Add extensive test suites for API routes and utilities:
- Implement test_search_routes.py (406 lines) for search endpoint validation
- Implement test_upload_routes.py (724 lines) for document upload workflows
- Implement test_s3_client.py (618 lines) for S3 storage operations
- Implement test_citation_utils.py (352 lines) for citation extraction
- Implement test_chunking.py (216 lines) for text chunking validation
Add S3 storage client implementation:
- Create lightrag/storage/s3_client.py with S3 operations
- Add storage module initialization with exports
- Integrate S3 client with document upload handling
Enhance API routes and core functionality:
- Add search_routes.py with full-text and graph search endpoints
- Add upload_routes.py with multipart document upload support
- Update operate.py with bulk operations and health checks
- Enhance postgres_impl.py with bulk upsert and parameterized queries
- Update lightrag_server.py to register new API routes
- Improve utils.py with citation and formatting utilities
Update dependencies and configuration:
- Add S3 and test dependencies to pyproject.toml
- Update docker-compose.test.yml for testing environment
- Sync uv.lock with new dependencies
Apply code quality improvements across all modified files:
- Add type hints to function signatures
- Update imports and router initialization
- Fix logging and error handling
Add comprehensive test suites for prompt evaluation:
- test_prompt_accuracy.py: 365 lines testing prompt extraction accuracy
- test_prompt_quality_deep.py: 672 lines for deep quality analysis
- Refactor prompt.py to consolidate optimized variants (removed prompt_optimized.py)
- Apply ruff formatting and type hints across 30 files
- Update pyrightconfig.json for static type checking
- Modernize reproduce scripts and examples with improved type annotations
- Sync uv.lock dependencies
Format entire codebase with ruff and add type hints across all modules:
- Apply ruff formatting to all Python files (121 files, 17K insertions)
- Add type hints to function signatures throughout lightrag core and API
- Update test suite with improved type annotations and docstrings
- Add pyrightconfig.json for static type checking configuration
- Create prompt_optimized.py and test_extraction_prompt_ab.py test files
- Update ruff.toml and .gitignore for improved linting configuration
- Standardize code style across examples, reproduce scripts, and utilities
- Add entity_chunks & relation_chunks storage
- Implement KEEP/FIFO limit strategies
- Update env.example with new settings
- Add migration for chunk tracking data
- Support all KV storage
- Add get_doc_by_file_path to all storages
- Skip processed files in scan operation
- Check duplicates in upload endpoints
- Check duplicates in text insert APIs
- Return status info in duplicate responses
• Replace pyuca with centralized utils function
• Add pinyin sort keys for file paths
• Update MongoDB indexes with zh collation
• Migrate existing indexes for compatibility
• Support Chinese chars in Redis/JSON storage
• Keep PostgreSQL sorting order controled by Database Collate order
- Add file_path sorting support to all database backends (JSON, Redis, PostgreSQL, MongoDB)
- Implement smart column header switching between "ID" and "File Name" based on display mode
- Add automatic sort field switching when toggling between ID and file name display
- Create composite indexes for workspace+file_path in PostgreSQL and MongoDB for better query performance
- Update frontend to maintain sort state when switching display modes
- Add internationalization support for "fileName" in English and Chinese locales
This enhancement improves user experience by providing intuitive file-based sorting
while maintaining performance through optimized database indexes.
- Add pagination support to BaseDocStatusStorage interface and all implementations (PostgreSQL, MongoDB, Redis, JSON)
- Implement RESTful API endpoints for paginated document queries and status counts
- Create reusable pagination UI components with internationalization support
- Optimize performance with database-level pagination and efficient in-memory processing
- Maintain backward compatibility while adding configurable page sizes (10-200 items)
- Add metadata field to DocProcessingStatus with start_time and end_time tracking
- Record processing timestamps using Unix time format (seconds precision)
- Update all storage backends (JSON, MongoDB, Redis, PostgreSQL) for new field support
- Maintain backward compatibility with default values for existing data
- Add error_msg field for better error tracking during document processing
- The previous implementation of the shared Redis connection pool had a critical issue where any Redis storage instance would disconnect the global shared pool upon closing. This caused `ConnectionError` exceptions for other instances still using the pool.
- This commit resolves the issue by introducing a reference counting mechanism in `RedisConnectionManager`.
Refactored the LLM cache to a flat Key-Value (KV) structure, replacing the previous nested format. The old structure used the 'mode' as a key and stored specific cache content as JSON nested under it. This change significantly enhances cache recall efficiency.
Enhance RedisKVStorage: Implement connection pooling and error handling. Refactor async methods to use context managers for Redis operations, improving resource management and error logging. Batch processing added for key operations to optimize performance.
