- Introduced functions to load and toggle CLI wrapper endpoints from the API.
- Updated the CLI manager UI to display and manage CLI wrapper endpoints.
- Removed CodexLens and Semantic Search from the tools section, now managed in their dedicated pages.
feat(codexlens-manager): move File Watcher card to the CodexLens Manager page
- Relocated the File Watcher card from the right column to the main content area of the CodexLens Manager page.
refactor(claude-cli-tools): enhance CLI tools configuration and migration
- Added support for new tool types: 'cli-wrapper' and 'api-endpoint'.
- Updated migration logic to handle new tool types and preserve endpoint IDs.
- Deprecated previous custom endpoint handling in favor of the new structure.
feat(cli-executor-core): integrate CLI settings for custom endpoint execution
- Implemented execution logic for custom CLI封装 endpoints using settings files.
- Enhanced error handling and output logging for CLI executions.
- Updated tool identification logic to support both built-in tools and custom endpoints.
- Implemented `model-download-custom` command to download HuggingFace models.
- Added support for discovering manually placed models in the cache.
- Enhanced the model list view to display recommended and discovered models separately.
- Introduced JSON editor for direct configuration mode in API settings.
- Added validation and formatting features for JSON input.
- Updated translations for new API settings and common actions.
- Improved user interface for model management, including action buttons and tooltips.
- Updated `claude-cli-tools.ts` to support new model configurations and migration from older versions.
- Added `getPredefinedModels` and `getAllPredefinedModels` functions for better model management.
- Deprecated `cli-config-manager.ts` in favor of `claude-cli-tools.ts`, maintaining backward compatibility.
- Introduced `skill-context-loader.ts` to handle skill context loading based on user prompts and keywords.
- Enhanced tool configuration functions to include secondary models and improved migration logic.
- Updated index file to register the new skill context loader tool.
- Added a function to parse JSON streaming content in core-memory.js, extracting readable text from messages.
- Updated memory detail view to utilize the new parsing function for content and summary.
- Introduced an enableReview option in rules-manager.js, allowing users to toggle review functionality in rule creation.
- Simplified skill creation modal in skills-manager.js by removing generation type selection UI.
- Improved CLI executor to handle tool calls for file writing, ensuring proper output parsing.
- Adjusted CLI command tests to set timeout to 0 for immediate execution.
- Updated file watcher to implement a true debounce mechanism and added a pending queue status for UI updates.
- Enhanced watcher manager to handle queue changes and provide JSON output for better integration with TypeScript backend.
- Established TypeScript naming conventions documentation to standardize code style across the project.
- Introduced best practices requirements specification covering code quality, performance, maintainability, error handling, and documentation standards.
- Established quality standards with overall quality metrics and mandatory checks for security, code quality, performance, and maintainability.
- Created security requirements specification aligned with OWASP Top 10 and CWE Top 25, detailing checks and patterns for common vulnerabilities.
- Developed templates for documenting best practice findings, security findings, and generating reports, including structured markdown and JSON formats.
- Updated dependencies in the project, ensuring compatibility and stability.
- Added test files and README documentation for vector indexing tests.
- Updated Windows platform guidelines for path formats and Bash rules.
- Refactored CodexLens routes to improve GPU detection and indexing cancellation logic.
- Added FastEmbed installation status handling in the dashboard, including UI updates for installation and reinstallation options.
- Implemented local model management with improved API responses for downloaded models.
- Enhanced GPU selection logic in the model mode configuration.
- Improved error handling and user feedback for FastEmbed installation processes.
- Adjusted Python environment checks to avoid shell escaping issues on Windows.
- Implemented CLI commands for listing, downloading, deleting, and retrieving information about reranker models.
- Enhanced the dashboard UI to support embedding and reranker configurations with internationalization.
- Updated environment variable management for embedding and reranker settings.
- Added functionality to dynamically update model options based on selected backend.
- Improved user experience with status indicators and action buttons for model management.
- Integrated new reranker models with detailed metadata and recommendations.
- Added `rerankerModels` property to the `ProviderCredential` interface in `litellm-api-config.ts` to support additional reranker configurations.
- Introduced a numerically stable sigmoid function in `FastEmbedReranker` for score normalization.
- Updated the scoring logic in `FastEmbedReranker` to use raw float scores from the encoder and normalize them using the new sigmoid function.
- Adjusted the result mapping to maintain original document order while applying normalization.
- Added `splade_encoder.py` for ONNX-optimized SPLADE encoding, including methods for encoding text and batch processing.
