* Remove outdated documentation files: Quick Start Guide, Apache AGE Analysis, and Scratchpad.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.
536 lines
20 KiB
Markdown
536 lines
20 KiB
Markdown
# LightRAG Configuration Reference
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## Configuration Overview
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```
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┌─────────────────────────────────────────────────────────────────────────────┐
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│ CONFIGURATION LAYERS │
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├─────────────────────────────────────────────────────────────────────────────┤
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│ │
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│ ┌────────────────────────────────────────────────────────────────────────┐ │
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│ │ 1. COMMAND LINE ARGUMENTS (highest priority) │ │
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│ │ python -m lightrag.api.lightrag_server --port 9621 --workers 2 │ │
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│ └────────────────────────────────────────────────────────────────────────┘ │
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│ │ │
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│ ▼ │
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│ ┌────────────────────────────────────────────────────────────────────────┐ │
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│ │ 2. ENVIRONMENT VARIABLES │ │
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│ │ export PORT=9621 │ │
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│ │ export LLM_MODEL=gpt-4o-mini │ │
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│ └────────────────────────────────────────────────────────────────────────┘ │
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│ │ │
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│ ▼ │
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│ ┌────────────────────────────────────────────────────────────────────────┐ │
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│ │ 3. .env FILE │ │
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│ │ LLM_MODEL=gpt-4o-mini │ │
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│ │ EMBEDDING_DIM=1536 │ │
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│ └────────────────────────────────────────────────────────────────────────┘ │
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│ │ │
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│ ▼ │
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│ ┌────────────────────────────────────────────────────────────────────────┐ │
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│ │ 4. PYTHON DATACLASS DEFAULTS (lowest priority) │ │
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│ │ LightRAG(working_dir="./rag_storage") │ │
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│ └────────────────────────────────────────────────────────────────────────┘ │
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│ │
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└─────────────────────────────────────────────────────────────────────────────┘
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```
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---
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## 1. Server Configuration
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### Basic Server Settings
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `HOST` | `--host` | `0.0.0.0` | Server bind address |
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| `PORT` | `--port` | `9621` | Server port |
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| `WORKERS` | `--workers` | `2` | Number of worker processes |
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| `TIMEOUT` | `--timeout` | `300` | Request timeout (seconds) |
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| `WORKING_DIR` | `--working-dir` | `./rag_storage` | RAG storage directory |
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| `INPUT_DIR` | `--input-dir` | `./inputs` | Document input directory |
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### SSL/TLS Configuration
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `SSL` | `--ssl` | `false` | Enable HTTPS |
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| `SSL_CERTFILE` | `--ssl-certfile` | `None` | Path to SSL certificate |
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| `SSL_KEYFILE` | `--ssl-keyfile` | `None` | Path to SSL private key |
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### Logging Configuration
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `LOG_LEVEL` | `--log-level` | `INFO` | Logging level (DEBUG/INFO/WARNING/ERROR/CRITICAL) |
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| `VERBOSE` | `--verbose` | `false` | Enable verbose debug output |
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| `LOG_MAX_BYTES` | — | `10485760` | Max log file size (10MB) |
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| `LOG_BACKUP_COUNT` | — | `5` | Number of log backups |
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| `LOG_FILENAME` | — | `lightrag.log` | Log filename |
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---
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## 2. LLM Configuration
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### Provider Selection
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `LLM_BINDING` | `--llm-binding` | `openai` | LLM provider |
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| `LLM_MODEL` | — | `mistral-nemo:latest` | Model name |
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| `LLM_BINDING_HOST` | — | Provider-specific | API endpoint URL |
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| `LLM_BINDING_API_KEY` | — | `None` | API key |
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**Supported LLM Bindings:**
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- `openai` - OpenAI API (default)
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- `ollama` - Local Ollama
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- `lollms` - LoLLMs server
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- `azure_openai` - Azure OpenAI Service
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- `aws_bedrock` - AWS Bedrock
