modified: The matrix share feature is now only available when the `matrix-nio` dependency is installed.
If `matrix-nio` is not installed:
1. Apply a strikethrough to the matrix checkbox text in the share UI and display a tooltip.
2. A warning is logged at startup indicating that `matrix-nio` is missing, along with the installation command.
fixed: Corrected an issue where PR #2025 was merged into draft-v4 but applied only to `legacy/..` and not to `glob/..`
- Regenerated Pydantic models from updated OpenAPI specification
- Updated import_fail_info_bulk route handler to use ImportFailInfoBulkRequest/Response models
- Replaced manual JSON validation with Pydantic model validation
- Added proper error handling with ValidationError
- Updated data_models/__init__.py to export new models
Following the process outlined in data_models/README.md for type safety and consistency.
* [feat] Add bulk import failure info API endpoint
- Add import_fail_info_bulk endpoint to both glob and legacy manager servers
- Supports bulk processing of cnr_ids and urls arrays in single request
- Maintains same error handling pattern as original import_fail_info API
- Reduces API calls from N to 1 for conflict detection optimization
- Validates input parameters and provides proper error responses
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* modified: remove manager button completely. Now, even when using the legacy UI, it must always be accessed through the menu.
* chore(api): Add temporary cache reload for import_fail_info_bulk
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Dr.Lt.Data <dr.lt.data@gmail.com>
- Strengthened the default security policy
- Subdivided the risky levels high and middle into high+, high, middle+, and middle
- Added support for personal_cloud network mode
- Updated README.md
fixed: invalid security message
fixed: legacy - crash when security policy violation occurred
modified: default 'use_uv' is now True
- Added query parameter models to OpenAPI spec for GET endpoints
- Regenerated data models to include new query param models
- Replaced manual validation with Pydantic model validation
- Removed obsolete validate_required_params helper function
- Provides better error messages and type safety for API endpoints
Co-Authored-By: Claude <noreply@anthropic.com>
- Removed do_update_all function that was never called and only returned an error
- Removed "update-all" from OperationType enum as it's no longer used
- Regenerated data models to reflect the enum change
The update_all functionality now properly creates individual update tasks through the API endpoint rather than being a single monolithic task.
Co-Authored-By: Claude <noreply@anthropic.com>
- Add SecurityLevel and RiskLevel enums to generated models
- Enhance ComfyUISystemState with additional system information fields:
- comfyui_root_path: ComfyUI installation directory
- model_paths: Map of model types to configured paths
- manager_version: ComfyUI Manager version
- security_level: Current security configuration
- network_mode: Network mode (online/offline/private)
- cli_args: Selected CLI arguments
- custom_nodes_count: Total number of custom nodes
- failed_imports: List of failed imports
- pip_packages: Installed pip packages
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix async/sync mismatch in TaskQueue worker implementation
- Use threading.Thread with asyncio.run() as originally designed
- Remove incorrect async task approach that caused blocking issues
- TaskQueue now properly manages its own thread lifecycle
- Resolves WebSocket message delivery and task processing issues
- Updated generated_models.py to reflect OpenAPI 3.1 nullable format changes
- Models now use Optional[type] instead of nullable: true
- All affected models regenerated with datamodel-codegen
- Syntax and linting checks pass
- Add proper async worker management to TaskQueue class
- Remove redundant task_worker_thread and task_worker_lock global variables
- Replace manual threading with async task management
- Update is_processing() logic to use TaskQueue state instead of thread status
- Implement automatic worker cleanup when queue processing completes
- Simplify queue start endpoint to use TaskQueue.start_worker()
- Eliminate TaskQueue.ExecutionStatus NamedTuple in favor of generated TaskExecutionStatus Pydantic model
- Remove manual conversion logic between NamedTuple and Pydantic model
- Use single source of truth for task execution status
- Clean up unused imports (Literal, NamedTuple)
- Maintain consistent data model usage throughout TaskQueue
