# Task Log: LightRAG Documentation Creation **Date**: 2025-01-21 **Mode**: beastmode-chatmode **Task**: Create comprehensive SOTA documentation for LightRAG workspace --- ## Actions - Explored entire LightRAG codebase structure (`lightrag/`, `kg/`, `llm/`, `api/`, `models/`, `services/`) - Read core modules: `lightrag.py` (3401 lines), `base.py` (944 lines), `operate.py` (4230 lines), `prompt.py`, `constants.py` - Analyzed all 20+ storage implementations in `kg/` directory - Reviewed all 16 LLM provider integrations in `llm/` directory - Examined Docker, docker-compose, and K8s deployment configurations - Created 9 comprehensive documentation files in `docs/` directory --- ## Documents Created | File | Description | Lines | |------|-------------|-------| | `README.md` | Main documentation index with navigation | ~200 | | `0001-quick-start.md` | Getting started guide | ~250 | | `0002-architecture-overview.md` | System architecture with ASCII diagrams | ~500 | | `0003-api-reference.md` | Complete REST API documentation | ~600 | | `0004-storage-backends.md` | All 15+ storage backend configurations | ~700 | | `0005-llm-integration.md` | 13+ LLM provider integrations | ~600 | | `0006-deployment-guide.md` | Docker, K8s, and local deployment | ~500 | | `0007-configuration-reference.md` | All environment variables and options | ~550 | | `0008-multi-tenancy.md` | Tenant isolation and RBAC guide | ~450 | --- ## Decisions - Used ASCII art diagrams instead of Mermaid for maximum compatibility across viewers - Organized documents numerically (0001-0008) for clear ordering - Included ERD-style diagrams showing entity relationships - Created dense, actionable tables for quick reference - Linked all documents together with cross-references --- ## Key Components Documented ### Storage Backends - **KV**: JsonKVStorage, RedisKVStorage, PGKVStorage, MongoKVStorage - **Vector**: NanoVectorDBStorage, PGVectorStorage, MilvusVectorDBStorage, QdrantStorage, FAISSStorage, RedisVectorStorage, MongoDBVectorStorage - **Graph**: NetworkXStorage, Neo4JStorage, PGGraphStorage, AGEStorage, MemgraphStorage, GremlinStorage ### LLM Providers - OpenAI, Anthropic, Ollama, Azure OpenAI, AWS Bedrock, HuggingFace, Jina, SiliconCloud, ZhiPu, NVIDIA, LoLLMs, LMDeploy ### Query Modes - naive, local, global, hybrid, mix, bypass --- ## Next Steps - Consider adding examples directory documentation - Add troubleshooting section to deployment guide - Create contribution guidelines - Add performance tuning guide --- ## Lessons/Insights - LightRAG has a highly modular architecture with pluggable storage backends - Multi-tenancy is implemented via TenantRAGManager with LRU caching - The system supports 15+ storage backends and 13+ LLM providers - Configuration follows a layered approach: CLI > ENV > .env > defaults - The codebase is well-structured with clear separation of concerns --- **Total Documentation**: ~4,350 lines across 9 files