Eric HissandCopilot
373ea8bda3
- Add Wildcard Prompt Composer and Wildcard Character Composer builder nodes (core/builder, web/prompt_builder.js, builders/, vp wildcard lists) - Add browser-based wildcard review tool (tools/wildcard_review) with manifest-based undo - Add wildcard catalog/curation, surreal compiler/lint/scene, profile token budget - README: document all 18 nodes, bump to v2.2.0, fix stale node/platform lists; CHANGELOG 2.2.0 - Rewrite NODE_COMPARISON for 18 nodes; fix QUICKSTART (dead test_setup.py ref, menu path) and QUICK_REFERENCE node list - gitignore review manifests and CLAUDE.md Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
152 lines
7.9 KiB
Python
152 lines
7.9 KiB
Python
"""
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Semantic Variation Node
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Makes controlled variations of a wildcard prompt. A plain re-roll replaces every random pick
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with an unrelated one. This node starts from the picks `seed` would make and moves each one to
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a SEMANTIC NEIGHBOUR inside its own list: a little for most slots, a lot for a few.
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variation 0 the plain seeded prompt, nothing moved
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variation 1, 2... different variations of that same prompt, each reproducible
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strength how far every slot drifts: 0.1 = nearest 1% of its list, 0.5 = a quarter of the way out,
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0.7 = halfway, 1.0 = the far end of the list
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far_jumps how many slots jump (far_strength) instead of drifting
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avoid_recent build several candidates and keep the one least like what you generated lately
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Slots are the wildcard constructs in the text: __name__, __objects[tag AND tag]__, {a|b|c}.
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Fixed words in the prompt are not touched. Feed `text` and `llm_instructions` to an enhancer
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node or straight to a text encoder.
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Author: Eric Hiss (GitHub: EricRollei)
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License: Dual License (Non-Commercial and Commercial Use). See LICENSE.
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"""
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import traceback
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from typing import Tuple
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from .core.variability import VariationSettings
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from .core.wildcards import split_paths
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from .variability_support import (
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EMBEDDER_CHOICES, available_embedders, direction_choices, get_embedder, get_variator,
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)
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from .wildcard_support import database_provider, wildcard_nsfw_input
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class SemanticVariation:
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"""Vary a wildcard prompt by moving each random pick to a semantic neighbour."""
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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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"text": ("STRING", {
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"multiline": True,
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"default": "__person__, __gestures__, beside __objects/**__ in __spaces/**__. __light/setups__.",
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"tooltip": "Prompt with wildcard syntax. Every __name__, tag query and {a|b|c} is a slot that can be varied.",
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}),
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"seed": ("INT", {
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"default": 0, "min": 0, "max": 0xFFFFFFFFFFFFFFFF,
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"tooltip": "Seed for the BASE picks. Keep it fixed and change `variation` to explore around one prompt.",
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}),
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"variation": ("INT", {
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"default": 1, "min": 0, "max": 0xFFFFFFFF,
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"tooltip": "0 = the base prompt untouched. 1, 2, 3... = different variations of it, each reproducible.",
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}),
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"strength": ("FLOAT", {
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"default": 0.35, "min": 0.0, "max": 1.0, "step": 0.05,
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"tooltip": "How far every slot drifts within its list. 0.1 = nearest few, 0.5 = a quarter of the way out, 0.7 = halfway, 1.0 = far end.",
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}),
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"far_jumps": ("INT", {
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"default": 0, "min": 0, "max": 16,
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"tooltip": "How many slots jump with far_strength instead of drifting. Which ones is decided by `variation`.",
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}),
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"far_strength": ("FLOAT", {
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"default": 0.9, "min": 0.0, "max": 1.0, "step": 0.05,
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"tooltip": "Strength used for the slots that jump.",
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}),
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"embedder": (EMBEDDER_CHOICES, {
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"default": "auto",
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"tooltip": (
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"What 'similar' means. auto = connected clip, else Qwen3-VL-Embedding, else open_clip.\n"
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"qwen3vl: similar in meaning and look. openclip / graph_clip: similar in look.\n"
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"sentence: similar in meaning. lexical: spelling only (no model)."
