- 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.
- Introduced a comprehensive code analysis action template for integrating code exploration and analysis capabilities.
- Added LLM action template for seamless integration of LLM calls with customizable prompts and tools.
- Implemented a benchmark search script to compare multiple search methods across various dimensions including speed, result quality, ranking stability, and coverage.
- Provided preset configurations for common analysis tasks and LLM actions, enhancing usability and flexibility.
Validate working directory path before passing to spawn() to prevent
ENOENT errors when malformed paths are provided. Uses existing
validatePath utility for path validation and existence checks.
- Import validatePath from path-resolver
- Validate cd parameter with mustExist check before use
- Provide clear error message with invalid path details
- Replace auto-complete with AskUserQuestion in execute.md Phase 5
- User can choose "Enter Review" or "Complete Session"
- Fix archived tasks showing incomplete on dashboard
- executeArchive now updates all .task/*.json status to completed
- Add broadcastStreamEvent() for real-time CLI output to Dashboard
- Send CLI_EXECUTION_STARTED/OUTPUT/COMPLETED events via /api/hook
- Add killCurrentCliProcess() to terminate child CLI on SIGINT/SIGTERM
- Track child process reference for cleanup on interruption
- Make CLI stream viewer panel full-height (calc(100vh - 32px))
- Fix completion status not updating by using consistent executionId
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add shared python-utils.ts module for consistent Python detection
- Use `python -m pip` instead of direct pip command (fixes "pip not found")
- Support CCW_PYTHON env var for custom Python path
- Use Windows py launcher to find compatible versions (3.9-3.12)
- Warn users when Python version may not be compatible with onnxruntime
Fixes issues where users couldn't install ccw-litellm due to:
- pip not in PATH
- Only pip3 available (not pip)
- Python 3.13+ without onnxruntime support
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- Add -d/--debug option to ccw cli command
- Enable debug logging at runtime when flag is set
- Change DEBUG check from const to function for runtime evaluation
- Support debug mode for both exec and status subcommands
- Update help text to include --debug option
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- Add debugLog and errorLog utility functions with DEBUG env control
- Add logging for tool availability check (TOOL_CHECK)
- Add logging for command building (BUILD_CMD)
- Add logging for process spawn (SPAWN, STDIN)
- Add logging for process completion (CLOSE, STATUS)
- Enhance error output with command details, exit code, and stderr
- Add troubleshooting hints for common failures
- Support DEBUG=true or CCW_DEBUG=true environment variables
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added integration tests for adaptive RRF weights in hybrid search.
- Enhanced query intent detection with new classifications: keyword, semantic, and mixed.
- Introduced symbol boosting in search results based on explicit symbol matches.
- Implemented embedding-based reranking with configurable options.
- Added global symbol index for efficient symbol lookups across projects.
- Improved file deletion handling on Windows to avoid permission errors.
- Updated chunk configuration to increase overlap for better context.
- Modified package.json test script to target specific test files.
- Created comprehensive writing style guidelines for documentation.
- Added TypeScript tests for query intent detection and adaptive weights.
- Established performance benchmarks for global symbol indexing.
- Phase 3: Added Mermaid diagram generation for system architecture, function modules, algorithms, class diagrams, sequence diagrams, and error flows.
- Phase 4: Assembled analysis and diagrams into a structured CPCC-compliant document with section templates and figure numbering.
- Phase 5: Developed compliance review process with iterative refinement based on analysis findings and user feedback.
- Added CPCC compliance requirements and quality standards for project analysis reports.
- Established a comprehensive project analysis skill with detailed execution flow and report types.
- Enhanced error handling and recovery mechanisms throughout the analysis phases.
- Introduced a `stream` parameter to control output streaming vs. caching.
- Enhanced status determination logic to prioritize valid output over exit codes.
- Updated output structure to include full stdout and stderr when not streaming.
feat(cli-history-store): extend conversation turn schema and migration
- Added `cached`, `stdout_full`, and `stderr_full` fields to the conversation turn schema.
- Implemented database migration to add new columns if they do not exist.
- Updated upsert logic to handle new fields.
feat(codex-lens): implement global symbol index for fast lookups
- Created `GlobalSymbolIndex` class to manage project-wide symbol indexing.
- Added methods for adding, updating, and deleting symbols in the global index.
- Integrated global index updates into directory indexing processes.
feat(codex-lens): optimize search functionality with global index
- Enhanced `ChainSearchEngine` to utilize the global symbol index for faster searches.
- Added configuration option to enable/disable global symbol indexing.
- Updated tests to validate global index functionality and performance.
- Added search limit, content length, and extra files input fields in the CodexLens manager UI.
- Updated API request parameters to include new fields: max_content_length and extra_files_count.
- Refactored smart-search.ts to support new parameters with default values.
- Implemented result splitting logic to return both full content and additional file paths.
- Updated CLI commands to remove worker limits and allow dynamic scaling based on endpoint count.
- Introduced EmbeddingPoolConfig for improved embedding management and auto-discovery of providers.
- Enhanced search engines to utilize new parameters for fuzzy and exact searches.
- Added support for embedding single texts in the LiteLLM embedder.
- 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.
- Create ccw-litellm Python package with AbstractEmbedder and AbstractLLMClient interfaces
- Add BaseEmbedder abstraction and factory pattern to codex-lens for pluggable backends
- Implement API Settings dashboard page for provider credentials and custom endpoints
- Add REST API routes for CRUD operations on providers and endpoints
- Extend CLI with --model parameter for custom endpoint routing
- Integrate existing context-cache for @pattern file resolution
- Add provider model registry with predefined models per provider type
- Include i18n translations (en/zh) for all new UI elements
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add context_cache MCP tool for caching files by @patterns:
- pattern-parser.ts: Parse @expressions using glob
- context-cache-store.ts: In-memory cache with TTL/LRU
- context-cache.ts: MCP tool with pack/read/status/release/cleanup
Simplify CLI cache options:
- --cache now uses comma-separated format instead of JSON
- Items starting with @ are patterns, others are text content
- Add --inject-mode option (none/full/progressive)
- Default: codex=full, gemini/qwen=none
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- 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.
- Updated the Chunker class to adjust the window movement logic, ensuring proper handling of overlap lines.
- Introduced a new smart search tool with features including intent classification, CodexLens integration, multi-backend search routing, and index status checking.
- Implemented various search modes (auto, hybrid, exact, ripgrep, priority) with detailed metadata and error handling.
- Added support for progress tracking during index initialization and enhanced output transformation based on user-defined modes.
- Included comprehensive documentation for usage and parameters in the smart search tool.
- Add SQLite table and CRUD methods for tracking update history
- Create freshness calculation service based on git file changes
- Add API endpoints for freshness data, marking updates, and history
- Display freshness badges in file tree (green/yellow/red indicators)
- Show freshness gauge and details in metadata panel
- Auto-mark files as updated after CLI sync
- Add English and Chinese i18n translations
Freshness algorithm: 100 - min((changedFilesCount / 20) * 100, 100)
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