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- `openai-ollama` - OpenAI LLM + Ollama embeddings
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### Provider-Specific Host Defaults
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| Provider | Default Host |
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|----------|-------------|
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| `openai` | `https://api.openai.com/v1` |
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| `ollama` | `http://localhost:11434` |
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| `lollms` | `http://localhost:9600` |
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| `azure_openai` | `AZURE_OPENAI_ENDPOINT` env |
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### LLM Performance Settings
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `MAX_ASYNC` | `4` | Max concurrent LLM requests |
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| `LLM_TIMEOUT` | `180` | LLM request timeout (seconds) |
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| `ENABLE_LLM_CACHE` | `true` | Enable LLM response caching |
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| `ENABLE_LLM_CACHE_FOR_EXTRACT` | `true` | Cache extraction responses |
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| `TEMPERATURE` | `1.0` | LLM temperature setting |
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### Ollama-Specific Settings
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `OLLAMA_NUM_CTX` | `32768` | Context window size |
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| `OLLAMA_EMULATING_MODEL_NAME` | `lightrag` | Simulated model name |
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| `OLLAMA_EMULATING_MODEL_TAG` | `latest` | Simulated model tag |
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---
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## 3. Embedding Configuration
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### Embedding Provider
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `EMBEDDING_BINDING` | `--embedding-binding` | `openai` | Embedding provider |
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| `EMBEDDING_MODEL` | — | `bge-m3:latest` | Embedding model name |
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| `EMBEDDING_DIM` | — | `1024` | Embedding dimensions |
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| `EMBEDDING_BINDING_HOST` | — | Provider-specific | API endpoint |
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| `EMBEDDING_BINDING_API_KEY` | — | `""` | API key |
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**Supported Embedding Bindings:**
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- `openai` - OpenAI embeddings
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- `ollama` - Local Ollama embeddings
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- `azure_openai` - Azure OpenAI embeddings
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- `aws_bedrock` - AWS Bedrock Titan
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- `jina` - Jina embeddings
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### Embedding Performance
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `EMBEDDING_FUNC_MAX_ASYNC` | `8` | Max concurrent embedding requests |
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| `EMBEDDING_BATCH_NUM` | `10` | Batch size for embeddings |
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| `EMBEDDING_TIMEOUT` | `30` | Embedding request timeout (seconds) |
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---
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## 4. Storage Configuration
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### Storage Backend Selection
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `LIGHTRAG_KV_STORAGE` | `JsonKVStorage` | Key-value storage backend |
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| `LIGHTRAG_VECTOR_STORAGE` | `NanoVectorDBStorage` | Vector storage backend |
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| `LIGHTRAG_GRAPH_STORAGE` | `NetworkXStorage` | Graph storage backend |
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| `LIGHTRAG_DOC_STATUS_STORAGE` | `JsonDocStatusStorage` | Document status storage |
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### Available Storage Backends
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**KV Storage Options:**
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| Value | Use Case |
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|-------|----------|
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| `JsonKVStorage` | Development, file-based |
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| `RedisKVStorage` | Production, distributed |
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| `PGKVStorage` | Production, PostgreSQL |
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| `MongoKVStorage` | Production, MongoDB |
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**Vector Storage Options:**
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| Value | Use Case |
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|-------|----------|
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| `NanoVectorDBStorage` | Development, in-memory |
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| `PGVectorStorage` | Production, PostgreSQL |
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| `MilvusVectorDBStorage` | Production, high-scale |
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| `QdrantStorage` | Production, managed |
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| `FAISSStorage` | Production, local |
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| `RedisVectorStorage` | Production, distributed |
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| `MongoDBVectorStorage` | Production, MongoDB |
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**Graph Storage Options:**
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| Value | Use Case |
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|-------|----------|
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| `NetworkXStorage` | Development, in-memory |
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| `Neo4JStorage` | Production, native graph |
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| `PGGraphStorage` | Production, PostgreSQL |
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| `AGEStorage` | Production, PostgreSQL AGE |
