When Civitai returns 429 (Too Many Requests) during example image
downloads, the previous behavior treated all failures identically and
permanently removed the corresponding images from model metadata —
making them impossible to retry.
This commit adds:
- 429 detection + Retry-After header parsing in download_to_memory
- Exponential backoff retry (up to 3 attempts) in
download_model_images_with_tracking
- Separate tracking of rate-limited vs permanently failed URLs
- rate_limited_models progress tracking persisted to disk
- Rate-limited models are NOT added to failed_models/processed_models
so they are automatically retried on subsequent download runs
- Force mode clears failed_models when rate-limited images exist
- 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
Extract auto-newline-on-paste logic into shared setupAutoNewlineOnPaste() utility in uiHelpers.js.
Apply it to both the Download modal (modelUrl) and Batch Import modal (batchUrlInput)
textarea, so users can paste multiple URLs in succession without manually pressing Enter.
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.)
