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LightRAG/docs/README.md
Raphael MANSUY 2b292d4924
docs: Enterprise Edition & Multi-tenancy attribution (#5) 
* Remove outdated documentation files: Quick Start Guide, Apache AGE Analysis, and Scratchpad.

* Add multi-tenant testing strategy and ADR index documentation

- Introduced ADR 008 detailing the multi-tenant testing strategy for the ./starter environment, covering compatibility and multi-tenant modes, testing scenarios, and implementation details.
- Created a comprehensive ADR index (README.md) summarizing all architecture decision records related to the multi-tenant implementation, including purpose, key sections, and reading paths for different roles.

* feat(docs): Add comprehensive multi-tenancy guide and README for LightRAG Enterprise

- Introduced `0008-multi-tenancy.md` detailing multi-tenancy architecture, key concepts, roles, permissions, configuration, and API endpoints.
- Created `README.md` as the main documentation index, outlining features, quick start, system overview, and deployment options.
- Documented the LightRAG architecture, storage backends, LLM integrations, and query modes.
- Established a task log (`2025-01-21-lightrag-documentation-log.md`) summarizing documentation creation actions, decisions, and insights.
2025-12-04 18:09:15 +08:00

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# LightRAG Enterprise Documentation
**Version 2.0.0-enterprise** | Graph-Enhanced Retrieval-Augmented Generation
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║ ENTERPRISE EDITION ║
║ Simple and Fast Graph-Enhanced RAG System ║
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```
> **🔱 Fork Project** | This is an enterprise-ready fork of [LightRAG](https://github.com/HKUDS/LightRAG) by [Raphaël MANSUY](https://www.elitizon.com/).
>
> **Goal**: Create an enterprise-ready version of LightRAG with production-grade features.
>
> **First Enterprise Feature**: ✅ Multi-tenancy support with RBAC, tenant isolation, and knowledge base management.
---
## Documentation Overview
| Document | Description |
|----------|-------------|
| [Quick Start](0001-quick-start.md) | Get up and running in 5 minutes |
| [Architecture Overview](0002-architecture-overview.md) | System design, data flow, and core concepts |
| [API Reference](0003-api-reference.md) | Complete REST API documentation |
| [Storage Backends](0004-storage-backends.md) | Configure KV, vector, and graph storage |
| [LLM Integration](0005-llm-integration.md) | LLM providers and embedding models |
| [Deployment Guide](0006-deployment-guide.md) | Docker, Kubernetes, and production setup |
| [Configuration Reference](0007-configuration-reference.md) | All environment variables and options |
| [Multi-Tenancy](0008-multi-tenancy.md) | Tenant isolation and RBAC |
---
## Quick Links
### Getting Started
```bash
# Install
pip install lightrag-hku
# Start server
export OPENAI_API_KEY=sk-xxx
python -m lightrag.api.lightrag_server
```
### Python Usage
```python
from lightrag import LightRAG, QueryParam
rag = LightRAG(working_dir="./rag_storage")
await rag.ainsert("Your document text...")
result = await rag.aquery("Your question?", param=QueryParam(mode="hybrid"))
```
### REST API
```bash
# Insert document
curl -X POST http://localhost:9621/documents/text \
-H "Content-Type: application/json" \
-d '{"text": "Document content..."}'
# Query
curl -X POST http://localhost:9621/query \
-H "Content-Type: application/json" \
-d '{"query": "Your question?", "mode": "hybrid"}'
```
### Docker
```bash
docker run -p 9621:9621 -e OPENAI_API_KEY=sk-xxx ghcr.io/hkuds/lightrag:latest
```
---
## System Overview
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ LightRAG │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ Documents ──▶ Chunking ──▶ Entity Extraction ──▶ Knowledge Graph │
│ │ │ │
│ ▼ ▼ │
│ Embeddings ──────────────────────▶ Hybrid Retrieval │
│ │ │
│ ▼ │
│ Query ──▶ LLM Generation ──▶ Response │
│ │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ Storage Backends: │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ KV Storage │ │ Vector Store │ │ Graph Store │ │
