Enhance entity extraction with better structured prompts:
- Reorganize prompt format for improved clarity and consistency
- Add XML-style formatting tags for better LLM parsing
- Include language parameter in keywords extraction cache key
- Fix language parameter usage in keywords_extraction prompt
Improve rerank module with chunking fixes:
- Fix top_n behavior to limit documents instead of chunks
- Add Cohere reranker support with proper chunking
- Improve error handling for rerank API responses
Update operate.py:
- Better entity extraction parsing and validation
- Improved cache key generation for multilingual support
Add S3 storage client and API routes for document management:
- Implement s3_routes.py with file upload, download, delete endpoints
- Enhance s3_client.py with improved error handling and operations
- Add S3 browser UI component with file viewing and management
- Implement FileViewer and PDFViewer components for storage preview
- Add Resizable and Sheet UI components for layout control
Update backend infrastructure:
- Add bulk operations and parameterized queries to postgres_impl.py
- Enhance document routes with improved type hints
- Update API server registration for new S3 routes
- Refine upload routes and utility functions
Modernize web UI:
- Integrate S3 browser into main application layout
- Update localization files for storage UI strings
- Add storage settings to application configuration
- Sync package dependencies and lock files
Remove obsolete reproduction script:
- Delete reproduce_citation.py (replaced by test suite)
Update configuration:
- Enhance pyrightconfig.json for stricter type checking
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
- Implement bulk upsert_nodes/edges via UNWIND reducing round trips
- Add health_check for graph connectivity and AGE catalog status
- Switch to parameterized queries preventing Cypher injection
- Fix node ID sanitization: strip control chars, escape quotes
Add citation tracking and display system across backend and frontend components.
Backend changes include citation.py for document attribution, enhanced query routes
with citation metadata, improved prompt templates, and PostgreSQL schema updates.
Frontend includes CitationMarker component, HoverCard UI, QuerySettings refinements,
and ChatMessage enhancements for displaying document sources. Update dependencies
and docker-compose test configuration for improved development workflow.
Graph Connectivity Awareness:
- Add db_degree property to all KG implementations (NetworkX, Postgres, Neo4j, Mongo, Memgraph)
- Show database degree vs visual degree in node panel with amber badge
- Add visual indicator (amber border) for nodes with hidden connections
- Add "Load X hidden connection(s)" button to expand hidden neighbors
- Add configurable "Expand Depth" setting (1-5) in graph settings
- Use global maxNodes setting for node expansion consistency
Orphan Connection UI:
- Add OrphanConnectionDialog component for manual orphan entity connection
- Add OrphanConnectionControl button in graph sidebar
- Expose /graph/orphans/connect API endpoint for frontend use
Backend Improvements:
- Add get_orphan_entities() and connect_orphan_entities() to base storage
- Add orphan connection configuration parameters
- Improve entity extraction with relationship density requirements
Frontend:
- Add graphExpandDepth and graphIncludeOrphans to settings store
- Add min_degree and include_orphans graph filtering parameters
- Update translations (en.json, zh.json)
Add comprehensive E2E testing infrastructure with PostgreSQL performance tuning,
Gunicorn multi-worker support, and evaluation scripts for RAGAS-based quality
assessment. Introduces 4 new evaluation utilities: compare_results.py for A/B test
analysis, download_wikipedia.py for reproducible test datasets, e2e_test_harness.py
for automated evaluation pipelines, and ingest_test_docs.py for batch document
ingestion. Updates docker-compose.test.yml with aggressive async settings, memory
limits, and optimized chunking parameters. Parallelize entity summarization in
operate.py for improved extraction performance. Fix typos in merge node/edge logs.
- Add EMBEDDING_TOKEN_LIMIT env var
- Set max_token_size on embedding func
- Add token limit property to LightRAG
- Validate summary length vs limit
- Log warning when limit exceeded
- Rename _build_llm_context to _build_context_str
- Change text_units_context to chunks_context
- Move string building before early return
- Update log messages and comments
- Consistent variable naming throughout
• Sort src/tgt for consistent ordering
• Create missing nodes before edges
• Update entity chunks storage
• Pass entity_vdb to rebuild function
• Ensure entities exist in all storages
- 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
