps = new Map<number | string, VueApp>()
|
||||
let autocompleteTextWidgetInstanceId = 0
|
||||
|
||||
export function createAutocompleteTextWidgetInstanceId() {
|
||||
@@ -402,7 +405,6 @@ function createJsonDisplayWidget(node) {
|
||||
return { widget }
|
||||
}
|
||||
|
||||
// Store nodeData options per widget type for autocomplete widgets
|
||||
const widgetInputOptions: Map<string, { placeholder?: string }> = new Map()
|
||||
|
||||
function getSerializableWidgetNames(node: any): string[] {
|
||||
@@ -642,6 +644,74 @@ if (app.ui?.settings) {
|
||||
}, 100)
|
||||
}
|
||||
|
||||
// @ts-ignore
|
||||
function createLoraInfoWidget(node: any) {
|
||||
const container = document.createElement('div')
|
||||
container.id = `lora-info-widget-${node.id}`
|
||||
container.style.width = '100%'
|
||||
container.style.height = '100%'
|
||||
container.style.display = 'flex'
|
||||
container.style.flexDirection = 'column'
|
||||
container.style.overflow = 'hidden'
|
||||
|
||||
forwardMiddleMouseToCanvas(container)
|
||||
|
||||
let internalValue: { name?: string; notes?: string; filePath?: string } | undefined
|
||||
|
||||
const widget = node.addDOMWidget(
|
||||
'lora_info_display',
|
||||
'LORA_INFO_DISPLAY',
|
||||
container,
|
||||
{
|
||||
getValue() {
|
||||
return internalValue
|
||||
},
|
||||
setValue(v: { name?: string; notes?: string; filePath?: string }) {
|
||||
internalValue = v
|
||||
if (typeof widget.onSetValue === 'function') {
|
||||
widget.onSetValue(v)
|
||||
}
|
||||
},
|
||||
serialize: false, // Display-only widget
|
||||
getMinHeight() {
|
||||
return LORA_INFO_WIDGET_MIN_HEIGHT
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
const vueApp = createApp(LoraInfoWidget, {
|
||||
widget,
|
||||
node,
|
||||
api,
|
||||
app,
|
||||
})
|
||||
|
||||
vueApp.use(PrimeVue, {
|
||||
unstyled: true,
|
||||
ripple: false
|
||||
})
|
||||
|
||||
vueApp.mount(container)
|
||||
vueApps.set(node.id + 40000, vueApp) // Offset to avoid collision
|
||||
|
||||
widget.computeLayoutSize = () => {
|
||||
const minWidth = LORA_INFO_WIDGET_MIN_WIDTH
|
||||
const minHeight = LORA_INFO_WIDGET_MIN_HEIGHT
|
||||
|
||||
return { minHeight, minWidth }
|
||||
}
|
||||
|
||||
widget.onRemove = () => {
|
||||
const vueApp = vueApps.get(node.id + 40000)
|
||||
if (vueApp) {
|
||||
vueApp.unmount()
|
||||
vueApps.delete(node.id + 40000)
|
||||
}
|
||||
}
|
||||
|
||||
return { widget }
|
||||
}
|
||||
|
||||
// Factory function for creating autocomplete text widgets
|
||||
// @ts-ignore
|
||||
function createAutocompleteTextWidgetFactory(
|
||||
@@ -651,16 +721,30 @@ function createAutocompleteTextWidgetFactory(
|
||||
inputOptions: { placeholder?: string } = {}
|
||||
) {
|
||||
const metadataWidgetName = `__lm_autocomplete_meta_${widgetName}`
|
||||
const instanceId = createAutocompleteTextWidgetInstanceId()
|
||||
const container = document.createElement('div')
|
||||
container.id = `autocomplete-text-widget-${instanceId}`
|
||||
container.style.width = '100%'
|
||||
container.style.height = '100%'
|
||||
container.style.display = 'flex'
|
||||
container.style.flexDirection = 'column'
|
||||
container.style.overflow = 'hidden'
|
||||
|
||||
forwardMiddleMouseToCanvas(container)
|
||||
let container: HTMLElement | null = null
