- Parse limit.output from model catalog alongside model IDs
for per-model max output token limits
- Use catalog lookup in chat_completion_json() to set max_tokens;
fall back to 4096 for unknown models (e.g. local Ollama)
- Remove the JSON retry (response_format → plain text fallback);
keep _try_salvage_json as last-resort for truncated responses
- Reduce Ollama num_ctx from 32768 to 8192 (sufficient for
metadata enrichment, saves VRAM)
- Fix stale test comment referencing removed retry
Remove tests/enrich_hf_validation/baselines/ from git tracking
(.gitignore entry + git rm --cached). These contain README snapshots
from community HF repos that may include NSFW/sensitive content.
Local files are preserved on disk for offline reference.
Commit 9a0d866b changed _strip_fenced_code_blocks to preserve bash/shell
code blocks (they carry CLI setup and trigger-word metadata signal).
Update the two affected tests to expect bash content in the output
instead of asserting it is stripped.
- Rename test_bash_code_block_stripped → test_bash_code_block_preserved
- Update assertions: expect 'pip install' in result
The bare call inside _build_prompt_context
would raise NameError because class methods don't close over class-level
scope. Use instead to trigger attribute lookup.
Update enrich_hf_metadata prompt.md clue locations for better LLM accuracy.
Update baseline report to v2 (mean 69.0, 46 models, +2.2pp vs baseline 71.1%).
Consolidate README snapshots into baselines/readmes/.
_Previous_ _find_scanner_for_model and identify_model_type contained ~25 lines
of identical scanner-iteration + path-matching logic. Factor it into
_find_model_entry() so a new scanner type or edge-case fix can't drift apart.
- Rename py/agent_cli/ -> py/metadata_ops/ (module was never agent-related)
- Rename tests/agent_cli/ -> tests/metadata_ops/
- Remove 9 low-value/debug INFO log points across agent_handlers.py,
agent_service.py, llm_service.py, and metadata_ops/__init__.py
- Keep LLM raw response at DEBUG level for diagnostics
- Consolidate per-model progress + LLM result into single concise
log line with basename instead of full path
- Update package/class/method docstrings to clarify this is a
pipeline infrastructure, not a true agent loop
Three-part fix for enrich_hf_metadata failing to extract correct preview_url
from HuggingFace collection repos where models share flat heading levels:
1. _strip_standalone_images() now converts <img> tags to markdown image
syntax  instead of stripping the URL entirely, so the LLM
can still extract preview URLs.
2. _extract_section() uses a line-count-based forward window (stopping at
<a id> anchors) for non-heading matches, instead of stopping at the
very next heading. This prevents same-level sub-headings (# Download,
# Trigger, # Sample prompt within a single model section) from
truncating the window before sample images are included.
3. Post-processor preview fallback now filters gallery images to the
model-specific README section before falling back to the repo-wide
first image.
Move the HF model list from ~/Documents/ into tests/enrich_hf_validation/test_data/
and commit the pipeline validation baseline artifacts (report.json,
preprocessing_audit.json, README snapshots) into baselines/.
Update config.py and run_validation.py defaults to use repo-relative paths
via os.path.dirname(__file__) instead of ~/Documents/ hardcode.
Originates from changes in 8fb00998 (validation pipeline audit).
- agent_service._format_base_models: output bullet list instead of
JSON array for cleaner LLM parsing
- prompt.md mapping section: replace 14-row HF→CivitAI table with
compact rule set covering 14 mapping paths including new entries
for HiDream-ai, OnomaAIResearch/Illustrious, ideogram-ai/ideogram,
Tongyi-MAI/Z-Image-Turbo, and Wan-AI/Wan2.*
- base_model extraction instruction: add guidance to infer from
model filename, YAML tags, and README body text when YAML
frontmatter has no explicit base_model:
- Rename md_to_html.py → readme_processor.py (file no longer just HTML conversion)
- _extract_section: include YAML frontmatter, use heading-level-aware forward
walk (sub-headings under # are included), increase walk limit past 30 lines
- _is_heading: exclude </hN> closing tags from boundary detection
- _heading_level: new helper for heading-level-aware section matching
- css: yield 0 for heading like closing tags, was unexpectedly caught by _is_heading
- extract_gallery_images: fix YAML block scalar (text: >-) prompt extraction;
use endswith instead of == to detect the block marker
- _strip_widget_section: add to clean_readme_for_llm (widget text is handled
by post-processor, not needed in LLM prompt)
- _strip_standalone_images: keep markdown image URLs intact for LLM preview
extraction (was stripping to alt text only)
- list_base_models: switch from scanner-cache aggregation to
CivitaiBaseModelService.get_base_models() - always returns full list
- Ollama: add num_ctx=32768 to payload options so thinking models have room
to both reason and produce output
- Add tests/agent_cli/test_readme_processor.py: 59 tests covering extraction,
cleaning, section matching, heading detection
- Update existing tests for behavioral changes
- PostProcessor returns updates dict from enrich_hf_metadata
