mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-07-06 09:21:16 -03:00
170c8068c5
- extract_relevant_section(): trim README to model-filename-matching section for collection repos (download link, anchor ID, heading strategies) - _strip_standalone_images(): preserve markdown image URLs so LLM can extract preview_url; strip only HTML <img> tags - extract_simple_markdown_images(): extract civitai.images from ![]() body - extract_html_img_tags(): extract from <img src="..."> (deadman44-style) - extract_gallery_images(): fix widget parser for YAML - output: dash prefix - _is_heading: exclude </hN> closing tags from boundary detection - _extract_section: start at matching heading when match IS a heading line - _try_salvage_json(): recover truncated JSON (close braces/brackets in LIFO order, close unterminated strings, strip trailing commas) - PostProcessor: store _llm_confidence, add instance_prompt YAML fallback - agent_service: pass model_basename to prompt, trim README via extract_relevant_section before clean_readme_for_llm - Add tests/enrich_hf_validation/ suite: 100-model pipeline with progress checkpoint/resume, per-field scoring, markdown+JSON reporting - Fix evaluation_engine: read _llm_confidence (not _llm_response)
98 lines
3.5 KiB
Python
98 lines
3.5 KiB
Python
"""Configuration for the HF metadata enrichment validation suite.
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Loads user settings, defines paths, and pulls constants from the main
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codebase (``py.utils.constants``).
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"""
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from __future__ import annotations
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import json
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import logging
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import os
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from typing import Any, Dict, List
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logger = logging.getLogger(__name__)
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# ---------------------------------------------------------------------------
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# Default paths
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# ---------------------------------------------------------------------------
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_DEFAULT_MODELS_FILE = os.path.expanduser(
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"~/Documents/hf_lora_models.txt"
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)
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_DEFAULT_SETTINGS_PATH = os.path.expanduser(
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"~/.config/ComfyUI-LoRA-Manager/settings.json"
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)
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_DEFAULT_OUTPUT_DIR = "/tmp/hf_enrich_validation"
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# ---------------------------------------------------------------------------
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# Constants from the main codebase (copied at import time)
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# ---------------------------------------------------------------------------
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# Priority tags used in the LLM prompt for tag selection guidance.
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CIVITAI_MODEL_TAGS: List[str] = [
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"character", "concept", "clothing", "realistic", "anime", "toon",
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"furry", "style", "poses", "background", "tool", "vehicle",
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"buildings", "objects", "assets", "animal", "action",
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]
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# Base models recognised as valid values.
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SUPPORTED_BASE_MODELS: List[str] = [
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"SD 1.4", "SD 1.5", "SD 1.5 LCM", "SD 1.5 Hyper",
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"SD 2.0", "SD 2.1",
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"SD 3", "SD 3.5", "SD 3.5 Medium", "SD 3.5 Large", "SD 3.5 Large Turbo",
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"SDXL 1.0", "SDXL Lightning", "SDXL Hyper",
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"Flux.1 D", "Flux.1 S", "Flux.1 Krea", "Flux.1 Kontext",
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"Flux.2 D", "Flux.2 Klein 9B", "Flux.2 Klein 9B-base",
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"Flux.2 Klein 4B", "Flux.2 Klein 4B-base",
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"AuraFlow", "Chroma", "PixArt a", "PixArt E",
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"Hunyuan 1", "Lumina", "Kolors",
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"NoobAI", "Illustrious", "Pony", "Pony V7",
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"HiDream", "Qwen", "ZImageTurbo", "ZImageBase",
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"SVD", "LTXV", "LTXV2", "LTXV 2.3",
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"CogVideoX", "Mochi",
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"Wan Video", "Wan Video 1.3B t2v", "Wan Video 14B t2v",
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"Wan Video 14B i2v 480p", "Wan Video 14B i2v 720p",
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"Wan Video 2.2 TI2V-5B", "Wan Video 2.2 T2V-A14B",
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"Wan Video 2.2 I2V-A14B",
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"Wan Video 2.5 T2V", "Wan Video 2.5 I2V",
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"Hunyuan Video", "Anima", "Ernie", "Ernie Turbo",
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"Nucleus", "Krea 2",
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]
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# Placeholder values the LLM sometimes emits that should count as "empty".
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PLACEHOLDER_VALUES = frozenset({
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"none", "null", "n/a", "unknown", "not available",
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"not specified", "no trigger words", "no trigger word",
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})
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# ---------------------------------------------------------------------------
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# User settings loader
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# ---------------------------------------------------------------------------
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def load_settings(settings_path: str) -> Dict[str, Any]:
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"""Load LoRA Manager settings from *settings_path*.
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Returns a flat dict with the LLM configuration fields that the
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enrichment pipeline depends on.
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"""
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path = os.path.expanduser(settings_path)
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if not os.path.exists(path):
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raise FileNotFoundError(
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f"Settings file not found: {path}\n"
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"Please provide a valid --settings path."
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)
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with open(path, "r", encoding="utf-8") as fh:
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raw: Dict[str, Any] = json.load(fh)
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# Extract LLM-relevant config
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return {
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"llm_provider": raw.get("llm_provider", "ollama"),
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"llm_model": raw.get("llm_model", "qwen3.5:9b"),
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"llm_api_base": raw.get("llm_api_base", "http://localhost:11434/v1"),
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"llm_api_key": raw.get("llm_api_key", ""),
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"settings_path": path,
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}
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