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| `MemgraphStorage` | Production, real-time |
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| `GremlinStorage` | Production, Gremlin-compatible |
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### PostgreSQL Configuration
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `POSTGRES_HOST` | `localhost` | PostgreSQL host |
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| `POSTGRES_PORT` | `5432` | PostgreSQL port |
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| `POSTGRES_USER` | — | Database user |
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| `POSTGRES_PASSWORD` | — | Database password |
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| `POSTGRES_DATABASE` | — | Database name |
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### Neo4j Configuration
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `NEO4J_URI` | `bolt://localhost:7687` | Neo4j connection URI |
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| `NEO4J_USERNAME` | `neo4j` | Neo4j username |
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| `NEO4J_PASSWORD` | — | Neo4j password |
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### Redis Configuration
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `REDIS_URI` | `redis://localhost:6379` | Redis connection URI |
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### Milvus Configuration
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `MILVUS_HOST` | `localhost` | Milvus host |
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| `MILVUS_PORT` | `19530` | Milvus port |
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| `MILVUS_USER` | — | Milvus user |
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| `MILVUS_PASSWORD` | — | Milvus password |
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| `MILVUS_DB_NAME` | `default` | Milvus database |
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---
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## 5. Document Processing Configuration
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### Chunking Settings
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `CHUNK_SIZE` | `1200` | Token size per chunk |
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| `CHUNK_OVERLAP_SIZE` | `100` | Overlap between chunks |
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### Entity Extraction
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `SUMMARY_LANGUAGE` | `English` | Language for summaries |
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| `MAX_GLEANING` | `1` | Entity extraction iterations |
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| `ENTITY_TYPES` | See below | Types of entities to extract |
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**Default Entity Types:**
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```python
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ENTITY_TYPES = [
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"Person", "Creature", "Organization", "Location",
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"Event", "Concept", "Method", "Content",
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"Data", "Artifact", "NaturalObject"
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]
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```
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### Summary Settings
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `SUMMARY_MAX_TOKENS` | `1200` | Max tokens per summary |
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| `SUMMARY_LENGTH_RECOMMENDED` | `600` | Recommended summary length |
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| `SUMMARY_CONTEXT_SIZE` | `12000` | Context window for summarization |
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| `FORCE_LLM_SUMMARY_ON_MERGE` | `8` | Fragment threshold for LLM summary |
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### Document Loader
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `DOCUMENT_LOADING_ENGINE` | `DEFAULT` | Document parser (DEFAULT/DOCLING) |
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---
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## 6. Query Configuration
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### QueryParam Class
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```python
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@dataclass
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class QueryParam:
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mode: str = "mix" # Query mode
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only_need_context: bool = False # Return only context
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only_need_prompt: bool = False # Return only prompt
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response_type: str = "Multiple Paragraphs"
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stream: bool = False # Enable streaming
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top_k: int = 40 # Top results
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chunk_top_k: int = 20 # Top chunks
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max_entity_tokens: int = 6000 # Entity token budget
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max_relation_tokens: int = 8000 # Relation token budget
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max_total_tokens: int = 30000 # Total token budget
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enable_rerank: bool = True # Enable reranking
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include_references: bool = False # Include citations
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```
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### Query Modes
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| Mode | Description | Best For |
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|------|-------------|----------|
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| `naive` | Basic vector search | Simple lookups |
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| `local` | Entity-focused retrieval | Specific entities |
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| `global` | High-level summaries | Broad questions |
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| `hybrid` | Local + Global combined | Balanced queries |
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| `mix` | KG + Vector integration | Complex questions |