|
||||
|
||||
const existingContainers = document.querySelectorAll<HTMLElement>(
|
||||
'[id^="autocomplete-text-widget-"]'
|
||||
)
|
||||
for (const el of existingContainers) {
|
||||
if (el.children.length === 0) {
|
||||
container = el
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
if (!container) {
|
||||
const instanceId = String(createAutocompleteTextWidgetInstanceId())
|
||||
container = document.createElement('div')
|
||||
container.id = `autocomplete-text-widget-${instanceId}`
|
||||
container.style.width = '100%'
|
||||
container.style.height = '100%'
|
||||
container.style.display = 'flex'
|
||||
container.style.flexDirection = 'column'
|
||||
container.style.overflow = 'hidden'
|
||||
forwardMiddleMouseToCanvas(container)
|
||||
}
|
||||
|
||||
// Store textarea reference on the container element so cloned widgets can access it
|
||||
// This is necessary because when widgets are promoted to subgraph nodes,
|
||||
@@ -739,15 +823,10 @@ function createAutocompleteTextWidgetFactory(
|
||||
})
|
||||
|
||||
vueApp.mount(container)
|
||||
const appKey = instanceId
|
||||
const appKey = container.id
|
||||
vueApps.set(appKey, vueApp)
|
||||
|
||||
if (maxHeight) {
|
||||
// Set only minHeight as a true minimum — remove maxHeight so the
|
||||
// textarea can grow when the user resizes it in app mode (where
|
||||
// [&_textarea]:resize-y applies). Graph mode (canvas & Vue render)
|
||||
// is unaffected because LiteGraph's layout system still governs
|
||||
// the widget area size.
|
||||
container.style.minHeight = `${AUTOCOMPLETE_TEXT_WIDGET_MIN_HEIGHT}px`
|
||||
}
|
||||
|
||||
@@ -759,10 +838,14 @@ function createAutocompleteTextWidgetFactory(
|
||||
)
|
||||
}
|
||||
|
||||
widget.onRemove = createVueWidgetCleanup(vueApp, () => {
|
||||
const vueCleanup = createVueWidgetCleanup(vueApp, () => {
|
||||
vueApps.delete(appKey)
|
||||
})
|
||||
|
||||
widget.onRemove = () => {
|
||||
vueCleanup()
|
||||
}
|
||||
|
||||
// Return minWidth/minHeight hints so ComfyUI's _initialMinSize mechanism
|
||||
// sets a sensible initial node width (and height for prompt/embeddings).
|
||||
// loras modelType retains its existing height constraints (getMaxHeight: 100).
|
||||
@@ -804,7 +887,75 @@ app.registerExtension({
|
||||
updateDownstreamLoaders(node)
|
||||
} : null
|
||||
|
||||
return addLorasWidgetCache(node, 'loras', { isRandomizerNode }, callback)
|
||||
const opts: { isRandomizerNode?: boolean; onSelectionChange?: (selection: any) => void } = {
|
||||
isRandomizerNode,
|
||||
}
|
||||
if (isRandomizerNode) {
|
||||
opts.onSelectionChange = async (selection: any) => {
|
||||
if (!selection?.name || !selection?.active) return
|
||||
|
||||
// Walk outputs to find directly connected Lora Info nodes
|
||||
const infoNodes: any[] = []
|
||||
if (node.outputs) {
|
||||
for (const output of node.outputs) {
|
||||
if (!output?.links?.length) continue
|
||||
for (const linkId of output.links) {
|
||||
const links = node.graph?.links
|
||||
if (!links) continue
|
||||
const link = Array.isArray(links) ? links[linkId] : links.get?.(linkId)
|
||||
if (!link) continue
|
||||
const targetNode = node.graph?.getNodeById?.(link.target_id)
|
||||
if (targetNode?.comfyClass === 'Lora Info (LoraManager)') {