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),
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}),
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"avoid_recent": ("BOOLEAN", {
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"default": False,
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"tooltip": "Make several candidate variations and keep the one least similar to recently generated prompts.",
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}),
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},
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"optional": {
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"clip": ("CLIP", {
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"tooltip": "Optional. A CLIP with a pooled output (CLIP-L/G). Used as the embedder when `embedder` is auto or graph_clip.",
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}),
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"legacy_syntax": ("BOOLEAN", {
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"default": True,
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"tooltip": "Also accept the v1 forms {animal} and {label:a|b|c}.",
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}),
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"extra_paths": ("STRING", {
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"multiline": True,
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"default": "",
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"tooltip": "Extra wildcard folders, one per line, highest priority. ComfyUI/models/wildcards is always searched.",
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}),
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# New inputs are only ever APPENDED below this line, so saved workflows keep their widget order.
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"direction": (direction_choices(), {
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"default": "none",
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"tooltip": (
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"Lean every move along a named axis, e.g. ordinary_to_uncanny or new_to_decayed.\n"
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"Axes are example phrases in variability/directions.yaml; add your own in directions_user.yaml.\n"
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"strength still decides how far a slot may go; this decides which way."
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),
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}),
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"direction_amount": ("FLOAT", {
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"default": 0.0, "min": -3.0, "max": 3.0, "step": 0.1,
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"tooltip": (
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"0 = no lean. Above 0 leans toward the axis's `to` side (uncanny, decayed, ...),\n"
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"below 0 toward its `from` side. 1.0 is a clear lean, 2-3 lets the axis dominate.\n"
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"The report shows each slot's lean so you can see whether an axis bites on a given list."
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),
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}),
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**wildcard_nsfw_input(),
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},
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}
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RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING")
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RETURN_NAMES = ("text", "llm_instructions", "base_text", "report")
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FUNCTION = "vary"
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CATEGORY = "Eric Prompt Enhancers"
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@classmethod
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def IS_CHANGED(cls, avoid_recent=False, **kwargs):
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"""With avoid_recent on, the result depends on the memory, so the node must not be cached."""
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if avoid_recent:
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import time
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return float(time.time())
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return ""
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def vary(self, text, seed, variation, strength, far_jumps, far_strength, embedder, avoid_recent,
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clip=None, legacy_syntax=True, extra_paths="", direction="none", direction_amount=0.0, nsfw="off",
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violence_filter="off") -> Tuple[str, str, str, str]:
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try:
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chosen_embedder, notes = get_embedder(embedder, clip)
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variator = get_variator(chosen_embedder, split_paths(extra_paths))
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settings = VariationSettings(
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variation=int(variation), strength=float(strength), far_jumps=int(far_jumps),
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far_strength=float(far_strength), avoid_recent=bool(avoid_recent),
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direction=str(direction or "none"), direction_amount=float(direction_amount or 0.0),
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)
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result = variator.vary(
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text, int(seed), settings,
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legacy=bool(legacy_syntax), providers={"db": database_provider}, nsfw=nsfw, violence=violence_filter,
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)
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result.notes = notes + result.notes
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report = result.report()
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if result.resolution.warnings:
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report += "\n" + "\n".join("warning: " + warning for warning in result.resolution.warnings)
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if chosen_embedder.name.startswith("lexical"):
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found = available_embedders(clip)
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report += "\nembedders available here: " + ", ".join(f"{name} ({where})" for name, where in found.items())
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return (result.resolution.text, result.resolution.format_for_llm(), result.base_text, report)
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except Exception as error: # never break the graph over a prompt
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traceback.print_exc()
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return (text, "", text, f"Semantic Variation error, text passed through unchanged: {error}")
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