- AgentService includes updated_data per model in WebSocket progress events
- Convert preview_url to HTTP URL via config.get_preview_static_url()
- LoraContextMenu: showEnhancedProgress + updateSingleItem per model
- BulkContextMenu: same pattern, remove window.location.reload()
- Guard empty updated_data and clean up callbacks on HTTP error
- Add clean_readme_for_llm() to strip noise from README before LLM injection
- Keep widget section text (valuable tag signal) and unmarked code blocks (trigger words)
- Preserve standalone image alt text instead of removing entirely
- Switch Ollama to native /api/chat with think:false to fix empty content on thinking models
- Extract Sample Gallery table images and deduplicate with widget images
- Only strip code blocks with explicit language tags (bash)
- Add notes and usage_tips fields to SKILL.md output format and post-processor
- Clean up dead code, fix regex edge cases, remove double type annotation
- Replace hardcoded provider list with PROVIDER_PRESETS (OpenAI, Ollama,
DeepSeek, Groq, OpenRouter, OpenCode Go, Custom)
- Load model lists from models.dev/api.json catalog at startup
- Add Combobox vanilla JS component for model/base-URL selection
- Fetch local Ollama models via live API instead of catalog
- Hide API key values from frontend (boolean-only llm_api_key_set)
- Add i18n translations for all 9+ locales
- Update snapshot tests for new response fields
Widget entries with unquoted multi-line YAML scalars (e.g. "text: two samurais...\n continuation") were not parsed, leaving gallery image prompts empty. Add a third branch for plain scalar format alongside the existing quoted and >- folded block handlers.
- Add extract_gallery_images() to parse YAML widget entries from README
frontmatter, convert relative image URLs to absolute HF URLs, and
build civitai.images-compatible entries with prompt metadata
- LLM now extracts recommended_width/recommended_height from README
(e.g. "Best Dimensions"), used as gallery image dimensions
- extract_gallery_images() accepts default_width/height parameters,
falling back to 512x512 when LLM provides no recommendation
- Frontend ShowcaseView.js: defensive NaN guard for 0 width/height
- post_processor: consistently merge civitai updates across triggers,
description, and gallery blocks with distinct variable names
- SKILL.md: add recommended_width/recommended_height to output schema
- 62 tests pass, including gallery extraction and dimension tests
- Add identify_model_type() helper to determine lora/checkpoint/embedding
- Pass priority_tags from user settings to LLM prompt for tag relevance
- SKILL.md: instruct LLM to exclude technical/generic HF tags, cross-reference
against priority_tags; forbid ['None'] placeholder for trigger words
- post_processor: fix preview_url not updated after download (now writes local
.webp path to metadata); write trigger words to civitai.trainedWords instead
of top-level; sanitize ['None']/'null'/'n/a' placeholder values to []
- download_preview() now returns str | None (local path) instead of bool
- Update tests for new return type and nested civitai.trainedWords structure
Merge skill.yaml (metadata) and prompt.md (prompt template) into a
single SKILL.md file with YAML frontmatter, matching the agent-skill
convention used by opencode and Claude Code.
- Add frontmatter parser (_parse_skill_file) to SkillRegistry
- Remove skill.yaml, prompt.md, empty skills/__init__.py
- Remove obsolete load_handler method
- Update tests for new format and cleaned-up fields
Introduce an agent skill framework for LLM-driven metadata enrichment:
- AgentCLI (py/agent_cli/): in-process wrappers around internal services
using standard relative imports, eliminating the need for sys.path hacks
- LLMService: centralized BYOK (bring-your-own-key) LLM client supporting
OpenAI, Ollama, and custom OpenAI-compatible endpoints
- PostProcessor: deterministic engine that applies LLM output via AgentCLI
(replaces old handler.py + _BASE_MODEL_ALIASES approach)
- SkillRegistry: filesystem-based skill discovery (skill.yaml + prompt.md)
- AgentService: orchestrates skill execution with WebSocket progress
- Frontend AgentManager: WebSocket listeners, skill execution, config UI
- Context menu entries (single + bulk) for "Enrich Metadata (Agent)"
- Settings UI for AI Provider configuration (BYOK)
- Full i18n support across 9 locales
Bug fixes found during review:
- aiohttp.web.json_response: status_code= -> status=
- settings_modal cancelEditApiKey: wrong argument position
- AgentManager.isLlmConfigured: allow Ollama without API key
- PostProcessor._merge_tags: lowercase all tags to match TagUpdateService
Replace native <select> with a searchable dropdown that:
- Filters options as the user types
- Shows filename-inferred suggestions at the top in a "Suggested" section
- Supports keyboard navigation (ArrowUp/Down/Enter/Escape)
- Allows typing custom values not in the list
- Removes dead .base-model-selector CSS
Adds 3 new i18n keys (baseModelSearchPlaceholder, baseModelSuggested,
baseModelNoMatch) with translations for all 9 locales.
Security hardening:
- Validate repo format with strict regex (reject .. traversal)
- Validate filename rejects path separators and ..