|
||||
infoNodes.push(targetNode)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (infoNodes.length === 0) return
|
||||
|
||||
// Bump request token to guard against stale async responses
|
||||
for (const infoNode of infoNodes) {
|
||||
infoNode.__loraInfoReqId = (infoNode.__loraInfoReqId || 0) + 1
|
||||
}
|
||||
const reqIdSnapshot = new Map<any, number>()
|
||||
for (const infoNode of infoNodes) {
|
||||
reqIdSnapshot.set(infoNode, infoNode.__loraInfoReqId)
|
||||
}
|
||||
|
||||
// Fetch notes via the real ComfyUI api
|
||||
let infoData: any
|
||||
try {
|
||||
const response = await api.fetchApi(
|
||||
`/lm/loras/get-notes?name=${encodeURIComponent(selection.name)}`,
|
||||
{ method: 'GET' }
|
||||
)
|
||||
if (response?.ok) {
|
||||
const data = await response.json()
|
||||
infoData = {
|
||||
name: selection.name,
|
||||
notes: data?.notes || '',
|
||||
filePath: data?.file_path || '',
|
||||
}
|
||||
} else {
|
||||
infoData = { name: selection.name, notes: '[Error loading notes]', filePath: '' }
|
||||
}
|
||||
} catch {
|
||||
infoData = { name: selection.name, notes: '[Error loading notes]', filePath: '' }
|
||||
}
|
||||
|
||||
for (const infoNode of infoNodes) {
|
||||
if (infoNode.__loraInfoReqId !== reqIdSnapshot.get(infoNode)) {
|
||||
continue
|
||||
}
|
||||
if (typeof infoNode._setLoraInfo === 'function') {
|
||||
infoNode._setLoraInfo(infoData)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return addLorasWidgetCache(node, 'loras', opts, callback)
|
||||
},
|
||||
// Autocomplete text widget for LoRAs (used by Lora Loader, Lora Stacker, WanVideo Lora Select)
|
||||
// @ts-ignore
|
||||
@@ -823,7 +974,7 @@ app.registerExtension({
|
||||
AUTOCOMPLETE_TEXT_PROMPT(node) {
|
||||
const options = widgetInputOptions.get(`${node.comfyClass}:text`) || {}
|
||||
return createAutocompleteTextWidgetFactory(node, 'text', 'prompt', options)
|
||||
}
|
||||
},
|
||||
}
|
||||
},
|
||||
|
||||
@@ -868,9 +1019,7 @@ app.registerExtension({
|
||||
info.widgets_values = [...(info.widgets_values ?? []), null]
|
||||
}
|
||||
|
||||
const result = originalConfigure?.apply(this, arguments)
|
||||
|
||||
return result
|
||||
return originalConfigure?.apply(this, arguments)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -903,5 +1052,17 @@ app.registerExtension({
|
||||
createJsonDisplayWidget(this)
|
||||
}
|
||||
}
|
||||
|
||||
// Add the Lora Info display widget
|
||||
if (nodeData.name === 'Lora Info (LoraManager)') {
|
||||
const onNodeCreated = nodeType.prototype.onNodeCreated
|
||||
|
||||
nodeType.prototype.onNodeCreated = function () {
|
||||
onNodeCreated?.apply(this, [])
|
||||
|
||||
// Create the lora info display widget
|
||||
createLoraInfoWidget(this)
|
||||
}
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
@@ -0,0 +1,182 @@
|
||||
import { app } from "../../scripts/app.js";
|
||||
import { api } from "../../scripts/api.js";
|
||||
import {
|
||||
getLinkFromGraph,
|
||||
chainCallback,
|
||||
} from "./utils.js";
|
||||
|
||||
const LORA_INFO_CLASS = "Lora Info (LoraManager)";
|
||||
|
||||
/**
|
||||
* Find Lora Info nodes directly connected to the given node's outputs.
|
||||
* Mirrors the getConnectedTriggerToggleNodes pattern from utils.js.
