feat(agent): enrich_hf_metadata — filename-aware section matching, preview extraction for markdown/HTML/widget, JSON salvage, instance_prompt fallback, and validation suite

- 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)

tests/enrich_hf_validation/config.py

@@ -0,0 +1,97 @@
+"""Configuration for the HF metadata enrichment validation suite.
+
+Loads user settings, defines paths, and pulls constants from the main
+codebase (``py.utils.constants``).
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+from typing import Any, Dict, List
+
+logger = logging.getLogger(__name__)
+
+# ---------------------------------------------------------------------------
+# Default paths
+# ---------------------------------------------------------------------------
+
+_DEFAULT_MODELS_FILE = os.path.expanduser(
+    "~/Documents/hf_lora_models.txt"
+)
+_DEFAULT_SETTINGS_PATH = os.path.expanduser(
+    "~/.config/ComfyUI-LoRA-Manager/settings.json"
+)
+_DEFAULT_OUTPUT_DIR = "/tmp/hf_enrich_validation"
+
+# ---------------------------------------------------------------------------
+# Constants from the main codebase (copied at import time)
+# ---------------------------------------------------------------------------
+
+# Priority tags used in the LLM prompt for tag selection guidance.
+CIVITAI_MODEL_TAGS: List[str] = [
+    "character", "concept", "clothing", "realistic", "anime", "toon",
+    "furry", "style", "poses", "background", "tool", "vehicle",
+    "buildings", "objects", "assets", "animal", "action",
+]
+
+# Base models recognised as valid values.
+SUPPORTED_BASE_MODELS: List[str] = [
+    "SD 1.4", "SD 1.5", "SD 1.5 LCM", "SD 1.5 Hyper",
+    "SD 2.0", "SD 2.1",
+    "SD 3", "SD 3.5", "SD 3.5 Medium", "SD 3.5 Large", "SD 3.5 Large Turbo",
+    "SDXL 1.0", "SDXL Lightning", "SDXL Hyper",
+    "Flux.1 D", "Flux.1 S", "Flux.1 Krea", "Flux.1 Kontext",
+    "Flux.2 D", "Flux.2 Klein 9B", "Flux.2 Klein 9B-base",
+    "Flux.2 Klein 4B", "Flux.2 Klein 4B-base",
+    "AuraFlow", "Chroma", "PixArt a", "PixArt E",
+    "Hunyuan 1", "Lumina", "Kolors",
+    "NoobAI", "Illustrious", "Pony", "Pony V7",
+    "HiDream", "Qwen", "ZImageTurbo", "ZImageBase",
+    "SVD", "LTXV", "LTXV2", "LTXV 2.3",
+    "CogVideoX", "Mochi",
+    "Wan Video", "Wan Video 1.3B t2v", "Wan Video 14B t2v",
+    "Wan Video 14B i2v 480p", "Wan Video 14B i2v 720p",
+    "Wan Video 2.2 TI2V-5B", "Wan Video 2.2 T2V-A14B",
+    "Wan Video 2.2 I2V-A14B",
+    "Wan Video 2.5 T2V", "Wan Video 2.5 I2V",
+    "Hunyuan Video", "Anima", "Ernie", "Ernie Turbo",
+    "Nucleus", "Krea 2",
+]
+
+# Placeholder values the LLM sometimes emits that should count as "empty".
+PLACEHOLDER_VALUES = frozenset({
+    "none", "null", "n/a", "unknown", "not available",
+    "not specified", "no trigger words", "no trigger word",
+})
+
+
+# ---------------------------------------------------------------------------
+# User settings loader
+# ---------------------------------------------------------------------------
+
+def load_settings(settings_path: str) -> Dict[str, Any]:
+    """Load LoRA Manager settings from *settings_path*.
+
+    Returns a flat dict with the LLM configuration fields that the
+    enrichment pipeline depends on.
+    """
+    path = os.path.expanduser(settings_path)
+    if not os.path.exists(path):
+        raise FileNotFoundError(
+            f"Settings file not found: {path}\n"
+            "Please provide a valid --settings path."
+        )
+
+    with open(path, "r", encoding="utf-8") as fh:
+        raw: Dict[str, Any] = json.load(fh)
+
+    # Extract LLM-relevant config
+    return {
+        "llm_provider": raw.get("llm_provider", "ollama"),
+        "llm_model": raw.get("llm_model", "qwen3.5:9b"),
+        "llm_api_base": raw.get("llm_api_base", "http://localhost:11434/v1"),
+        "llm_api_key": raw.get("llm_api_key", ""),
+        "settings_path": path,
+    }