- Validate relative_path rejects absolute paths and ..
- Verify model_root is within configured scanner roots using
realpath + os.sep guard to prevent prefix-match bypass
- Add realpath-based escape detection for final dest_path
Bug fixes:
- Fix WebSocket leak in _downloadHfSingle: wrap ws.close() in
try/finally so it closes even if downloadHfModel() throws
- Same fix for batch HF download per-file WebSocket loop
Frontend hardening:
- Tighten HF repo regex: require huggingface.co for full URLs,
reject bare .. patterns
- Add 12 unit tests for detectUrlType() covering HF resolve,
HF repo, CivitAI, CivArchive, direct HTTP, edge cases
- Unify single-URL and multi-URL HF repo flows to use the same batch
preview interface (remove separate repoFileStep)
- Remove unnecessary cloud icon from HF batch preview items
- Use formatFileSize() instead of hardcoded MB text
- Change default selection to unchecked (no preselected files)
- Add select all / deselect all checkbox with dynamic Next button
- Clean up dead CSS, HTML template, and JS methods from removed
repoFileStep
- Add selectAll i18n key with translations for all 10 locales
- Fix batch progress bar name fallback for HF items
A model not being found on CivArchive by hash is a routine case (the
model simply isn't published there), not an error. The callers already
log the outcome at WARNING (bulk_metadata_refresh) or DEBUG
(metadata_sync_service) with full context, making this ERROR-level log
both misleading and redundant.
Cache corruption (NULL model_name/file_name from legacy DB rows or partial
writes) caused format_response to raise KeyError/AttributeError, failing the
entire /loras/list request and showing no models in the UI.
Fix across three layers:
- format_response (lora/checkpoint/embedding): replace direct dict[] access
with .get() fallbacks; return None for entries missing file_path
- handlers: filter None entries from list/excluded/fetch/duplicate/conflict
endpoints instead of letting them crash or appear as null in responses
- model_scanner: always use validate_batch repaired copies (previously
discarded when no invalid entries, leaving None values in raw_data)
- persistent_model_cache: add or-empty-string guards on read and write for
nullable TEXT columns (model_name, file_name, folder, base_model, etc.)
git clean -fd in _perform_git_update deleted untracked, non-ignored
directories (wildcards, stats, backups, civitai, caches, logs) during
portable-mode updates, since released tags do not list them in .gitignore.
Add -e excludes for all user-managed paths to both nightly and stable
update branches. Add regression tests for both paths.
Move NodeRegistry from a single global _nodes dict to a per-client
(_tab_nodes) structure so that multiple ComfyUI browser tabs no
longer overwrite each other's workflow node data during a
lora_registry_refresh cycle. The merged result is a union of all
known tabs' target nodes, eliminating the non-deterministic failure
where send-to-workflow could randomly target a tab lacking valid
targets.
- NodeRegistry.register_nodes(sid, nodes) replaces per-tab data
without affecting other tabs.
- NodeRegistry.get_merged_registry() returns the union across all
connected clients, together with tab_count / per-tab metadata.
- prepare_for_refresh() snapshots the current active sockets; caller
re-reads before merging so that newly-connected tabs are not pruned.
- workflow_registry.js sends api.clientId in the POST body so the
backend can identify which tab is registering.
- Add &withMeta=true to image info URL so API returns full generation
metadata (resources with hash/type) instead of null meta
- Fix checkpoint assignment guard: check modelId instead of id so non-
checkpoint types (upscaler) are not wrongly set as recipe checkpoint
- Skip modelVersionIds loop when resources/civitaiResources already
provided LoRAs, preventing hash-resolved duplicates
- Fix int/str type comparison in CivArchive get_model_version so
version ID matching works correctly
When CivitAI image API returns meta=null and modelVersionIds at root
level, the import flow now:
- Injects modelVersionIds + browsingLevel into a minimal metadata dict
so the parser can discover LoRAs and checkpoints (both import-from-url
and analyze-image paths)
- Adds checkpoint dedup + fallback in the parser's modelVersionIds
handler to avoid duplicate API calls
- Runs EXIF extraction unconditionally in analyze-image path, then
merges with API metadata (fixes gen params loss)
- Propagates preview_nsfw_level through all three import paths:
import-from-url, analyze-image (UI Import), and batch-import,
plus the frontend save flow
- Prefer file type (UNet/Diffusion Model) over baseModel name when
deciding whether a checkpoint routes to the unet folder
- Add UNet to backend primary file type whitelist
- Add Krea 2 to DIFFUSION_MODEL_BASE_MODELS
- Include UNet/Diffusion Model files in frontend file selection UI
- Use actual file type from CivitAI in download params instead of
hardcoded 'Model'
- Convert marquee selection from viewport to document coordinates so
scrolling during a drag no longer deselects off-screen cards.
- Add RAF-based auto-scroll when dragging near viewport edges.
- Compute off-screen card positions from VirtualScroller layout
parameters instead of relying on DOM queries.
