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
Move extra folder path resolution from _initialize_services (app.on_startup)
into Config.__init__ via new _load_extra_paths_from_settings() method.
This eliminates a redundant second symlink scan and consolidates all
'Found roots' / 'Found extra roots' logs into one contiguous block
during custom node import, before the ComfyUI server starts.
- Fix config.py: save and restore main paths when processing extra folder paths to prevent
_prepare_checkpoint_paths from overwriting checkpoints_roots and unet_roots
- Fix lora_manager.py: apply library settings during initialization to load extra folder paths
in ComfyUI plugin mode
- Fix checkpoint_routes.py: merge checkpoints/unet roots with extra paths in API endpoints
- Add logging for extra folder paths
Fixes issue where extra folder paths were not recognized for checkpoints and unet models.
- Fix config.py: save and restore main paths when processing extra folder paths to prevent
_prepare_checkpoint_paths from overwriting checkpoints_roots and unet_roots
- Fix lora_manager.py: apply library settings during initialization to load extra folder paths
in ComfyUI plugin mode
- Fix checkpoint_routes.py: merge checkpoints/unet roots with extra paths in API endpoints
- Add logging for extra folder paths
Fixes issue where extra folder paths were not recognized for checkpoints and unet models.
- Initialize logging configuration via `setup_logging()` when not in standalone mode
- Detect standalone mode using environment variables `LORA_MANAGER_STANDALONE` and `HF_HUB_DISABLE_TELEMETRY`
- Remove redundant `STANDALONE_MODE` variable that previously checked `sys.modules`
Introduce `relax_csp_for_remote_media` middleware that modifies Content Security Policy headers to permit loading media from trusted external domains (Civitai and Genur). This is necessary for LoRA Manager UI previews when ComfyUI runs with `--disable-api-nodes`, which otherwise blocks remote images and videos. The middleware is inserted after ComfyUI's `block_external_middleware` to properly extend the restrictive CSP header.
- Added ModelMetadataProvider and CivitaiModelMetadataProvider for handling model metadata.
- Introduced SQLiteModelMetadataProvider for SQLite database integration.
- Created metadata_service.py to initialize and configure metadata providers.
- Updated CivitaiClient to register as a metadata provider.
- Refactored download_manager to use the new download_file method.
- Added SQL schema for models, model_versions, and model_files.
- Updated requirements.txt to include aiosqlite.
- Created zh-CN.json and zh-TW.json for Simplified and Traditional Chinese translations respectively.
- Added comprehensive test suite in test_i18n.py to validate JSON structure, server-side i18n functionality, and translation completeness across multiple languages.
- Added BaseModelRoutes class to handle common routes and logic for model types.
- Created CheckpointRoutes class inheriting from BaseModelRoutes for checkpoint-specific routes.
- Implemented CheckpointService class for handling checkpoint-related data and operations.
- Developed LoraService class for managing LoRA-specific functionalities.
- Introduced ModelServiceFactory to manage service and route registrations for different model types.
- Established methods for fetching, filtering, and formatting model data across services.
- Integrated CivitAI metadata handling within model routes and services.
- Added pagination and filtering capabilities for model data retrieval.
- Implemented CSS styles for the statistics page layout and components.
- Developed JavaScript functionality for managing statistics, including data fetching, chart rendering, and tab navigation.
- Created HTML template for the statistics page, integrating dynamic content for metrics, charts, and insights.
- Added responsive design adjustments and loading states for better user experience.