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| `bypass` | Skip RAG, direct LLM | Testing |
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### Query Environment Variables
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `TOP_K` | `40` | Top-K entities/relations |
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| `CHUNK_TOP_K` | `20` | Top-K text chunks |
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| `MAX_ENTITY_TOKENS` | `6000` | Entity context budget |
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| `MAX_RELATION_TOKENS` | `8000` | Relation context budget |
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| `MAX_TOTAL_TOKENS` | `30000` | Total context budget |
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| `COSINE_THRESHOLD` | `0.2` | Similarity threshold |
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| `RELATED_CHUNK_NUMBER` | `5` | Related chunks to retrieve |
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| `HISTORY_TURNS` | `0` | Conversation history turns |
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---
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## 7. Reranking Configuration
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `RERANK_BINDING` | `--rerank-binding` | `null` | Rerank provider |
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| `RERANK_MODEL` | — | `None` | Rerank model name |
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| `RERANK_BINDING_HOST` | — | `None` | Rerank API endpoint |
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| `RERANK_BINDING_API_KEY` | — | `None` | Rerank API key |
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| `MIN_RERANK_SCORE` | — | `0.0` | Minimum rerank score |
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| `RERANK_BY_DEFAULT` | — | `true` | Enable reranking by default |
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**Supported Rerank Bindings:**
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- `null` - Disabled
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- `cohere` - Cohere rerank
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- `jina` - Jina rerank
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- `aliyun` - Aliyun rerank
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---
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## 8. Authentication & Security
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### API Authentication
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| Variable | CLI Flag | Default | Description |
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|----------|----------|---------|-------------|
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| `LIGHTRAG_API_KEY` | `--key` | `None` | Simple API key auth |
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| `AUTH_ACCOUNTS` | — | `""` | Format: `user1:pass1,user2:pass2` |
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| `AUTH_USER` | — | `""` | Single username (if AUTH_ACCOUNTS not set) |
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| `AUTH_PASS` | — | `""` | Single password |
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### JWT Configuration
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `TOKEN_SECRET` | `lightrag-jwt-default-secret` | JWT signing secret |
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| `TOKEN_EXPIRE_HOURS` | `48` | Token expiration (hours) |
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| `GUEST_TOKEN_EXPIRE_HOURS` | `24` | Guest token expiration |
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| `JWT_ALGORITHM` | `HS256` | JWT algorithm |
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### CORS & Network
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `CORS_ORIGINS` | `*` | Allowed CORS origins |
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| `WHITELIST_PATHS` | `/health,/api/*` | Public paths |
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### Multi-Tenant Security
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `LIGHTRAG_MULTI_TENANT_STRICT` | `true` | Enforce tenant isolation |
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| `LIGHTRAG_REQUIRE_USER_AUTH` | `true` | Require user authentication |
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| `LIGHTRAG_SUPER_ADMIN_USERS` | `admin` | Comma-separated admin usernames |
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---
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## 9. Multi-Tenancy Configuration
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `ENABLE_MULTI_TENANTS` | `false` | Enable multi-tenant mode |
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| `WORKSPACE` | `""` | Default workspace name |
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| `MAX_GRAPH_NODES` | `1000` | Max graph nodes per query |
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| `MAX_PARALLEL_INSERT` | `2` | Max parallel inserts |
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---
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## 10. Complete .env Example
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```bash
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# =============================================================================
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# SERVER CONFIGURATION
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# =============================================================================
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HOST=0.0.0.0
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PORT=9621
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WORKERS=2
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TIMEOUT=300
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WORKING_DIR=./rag_storage
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INPUT_DIR=./inputs
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LOG_LEVEL=INFO
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# =============================================================================
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# LLM CONFIGURATION
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# =============================================================================
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LLM_BINDING=openai
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LLM_MODEL=gpt-4o-mini
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LLM_BINDING_HOST=https://api.openai.com/v1
