Adds robust exception handling for os.path.commonpath() in search_symbols()
to prevent crashes on malformed paths and Windows cross-drive scenarios.
Invalid symbols are skipped with debug logging, search continues.
Solution-ID: SOL-1735385400004
Issue-ID: ISS-1766921318981-4
Task-ID: T1
Add fallback validation to detect dead threads missed by
threading.enumerate(), ensuring all stale connections are cleaned.
Solution-ID: SOL-1735392000002
Issue-ID: ISS-1766921318981-3
Task-ID: T2
Protect fast path cache read in get_embedder() to prevent KeyError
during concurrent access and cache clearing operations.
Solution-ID: SOL-1735392000001
Issue-ID: ISS-1766921318981-2
Task-ID: T1
Adds case normalization for path comparison on Windows to handle
case-insensitive filesystem behavior. Preserves case-sensitivity on Unix.
Fixes: ISS-1766921318981-13
Solution-ID: SOL-1735386000-13
Issue-ID: ISS-1766921318981-13
Task-ID: T1
Define module-level EPSILON constant and use it in both
_cosine_similarity and _refresh_cache for consistent
floating point precision handling.
Solution-ID: SOL-20251228113619
Issue-ID: ISS-1766921318981-11
Task-ID: T3
Add comprehensive test coverage for near-zero norms, product
underflow, and floating point precision edge cases in
_cosine_similarity function.
Solution-ID: SOL-20251228113619
Issue-ID: ISS-1766921318981-11
Task-ID: T2
Replace exact zero comparison with epsilon-based check (< 1e-10)
in _cosine_similarity to handle floating point precision issues.
Also check for product underflow to prevent inf/nan from division
by very small numbers.
Solution-ID: SOL-20251228113619
Issue-ID: ISS-1766921318981-11
Task-ID: T1
Replaces bare exception handler in load_settings() with logging.warning()
to help users debug configuration file issues (syntax errors, permissions).
Maintains backward compatibility - errors do not break initialization.
Solution-ID: SOL-1735385400001
Issue-ID: ISS-1766921318981-1
Task-ID: T1
Add math.isnan() check before math.isfinite() to properly catch
NaN values in weight totals. Prevents division by NaN which could
produce unexpected results in RRF fusion calculations.
Solution-ID: SOL-20251228113631
Issue-ID: ISS-1766921318981-0
Task-ID: T1
- 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.
- 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.
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
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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.
- 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
🤖 Generated with [Claude Code](https://claude.com/claude-code)
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.
- Fix cli.ts loadPackageInfo() to try root package.json first (../../package.json)
- Add build script and devDependencies to root package.json
- Remove ccw/package.json and ccw/package-lock.json (no longer needed)
- CodexLens: add config.json support for index_dir configuration
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Fix model installation detection using fastembed ONNX cache names
- Add embeddings_config table for model metadata tracking
- Fix hybrid search segfault by using single-threaded GPU mode
- Suppress INFO logs in JSON mode to prevent error display
- Add model dropdown filtering to show only installed models
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- 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)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Updated the dashboard template to hide the Code Graph Explorer feature.
- Enhanced the `executeCodexLens` function to use `exec` for better cross-platform compatibility and improved command execution.
- Changed the default `maxResults` and `limit` parameters in the smart search tool to 10 for better performance.
- Introduced a new `priority` search mode in the smart search tool, replacing the previous `parallel` mode, which now follows a fallback strategy: hybrid -> exact -> ripgrep.
- Optimized the embedding generation process in the embedding manager by batching operations and using a cached embedder instance to reduce model loading overhead.
- Implemented a thread-safe singleton pattern for the embedder to improve performance across multiple searches.
Add functionality to group search results with similar content and scores
into a single representative result with additional locations.
Changes:
- Add AdditionalLocation entity model for storing grouped result locations
- Add additional_locations field to SearchResult for backward compatibility
- Implement group_similar_results() function in ranking.py with:
- Content-based grouping (by excerpt or content field)
- Score-based sub-grouping with configurable threshold
- Metadata preservation with grouped_count tracking
- Add group_results and grouping_threshold options to SearchOptions
- Integrate grouping into ChainSearchEngine.search() after RRF fusion
Test coverage:
- 36 multi-level tests covering unit, boundary, integration, and performance
- Real-world scenario tests for RRF scores and duplicate code detection
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