- Created `SPLADE_IMPLEMENTATION.md` to document the SPLADE encoder's functionality, design patterns, and integration points.
- Introduced migration script `migration_009_add_splade.py` to add SPLADE metadata and posting list tables to the database.
- Developed `splade_index.py` for managing the SPLADE inverted index, supporting efficient sparse vector retrieval.
- Added verification script `verify_watcher.py` to test FileWatcher event filtering and debouncing functionality.
- Simplify rotation section to show status only
- Add link to navigate to API Settings Embedding Pool
- Update loadRotationStatus to read from embedding-pool API
- Remove detailed modal in favor of API Settings config
- Add i18n translations for 'Configure in API Settings'
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Architecture refactoring for multi-provider rotation:
Backend:
- Add EmbeddingPoolConfig type with autoDiscover support
- Implement discoverProvidersForModel() for auto-aggregation
- Add GET/PUT /api/litellm-api/embedding-pool endpoints
- Add GET /api/litellm-api/embedding-pool/discover/:model preview
- Convert ccw-litellm status check to async with 5-min cache
- Maintain backward compatibility with legacy rotation config
Frontend:
- Add "Embedding Pool" tab in API Settings
- Auto-discover providers when target model selected
- Show provider/key count with include/exclude controls
- Increase sidebar width (280px → 320px)
- Add sync result feedback on save
Other:
- Remove worker count limits (was max=32)
- Add i18n translations (EN/CN)
- Update .gitignore for .mcp.json
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added functions to get and update CodexLens embedding rotation configuration.
- Introduced functionality to retrieve enabled embedding providers for rotation.
- Created endpoints for managing rotation configuration via API.
- Enhanced dashboard UI to support multi-provider rotation configuration.
- Updated internationalization strings for new rotation features.
- Adjusted CLI commands and embedding manager to support increased concurrency limits.
- Modified hybrid search weights for improved ranking behavior.
- Added token estimation and batching functionality in LiteLLMEmbedder to handle large text inputs efficiently.
- Updated embed method to support max_tokens_per_batch parameter for better API call management.
- Introduced new API routes for managing custom CLI endpoints, including GET, POST, PUT, and DELETE methods.
- Enhanced CLI history component to support source directory context for native session content.
- Improved error handling and logging in various components for better debugging and user feedback.
- Added internationalization support for new API endpoint features in the i18n module.
- Updated CodexLens CLI commands to allow for concurrent API calls with a max_workers option.
- Enhanced embedding manager to track model information and handle embeddings generation more robustly.
- Added entry points for CLI commands in the package configuration.
- Added JSON-based settings management in Config class for embedding and LLM configurations.
- Introduced methods to save and load settings from a JSON file.
- Updated BaseEmbedder and its subclasses to include max_tokens property for better token management.
- Enhanced chunking strategy to support recursive splitting of large symbols with improved overlap handling.
- Implemented comprehensive tests for recursive splitting and chunking behavior.
- Added CLI tools configuration management for better integration with external tools.
- Introduced a new command for compacting session memory into structured text for recovery.
- Updated embedding_manager.py to include backend parameter in model configuration.
- Modified model_manager.py to utilize cache_name for ONNX models.
- Refactored hybrid_search.py to improve embedder initialization based on backend type.
- Added backend column to vector_store.py for better model configuration management.
- Implemented migration for existing database to include backend information.
- Enhanced API settings implementation with comprehensive provider and endpoint management.
- Introduced LiteLLM integration guide detailing configuration and usage.
- Added examples for LiteLLM usage in TypeScript.
- Introduced a new CodexLens Manager item in the dashboard for easier access.
- Implemented GPU management commands in the CLI, including listing available GPUs, selecting a specific GPU, and resetting to automatic detection.
- Enhanced the embedding generation process to utilize GPU resources more effectively, including batch size optimization for better performance.
- Updated the embedder to support device ID options for GPU selection, ensuring compatibility with DirectML and CUDA.
- Added detailed logging and error handling for GPU detection and selection processes.
- Updated package version to 6.2.9 and added comprehensive documentation for Codex Agent Execution Protocol.
- Added accelerator and providers fields to SemanticStatus interface.
- Updated checkSemanticStatus function to retrieve ONNX providers and accelerator type.
- Introduced detectGpuSupport function to identify available GPU modes (CUDA, DirectML).
- Modified installSemantic function to support GPU acceleration modes and clean up ONNX Runtime installations.
- Updated package requirements in PKG-INFO for semantic-gpu and semantic-directml extras.
- Added new source files for GPU support and enrichment functionalities.
- Updated tests to cover new features and ensure comprehensive testing.
