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https://github.com/willmiao/ComfyUI-Lora-Manager.git
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191c4e03cd
The model field now accepts either a manual string or a MODEL connection. When wired, the model name is extracted from the patcher's cached_patcher_init (registered by core loaders load_checkpoint_guess_config and load_diffusion_model, preserved through LoRA clones) and converted to a ComfyUI-style relative name via config model roots. - model input declared as "STRING,MODEL" with widgetType STRING, so the text widget and the dual-type connection slot coexist; non-STRING/MODEL links are rejected by frontend and backend type validation - UNETLoaderLM GGUF branch now registers a custom cached_patcher_init reload factory so GGUF models participate in name extraction and ModelPatcher deepclone/dynamic machinery - shared collect_overwrite_params() helper keeps the node and the metadata extractor conversion logic in sync; extraction failures are logged instead of silently dropping the overwrite
170 lines
6.4 KiB
Python
170 lines
6.4 KiB
Python
"""Metadata Overwrite node — allows users to manually specify generation parameters
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that override the automatically collected/inferred metadata.
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Most inputs have falsy defaults (empty string / 0) which are skipped.
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clip_skip uses a sentinel default (-25) so that a wired value of 0 is
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preserved — both ComfyUI and A1111 conventions have no meaningful 0 value,
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but users may wire 0 to express "no clip skip / default".
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"""
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from typing import Any
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from ..metadata_collector.constants import CLIP_SKIP_SENTINEL as _CLIP_SKIP_SENTINEL
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from ..metadata_collector.overwrite_utils import collect_overwrite_params
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class MetadataOverwriteLM:
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NAME = "Metadata Overwrite (LoraManager)"
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CATEGORY = "Lora Manager/utils"
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DESCRIPTION = (
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"Manually specify generation parameters to override automatically collected "
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"metadata. Only filled/connected inputs will take effect — empty defaults "
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"are ignored."
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)
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@classmethod
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def INPUT_TYPES(cls) -> dict[str, Any]:
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return {
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"optional": {
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"prompt": (
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"STRING",
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{
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"default": "",
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"multiline": True,
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"tooltip": "Positive prompt. Only overwrites when non-empty.",
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},
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),
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"negative_prompt": (
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"STRING",
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{
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"default": "",
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"multiline": True,
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"tooltip": "Negative prompt. Only overwrites when non-empty.",
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},
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),
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"seed": (
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"INT",
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{
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"default": 0,
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"min": 0,
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"max": 0xFFFFFFFFFFFFFFFF,
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"control_after_generate": False,
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"tooltip": "Seed value. Only overwrites when > 0.",
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},
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),
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"steps": (
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"INT",
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{
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"default": 0,
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"min": 0,
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"max": 10000,
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"tooltip": "Number of steps. Only overwrites when > 0.",
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},
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),
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"cfg_scale": (
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"FLOAT",
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{
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"default": 0.0,
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"min": 0.0,
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"max": 100.0,
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"tooltip": "CFG scale. Only overwrites when > 0.",
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},
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),
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"sampler": (
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"STRING",
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{
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"default": "",
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"tooltip": "Sampler name. Only overwrites when non-empty.",
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},
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),
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"scheduler": (
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"STRING",
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{
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"default": "",
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"tooltip": "Scheduler name. Only overwrites when non-empty.",
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},
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),
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"model": (
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"STRING,MODEL",
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{
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"default": "",
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"widgetType": "STRING",
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"tooltip": (
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"The checkpoint or diffusion model (UNet) used "
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"for generation. Fill in the name manually or "
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"connect a MODEL output — the model name is then "
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"extracted automatically. Only overwrites when "
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"non-empty."
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),
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},
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),
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"loras": (
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"STRING",
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{
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"default": "",
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"multiline": True,
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"tooltip": (
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"LoRA syntax, e.g. <lora:name:strength> "
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"or <lora:name:model_strength:clip_strength>, "
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"separated by spaces. Only overwrites when non-empty."
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),
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},
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),
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"size": (
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"STRING",
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{
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"default": "",
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"tooltip": (
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"Image size in WIDTHxHEIGHT format (e.g. 512x768). "
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"Only overwrites when non-empty."
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),
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},
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),
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"clip_skip": (
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"INT",
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{
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"default": _CLIP_SKIP_SENTINEL,
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"min": -25,
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"max": 24,
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"tooltip": (
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"Clip skip (ComfyUI: -24..-1, A1111: 1+). "
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"Default -25 means not set — any other value "
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"overwrites."
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),
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},
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),
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"additional_data": (
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"STRING",
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{
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"default": "",
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"multiline": True,
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"tooltip": (
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"Additional data to embed in the image metadata. "
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"Inserted between Clip skip and Model hash in the "
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"A1111-compatible parameters string. "
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'Example: "Copyright": "Some license info"'
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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 = ("METADATA",)
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RETURN_NAMES = ("metadata",)
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FUNCTION = "collect_metadata"
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OUTPUT_NODE = True
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def collect_metadata(self, **kwargs: Any) -> tuple[dict[str, Any]]:
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"""Collect non-default input values into a metadata dict.
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For most fields, a falsy value (empty string, 0) means "not set"
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and is skipped. clip_skip uses a dedicated sentinel (-25) so that
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a wired value of 0 is preserved and reaches the metadata pipeline.
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The ``model`` field accepts either a manual string or a wired MODEL
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(ModelPatcher) connection; in the latter case the underlying model
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name is extracted from the patcher's ``cached_patcher_init`` and
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stored as a ComfyUI-style relative path.
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"""
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return (collect_overwrite_params(kwargs),)
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