|
||||
* @param {object} node - The source node to check outputs from
|
||||
* @returns {object[]} Array of connected Lora Info node instances
|
||||
*/
|
||||
export function getConnectedLoraInfoNodes(node) {
|
||||
const connectedNodes = [];
|
||||
|
||||
if (!node?.outputs) {
|
||||
return connectedNodes;
|
||||
}
|
||||
|
||||
for (const output of node.outputs) {
|
||||
if (!output?.links?.length) {
|
||||
continue;
|
||||
}
|
||||
|
||||
for (const linkId of output.links) {
|
||||
const link = getLinkFromGraph(node.graph, linkId);
|
||||
if (!link) {
|
||||
continue;
|
||||
}
|
||||
|
||||
const targetNode = node.graph?.getNodeById?.(link.target_id);
|
||||
if (targetNode && targetNode.comfyClass === LORA_INFO_CLASS) {
|
||||
connectedNodes.push(targetNode);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return connectedNodes;
|
||||
}
|
||||
|
||||
/**
|
||||
* Fetch notes for the selected lora and push them to all directly connected
|
||||
* Lora Info nodes (no recursive chain traversal — only direct connections).
|
||||
* @param {object} node - The source LoRA Loader/Stacker node
|
||||
* @param {object|null} selection - The current lora selection {name, active, entry}
|
||||
*/
|
||||
export async function updateConnectedLoraInfoNodes(node, selection) {
|
||||
if (!node) {
|
||||
return;
|
||||
}
|
||||
|
||||
const infoNodes = getConnectedLoraInfoNodes(node);
|
||||
|
||||
if (infoNodes.length === 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
// No selection or inactive — clear the display on all connected info nodes
|
||||
if (!selection?.name || !selection?.active) {
|
||||
for (const infoNode of infoNodes) {
|
||||
infoNode.__loraInfoReqId = (infoNode.__loraInfoReqId || 0) + 1;
|
||||
if (typeof infoNode._setLoraInfo === "function") {
|
||||
infoNode._setLoraInfo(null);
|
||||
} else {
|
||||
infoNode.__pendingLoraInfo = null;
|
||||
}
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
// Bump request token on each info node to guard against stale async responses
|
||||
for (const infoNode of infoNodes) {
|
||||
infoNode.__loraInfoReqId = (infoNode.__loraInfoReqId || 0) + 1;
|
||||
}
|
||||
const reqIdSnapshot = new Map();
|
||||
for (const infoNode of infoNodes) {
|
||||
reqIdSnapshot.set(infoNode, infoNode.__loraInfoReqId);
|
||||
}
|
||||
|
||||
// Fetch notes for the selected lora
|
||||
try {
|
||||
const response = await api.fetchApi(
|
||||
`/lm/loras/get-notes?name=${encodeURIComponent(selection.name)}`,
|
||||
{ method: "GET" }
|
||||
);
|
||||
|
||||
if (!response?.ok) {
|
||||
throw new Error(`Failed to fetch notes for ${selection.name}`);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
const infoData = {
|
||||
name: selection.name,
|
||||
notes: data?.notes || "",
|
||||
filePath: data?.file_path || "",
|
||||
};
|
||||
|
||||
for (const infoNode of infoNodes) {
|
||||
// Discard if a newer request has been issued for this node
|
||||
if (infoNode.__loraInfoReqId !== reqIdSnapshot.get(infoNode)) {
|
||||
continue;
|
||||
}
|
||||
if (typeof infoNode._setLoraInfo === "function") {
|
||||
infoNode._setLoraInfo(infoData);
|
||||
} else {
|
||||
infoNode.__pendingLoraInfo = infoData;
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error fetching notes for lora info:", error);
|
||||
|
||||
const errorData = {
|
||||
name: selection.name,
|
||||
notes: "[Error loading notes]",
|
||||
filePath: "",
|
||||
};
|
||||
|
||||
for (const infoNode of infoNodes) {
|
||||
if (infoNode.__loraInfoReqId !== reqIdSnapshot.get(infoNode)) {
|
||||
continue;
|
||||
}
|
||||
if (typeof infoNode._setLoraInfo === "function") {
|
||||
infoNode._setLoraInfo(errorData);
|
||||
} else {
|
||||
infoNode.__pendingLoraInfo = errorData;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: "LoraManager.LoraInfo",
|
||||
|
||||
beforeRegisterNodeDef(nodeType, nodeData) {
|
||||
if (nodeData.name !== LORA_INFO_CLASS) {
|
||||
return;
|
||||
}
|
||||
|
||||
chainCallback(nodeType.prototype, "onNodeCreated", function () {
|
||||
// Add wire-only input for receiving connections from LoRA nodes
|
||||
this.addInput("lora_source", "*", { shape: 7 });
|
||||
|
||||
// Forward lora info data to the Vue widget when available.