│ │ JSON/Redis/ │ │ NanoVectorDB │ │ NetworkX/ │ │
│ │ PostgreSQL/ │ │ pgvector/ │ │ Neo4j/AGE/ │ │
│ │ MongoDB │ │ Milvus/FAISS │ │ Memgraph │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │
│ LLM Providers: │
│ OpenAI │ Anthropic │ Ollama │ Azure │ Bedrock │ HuggingFace │ ... │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
## Query Modes
| Mode | Description | Best For |
|------|-------------|----------|
| `naive` | Basic vector similarity search | Simple lookups |
| `local` | Entity-focused retrieval | Specific facts |
| `global` | High-level community summaries | Broad questions |
| `hybrid` | Combined local + global | Balanced queries |
| `mix` | Full KG + vector integration | Complex reasoning |
---
## Deployment Options
| Option | Use Case | Guide |
|--------|----------|-------|
| **Local** | Development | `pip install lightrag-hku` |
| **Docker** | Staging/Production | [Docker Guide](0006-deployment-guide.md#2-docker-deployment) |
| **Kubernetes** | Production/Scale | [K8s Guide](0006-deployment-guide.md#3-kubernetes-deployment-helm) |
### Storage Topology
| Environment | KV | Vector | Graph |
|-------------|-----|--------|-------|
| Development | JSON | NanoVectorDB | NetworkX |
| Production | PostgreSQL | pgvector | Neo4j |
| High-Scale | Redis | Milvus | Neo4j |
---
## Configuration Quick Reference
### Essential Environment Variables
```bash
# LLM
LLM_BINDING=openai
LLM_MODEL=gpt-4o-mini
OPENAI_API_KEY=sk-xxx
# Embedding
EMBEDDING_BINDING=openai
EMBEDDING_MODEL=text-embedding-ada-002
EMBEDDING_DIM=1536
# Storage
LIGHTRAG_KV_STORAGE=JsonKVStorage
LIGHTRAG_VECTOR_STORAGE=NanoVectorDBStorage
LIGHTRAG_GRAPH_STORAGE=NetworkXStorage
# Server
PORT=9621
```
See [Configuration Reference](0007-configuration-reference.md) for all options.
---
## Feature Highlights
### Knowledge Graph Integration
```
┌────────────────────────────────────────────────────┐
│ KNOWLEDGE GRAPH │
│ │
│ [Person: Einstein] ─────developed──────▶ │
│ │ │ │
│ born_in [Theory: │
│ │ Relativity] │
│ ▼ │ │
│ [Location: Germany] describes_│ │
│ ▼ │
│ [Concept: │
│ Spacetime] │
└────────────────────────────────────────────────────┘
```
### Multi-Tenant Isolation
```
Tenant A Tenant B Tenant C
│ │ │
▼ ▼ ▼
┌────────┐ ┌────────┐ ┌────────┐
│ KB-1 │ │ KB-1 │ │ KB-1 │
│ KB-2 │ │ KB-2 │ └────────┘
│ KB-3 │ └────────┘
└────────┘
```
---
## Resources
### Enterprise Fork
- **GitHub (Enterprise)**: https://github.com/raphaelmansuy/LightRAG
- **Author**: [Raphaël MANSUY](https://www.elitizon.com/) - Elitizon
- **Issues**: https://github.com/raphaelmansuy/LightRAG/issues
### Original Project
- **GitHub (Original)**: https://github.com/HKUDS/LightRAG
- **PyPI**: https://pypi.org/project/lightrag-hku/
---
## Document Index
1. **[Quick Start Guide](0001-quick-start.md)**
- Installation options
- Python SDK basics
- REST API basics
- Common patterns
2. **[Architecture Overview](0002-architecture-overview.md)**
- System design diagrams
- Core concepts (entities, relations, chunks)
- Data flow pipeline
- Query execution flow
3. **[API Reference](0003-api-reference.md)**
- Document endpoints
- Query endpoints
- Graph endpoints
- Admin endpoints
4. **[Storage Backends](0004-storage-backends.md)**
- KV storage options
- Vector storage options
- Graph storage options
- Configuration tables
5. **[LLM Integration](0005-llm-integration.md)**
- Provider configurations
- Embedding models
- Reranking options
- Custom implementations
6. **[Deployment Guide](0006-deployment-guide.md)**
- Local development
- Docker deployment
- Kubernetes/Helm
- Production best practices
7. **[Configuration Reference](0007-configuration-reference.md)**
- Environment variables
- CLI arguments
- QueryParam options
- Complete .env example
8. **[Multi-Tenancy Guide](0008-multi-tenancy.md)**
- Tenant isolation
- RBAC roles/permissions
- TenantRAGManager
- API endpoints
---
*Original LightRAG built with ❤️ by [HKUDS](https://github.com/HKUDS)*
*Enterprise Edition maintained by [Raphaël MANSUY](https://www.elitizon.com/) @ Elitizon*
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