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LLM_BINDING_API_KEY=sk-xxx
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MAX_ASYNC=4
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ENABLE_LLM_CACHE=true
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# =============================================================================
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# EMBEDDING CONFIGURATION
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# =============================================================================
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EMBEDDING_BINDING=openai
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EMBEDDING_MODEL=text-embedding-ada-002
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EMBEDDING_DIM=1536
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EMBEDDING_BINDING_API_KEY=sk-xxx
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EMBEDDING_FUNC_MAX_ASYNC=8
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EMBEDDING_BATCH_NUM=10
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# =============================================================================
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# STORAGE CONFIGURATION
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# =============================================================================
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LIGHTRAG_KV_STORAGE=JsonKVStorage
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LIGHTRAG_VECTOR_STORAGE=NanoVectorDBStorage
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LIGHTRAG_GRAPH_STORAGE=NetworkXStorage
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LIGHTRAG_DOC_STATUS_STORAGE=JsonDocStatusStorage
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# PostgreSQL (if using PG storage)
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# POSTGRES_HOST=localhost
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# POSTGRES_PORT=5432
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# POSTGRES_USER=lightrag
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# POSTGRES_PASSWORD=secret
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# POSTGRES_DATABASE=lightrag
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# Neo4j (if using Neo4J storage)
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# NEO4J_URI=bolt://localhost:7687
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# NEO4J_USERNAME=neo4j
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# NEO4J_PASSWORD=secret
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# =============================================================================
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# DOCUMENT PROCESSING
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# =============================================================================
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CHUNK_SIZE=1200
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CHUNK_OVERLAP_SIZE=100
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SUMMARY_LANGUAGE=English
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SUMMARY_MAX_TOKENS=1200
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SUMMARY_CONTEXT_SIZE=12000
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# =============================================================================
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# QUERY CONFIGURATION
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# =============================================================================
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TOP_K=40
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CHUNK_TOP_K=20
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MAX_ENTITY_TOKENS=6000
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MAX_RELATION_TOKENS=8000
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MAX_TOTAL_TOKENS=30000
|
|
COSINE_THRESHOLD=0.2
|
|
|
|
# =============================================================================
|
|
# RERANKING (optional)
|
|
# =============================================================================
|
|
# RERANK_BINDING=cohere
|
|
# RERANK_MODEL=rerank-english-v2.0
|
|
# RERANK_BINDING_API_KEY=xxx
|
|
|
|
# =============================================================================
|
|
# AUTHENTICATION
|
|
# =============================================================================
|
|
AUTH_USER=admin
|
|
AUTH_PASS=admin123
|
|
TOKEN_SECRET=your-secure-secret-key
|
|
TOKEN_EXPIRE_HOURS=48
|
|
CORS_ORIGINS=*
|
|
|
|
# =============================================================================
|
|
# MULTI-TENANCY (optional)
|
|
# =============================================================================
|
|
# ENABLE_MULTI_TENANTS=true
|
|
# LIGHTRAG_MULTI_TENANT_STRICT=true
|
|
# LIGHTRAG_REQUIRE_USER_AUTH=true
|
|
# LIGHTRAG_SUPER_ADMIN_USERS=admin
|
|
```
|
|
|
|
---
|
|
|
|
## 11. Python LightRAG Dataclass
|
|
|
|
```python
|
|
@dataclass
|
|
class LightRAG:
|
|
# Directory configuration
|
|
working_dir: str = "./rag_storage"
|
|
|
|
# LLM configuration
|
|
llm_model_name: str = "gpt-4o-mini"
|
|
llm_model_func: Callable = openai_complete_if_cache
|
|
llm_model_max_async: int = 4
|
|
llm_model_max_token_size: int = 32768
|
|
llm_model_kwargs: dict = field(default_factory=dict)
|
|
|
|
# Embedding configuration
|
|
embedding_model_name: str = "text-embedding-ada-002"
|
|
embedding_func: EmbeddingFunc = None
|
|
embedding_batch_num: int = 10
|
|
embedding_func_max_async: int = 8
|
|
|
|
# Chunking configuration
|
|
chunk_token_size: int = 1200
|
|
chunk_overlap_token_size: int = 100
|
|
tiktoken_model_name: str = "gpt-4o"
|
|
|
|
# Entity extraction
|
|
entity_extract_max_gleaning: int = 1
|
|
entity_summary_to_max_tokens: int = 1200
|
|
|
|
# Storage backends
|
|
kv_storage: str = "JsonKVStorage"
|
|
vector_storage: str = "NanoVectorDBStorage"
|
|
graph_storage: str = "NetworkXStorage"
|
|
doc_status_storage: str = "JsonDocStatusStorage"
|
|
|
|
# Advanced options
|
|
enable_llm_cache: bool = True
|
|
enable_llm_cache_for_entity_extract: bool = True
|
|
auto_manage_storages_states: bool = True
|
|
|
|
# Namespace (for multi-tenancy)
|
|
namespace: str = None
|
|
```
|
|
|
|
---
|
|
|
|
**Related Documentation:**
|
|
- [Architecture Overview](0002-architecture-overview.md)
|
|
- [Storage Backends](0004-storage-backends.md)
|
|
- [LLM Integration](0005-llm-integration.md)
|
|
- [Deployment Guide](0006-deployment-guide.md)
|