|
||||
this._setLoraInfo = function (data) {
|
||||
const widget = this.widgets?.find(
|
||||
(w) => w.type === "LORA_INFO_DISPLAY"
|
||||
);
|
||||
if (widget) {
|
||||
if (typeof widget._setLoraInfo === "function") {
|
||||
widget._setLoraInfo(data);
|
||||
} else {
|
||||
widget.__pendingLoraInfo = data;
|
||||
}
|
||||
}
|
||||
};
|
||||
});
|
||||
|
||||
// When the lora_source wire is disconnected, clear the display.
|
||||
const origOnConnectionsChange = nodeType.prototype.onConnectionsChange;
|
||||
nodeType.prototype.onConnectionsChange = function (type, index, connected, link_info) {
|
||||
if (origOnConnectionsChange) {
|
||||
origOnConnectionsChange.apply(this, arguments);
|
||||
}
|
||||
// type 1 = input connection change; disconnected = !connected
|
||||
if (type === 1 && !connected) {
|
||||
const input = this.inputs?.[index];
|
||||
if (input?.name === "lora_source") {
|
||||
// Check if any lora_source input still has a connection
|
||||
const hasLoraSourceConnection = this.inputs?.some(
|
||||
(inp) => inp.name === "lora_source" && inp.link != null
|
||||
);
|
||||
if (!hasLoraSourceConnection) {
|
||||
this._setLoraInfo?.(null);
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
},
|
||||
});
|
||||
@@ -13,6 +13,7 @@ import {
|
||||
import { addLorasWidget } from "./loras_widget.js";
|
||||
import { applyLoraValuesToText, debounce } from "./lora_syntax_utils.js";
|
||||
import { applySelectionHighlight } from "./trigger_word_highlight.js";
|
||||
import { updateConnectedLoraInfoNodes } from "./lora_info.js";
|
||||
|
||||
app.registerExtension({
|
||||
name: "LoraManager.LoraLoader",
|
||||
@@ -185,8 +186,10 @@ app.registerExtension({
|
||||
this,
|
||||
"loras",
|
||||
{
|
||||
onSelectionChange: (selection) =>
|
||||
applySelectionHighlight(this, selection),
|
||||
onSelectionChange: (selection) => {
|
||||
applySelectionHighlight(this, selection);
|
||||
updateConnectedLoraInfoNodes(this, selection);
|
||||
},
|
||||
},
|
||||
(value) => {
|
||||
// Prevent recursive calls
|
||||
|
||||
@@ -11,6 +11,7 @@ import {
|
||||
import { addLorasWidget } from "./loras_widget.js";
|
||||
import { applyLoraValuesToText, debounce } from "./lora_syntax_utils.js";
|
||||
import { applySelectionHighlight } from "./trigger_word_highlight.js";
|
||||
import { updateConnectedLoraInfoNodes } from "./lora_info.js";
|
||||
|
||||
app.registerExtension({
|
||||
name: "LoraManager.LoraStacker",
|
||||
@@ -64,8 +65,10 @@ app.registerExtension({
|
||||
this,
|
||||
"loras",
|
||||
{
|
||||
onSelectionChange: (selection) =>
|
||||
applySelectionHighlight(this, selection),
|
||||
onSelectionChange: (selection) => {
|
||||
applySelectionHighlight(this, selection);
|
||||
updateConnectedLoraInfoNodes(this, selection);
|
||||
},
|
||||
},
|
||||
(value) => {
|
||||
// Prevent recursive calls
|
||||
|
||||
+30
-12
@@ -14,12 +14,31 @@ import { getStrengthStepPreference } from "./settings.js";
|
||||
export function addLorasWidget(node, name, opts, callback) {
|
||||
ensureLmStyles();
|
||||
|
||||
// Create container for loras
|
||||
const container = document.createElement("div");
|
||||
container.className = "lm-loras-container";
|
||||
// Create container for loras — search for an empty container already
|
||||
// in the DOM first. During undo/redo in ComfyUI Vue render mode,
|
||||
// WidgetDOM.vue reuses its component without re-calling
|
||||
// mountWidgetElement(), so we must reuse the existing DOM element
|
||||
// instead of creating an orphaned replacement.
