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
Fix logging output in evaluation test harness and examples:
- Replace print() statements with logger calls in e2e_test_harness.py
- Update copy_llm_cache_to_another_storage.py to use logger instead of print
- Remove redundant logging configuration in copy_llm_cache_to_another_storage.py
Fix path handling and typos:
- Correct makedirs() call in lightrag_openai_demo.py to create log_dir directly
- Update constants.py comments to clarify SOURCE_IDS_LIMIT_METHOD options
- Remove duplicate return statement in utils.py normalize_extracted_info()
- Fix error string formatting in chroma_impl.py with !s conversion
- Remove unused pipmaster import from chroma_impl.py
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
Improve code quality and test robustness:
- Refactor environment variable parsing in rerank config using centralized get_env_value helper
- Add return type hints to all test methods for better type safety
- Fix patch path in test from lightrag.utils to lightrag.rerank for correct import location
- Clarify batch insert endpoint behavior regarding duplicate content rejection
- Expand .dockerignore to comprehensively exclude node_modules (200MB+), Python cache files, and venv directories
- Update dependency groups: align evaluation and test extras with pytest/pre-commit/ruff tools
- Add KaTeX extensions (mhchem for chemistry, copy-tex for copying)
- Add CASCADE to AGE extension for PostgreSQL
- Remove future dependency, replace passlib with bcrypt
- Fix Jina embedding configuration and provider defaults
- Update gunicorn help text and bump API version to 0258
- Documentation and README updates
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.
Add citation.py module for document citation tracking and management.
Configure Biome and Ruff for consistent code formatting across TypeScript
and Python. Update webui with improved component organization, API client
refactoring, and enhanced user interface patterns. Add formatting configs
and dependency updates for build toolchain optimization.
Add comprehensive test dataset with 7 domain-specific Wikipedia documents
(climate, finance, medical, sports) and corresponding test cases in JSON format.
Total of 2292 lines of test data across 8 files for RAG quality evaluation
and end-to-end testing infrastructure.
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.
Implement automatic orphan entity connection system that identifies entities with
no relationships and creates meaningful connections via vector similarity + LLM
validation. This improves knowledge graph connectivity and retrieval quality.
Changes:
- Add orphan connection configuration parameters (thresholds, cross-connect settings)
- Implement aconnect_orphan_entities() method with 4-step validation pipeline
- Add SQL templates for efficient orphan and candidate entity queries
- Create POST /graph/orphans/connect API endpoint with configurable parameters
- Add orphan connection validation prompt for LLM-based relationship verification
- Include relationship density requirement in extraction prompts to prevent orphans
- Update docker-compose.test.yml with optimized extraction parameters
- Add quality validation test suite (run_quality_tests.py) for retrieval evaluation
- Add unit test framework (test_orphan_connection_quality.py) with test cases
- Enable auto-run of orphan connection after document processing
- Extract PostgreSQL storage check into named variable for clarity
- Move APIRouter initialization into create_table_routes function scope
- Add robust type handling for database query results
- Add input validation for table names and pagination parameters
- Add regex-based SQL injection prevention for table name sanitization
- Improve clipboard copy fallback logic and error handling
- Add memoization for JSON serialization to prevent unnecessary recalculations
- Hide meta column from table explorer UI display
- Sort table columns alphabetically for consistent ordering
- Add keyboard accessibility to status filter buttons
- Add preprocessed status filter to document manager
- Update @tanstack/react-query from 5.60.0 to 5.87.1
- Extract dev storage config into constant to reduce duplication
- Update documentation comments for clarity
- Implemented Table Explorer component to allow users to select and view database tables.
- Added API calls for fetching table list, schema, and paginated data.
- Introduced row detail modal for displaying and copying row data.
- Enhanced DataTable component to support row click events.
- Updated UI components for better user experience and accessibility.
- Added mock data for development mode to facilitate testing.
- Updated localization files to include new terms related to tables.
- Modified settings store to include storage configuration for conditional UI rendering.
- Improved styling and layout for various components to align with new design standards.
- Change build check from error to warning
- Redirect to /docs when WebUI unavailable
- Add webui_available to health endpoint
- Only mount /webui if assets exist
- Return status tuple from build check
Added support for structured output (JSON mode) from the OpenAI API in `openai.py` and `azure_openai.py`.
When `response_format` is used to request structured data, the new logic checks for the `message.parsed` attribute. If it exists, it's serialized into a JSON string as the final content. If not, the code falls back to the existing `message.content` handling, ensuring backward compatibility.