|
||||
let container = null;
|
||||
let reuseExisting = false;
|
||||
const existingContainers = document.querySelectorAll('.lm-loras-container');
|
||||
for (const el of existingContainers) {
|
||||
if (el.children.length === 0) {
|
||||
container = el;
|
||||
reuseExisting = true;
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
forwardMiddleMouseToCanvas(container);
|
||||
forwardWheelToCanvas(container);
|
||||
if (!container) {
|
||||
container = document.createElement("div");
|
||||
container.className = "lm-loras-container";
|
||||
}
|
||||
|
||||
if (!reuseExisting) {
|
||||
forwardMiddleMouseToCanvas(container);
|
||||
forwardWheelToCanvas(container);
|
||||
}
|
||||
|
||||
// Set initial height using CSS variables approach
|
||||
const defaultHeight = 200;
|
||||
@@ -29,10 +48,8 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
// scrolls when content exceeds the allocated space.
|
||||
container.style.setProperty('--comfy-widget-min-height', `${defaultHeight}px`);
|
||||
|
||||
if (typeof LiteGraph !== 'undefined' && LiteGraph.vueNodesMode) {
|
||||
if (!reuseExisting && typeof LiteGraph !== 'undefined' && LiteGraph.vueNodesMode) {
|
||||
container.classList.add('lm-vue-node');
|
||||
// Window capture-phase hook: scroll the widget instead of zooming the canvas
|
||||
// when the wheel is over a scrollable loras list.
|
||||
enableListWheelScroll(container);
|
||||
}
|
||||
|
||||
@@ -280,8 +297,8 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
|
||||
e.preventDefault();
|
||||
e.stopPropagation();
|
||||
selectLora(name);
|
||||
container.focus(); // Focus container for keyboard events
|
||||
selectLora(name === selectedLora ? null : name);
|
||||
container.focus();
|
||||
});
|
||||
|
||||
// Conditionally create drag handle OR lock button
|
||||
@@ -732,9 +749,10 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
widget.callback = callback;
|
||||
|
||||
widget.onRemove = () => {
|
||||
container.remove();
|
||||
while (container.firstChild) {
|
||||
container.removeChild(container.firstChild);
|
||||
}
|
||||
previewTooltip.cleanup();
|
||||
// Remove keyboard event listener
|
||||
container.removeEventListener('keydown', handleKeyboardNavigation);
|
||||
};
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because one or more lines are too long
@@ -9,6 +9,7 @@ import {
|
||||
} from "./utils.js";
|
||||
import { addLorasWidget } from "./loras_widget.js";
|
||||
import { applyLoraValuesToText, debounce } from "./lora_syntax_utils.js";
|
||||
import { updateConnectedLoraInfoNodes } from "./lora_info.js";
|
||||
|
||||
app.registerExtension({
|
||||
name: "LoraManager.WanVideoLoraSelect",
|
||||
@@ -63,7 +64,11 @@ app.registerExtension({
|
||||
}
|
||||
});
|
||||
|
||||
const result = addLorasWidget(this, "loras", {}, (value) => {
|
||||
const result = addLorasWidget(this, "loras", {
|
||||
onSelectionChange: (selection) => {
|
||||
updateConnectedLoraInfoNodes(this, selection);
|
||||
},
|
||||
}, (value) => {
|
||||
// Prevent recursive calls
|
||||
if (isUpdating) return;
|
||||
isUpdating = true;
|
||||
|
||||
Reference in New Issue
Block a user