### This is sample file of .env ########################### ### Server Configuration ########################### HOST=0.0.0.0 PORT=9621 WEBUI_TITLE='My Graph KB' WEBUI_DESCRIPTION="Simple and Fast Graph Based RAG System" OLLAMA_EMULATING_MODEL_TAG=latest # WORKERS=2 # CORS_ORIGINS=http://localhost:3000,http://localhost:8080 ### Optional SSL Configuration # SSL=true # SSL_CERTFILE=/path/to/cert.pem # SSL_KEYFILE=/path/to/key.pem ### Directory Configuration (defaults to current working directory) ### Default value is ./inputs and ./rag_storage # INPUT_DIR= # WORKING_DIR= ### Max nodes return from grap retrieval in webui # MAX_GRAPH_NODES=1000 ### Logging level # LOG_LEVEL=INFO # VERBOSE=False # LOG_MAX_BYTES=10485760 # LOG_BACKUP_COUNT=5 ### Logfile location (defaults to current working directory) # LOG_DIR=/path/to/log/directory ##################################### ### Login and API-Key Configuration ##################################### # AUTH_ACCOUNTS='admin:admin123,user1:pass456' # TOKEN_SECRET=Your-Key-For-LightRAG-API-Server # TOKEN_EXPIRE_HOURS=48 # GUEST_TOKEN_EXPIRE_HOURS=24 # JWT_ALGORITHM=HS256 ### API-Key to access LightRAG Server API # LIGHTRAG_API_KEY=your-secure-api-key-here # WHITELIST_PATHS=/health,/api/* ######################## ### Query Configuration ######################## # LLM responde cache for query (Not valid for streaming response ENABLE_LLM_CACHE=true # HISTORY_TURNS=0 # COSINE_THRESHOLD=0.2 ### Number of entities or relations retrieved from KG # TOP_K=40 ### Maxmium number or chunks plan to send to LLM # CHUNK_TOP_K=10 ### control the actual enties send to LLM # MAX_ENTITY_TOKENS=10000 ### control the actual relations send to LLM # MAX_RELATION_TOKENS=10000 ### control the maximum tokens send to LLM (include entities, raltions and chunks) # MAX_TOTAL_TOKENS=32000 ### maxumium related chunks grab from single entity or relations # RELATED_CHUNK_NUMBER=10 ### Reranker configuration (Set ENABLE_RERANK to true in reranking model is configed) ENABLE_RERANK=False # RERANK_MODEL=BAAI/bge-reranker-v2-m3 # RERANK_BINDING_HOST=https://api.your-rerank-provider.com/v1/rerank # RERANK_BINDING_API_KEY=your_rerank_api_key_here ######################################## ### Document processing configuration ######################################## ### Language: English, Chinese, French, German ... SUMMARY_LANGUAGE=English ENABLE_LLM_CACHE_FOR_EXTRACT=true ### MAX_TOKENS: max tokens send to LLM for entity relation summaries (less than context size of the model) MAX_TOKENS=32000 ### Chunk size for document splitting, 500~1500 is recommended # CHUNK_SIZE=1200 # CHUNK_OVERLAP_SIZE=100 ### Entity and relation summarization configuration ### Number of duplicated entities/edges to trigger LLM re-summary on merge ( at least 3 is recommented) # FORCE_LLM_SUMMARY_ON_MERGE=4 ### Maximum number of entity extraction attempts for ambiguous content # MAX_GLEANING=1 ############################### ### Concurrency Configuration ############################### ### Max concurrency requests of LLM (for both query and document processing) MAX_ASYNC=4 ### Number of parallel processing documents(between 2~10, MAX_ASYNC/4 is recommended) MAX_PARALLEL_INSERT=2 ### Max concurrency requests for Embedding # EMBEDDING_FUNC_MAX_ASYNC=8 ### Num of chunks send to Embedding in single request # EMBEDDING_BATCH_NUM=10 ####################### ### LLM Configuration ####################### ### Time out in seconds for LLM, None for infinite timeout TIMEOUT=240 ### Some models like o1-mini require temperature to be set to 1 TEMPERATURE=0 ### LLM Binding type: openai, ollama, lollms, azure_openai LLM_BINDING=openai LLM_MODEL=gpt-4o LLM_BINDING_HOST=https://api.openai.com/v1 LLM_BINDING_API_KEY=your_api_key ### Set as num_ctx option for Ollama LLM # OLLAMA_NUM_CTX=32768 ### Optional for Azure # AZURE_OPENAI_API_VERSION=2024-08-01-preview # AZURE_OPENAI_DEPLOYMENT=gpt-4o #################################################################################### ### Embedding Configuration (Should not be changed after the first file processed) #################################################################################### ### Embedding Binding type: openai, ollama, lollms, azure_openai, jina EMBEDDING_BINDING=ollama EMBEDDING_MODEL=bge-m3:latest EMBEDDING_DIM=1024 EMBEDDING_BINDING_API_KEY=your_api_key # If the embedding service is deployed within the same Docker stack, use host.docker.internal instead of localhost EMBEDDING_BINDING_HOST=http://localhost:11434 ### Maximum tokens sent to Embedding for each chunk (no longer in use?) # MAX_EMBED_TOKENS=8192 ### Optional for Azure # AZURE_EMBEDDING_DEPLOYMENT=text-embedding-3-large # AZURE_EMBEDDING_API_VERSION=2023-05-15 # AZURE_EMBEDDING_ENDPOINT=your_endpoint # AZURE_EMBEDDING_API_KEY=your_api_key ### Jina AI Embedding EMBEDDING_BINDING=jina EMBEDDING_BINDING_HOST=https://api.jina.ai/v1/embeddings EMBEDDING_MODEL=jina-embeddings-v4 EMBEDDING_DIM=2048 EMBEDDING_BINDING_API_KEY=your_api_key ############################ ### Data storage selection ############################ ### Default storage (Recommended for small scale deployment) # LIGHTRAG_KV_STORAGE=JsonKVStorage # LIGHTRAG_DOC_STATUS_STORAGE=JsonDocStatusStorage # LIGHTRAG_GRAPH_STORAGE=NetworkXStorage # LIGHTRAG_VECTOR_STORAGE=NanoVectorDBStorage ### Redis Storage (Recommended for production deployment) # LIGHTRAG_KV_STORAGE=RedisKVStorage # LIGHTRAG_DOC_STATUS_STORAGE=RedisDocStatusStorage ### Vector Storage (Recommended for production deployment) # LIGHTRAG_VECTOR_STORAGE=MilvusVectorDBStorage # LIGHTRAG_VECTOR_STORAGE=QdrantVectorDBStorage # LIGHTRAG_VECTOR_STORAGE=FaissVectorDBStorage ### Graph Storage (Recommended for production deployment) # LIGHTRAG_GRAPH_STORAGE=Neo4JStorage # LIGHTRAG_GRAPH_STORAGE=MemgraphStorage ### PostgreSQL # LIGHTRAG_KV_STORAGE=PGKVStorage # LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage # LIGHTRAG_GRAPH_STORAGE=PGGraphStorage # LIGHTRAG_VECTOR_STORAGE=PGVectorStorage ### MongoDB (Vector storage only available on Atlas Cloud) # LIGHTRAG_KV_STORAGE=MongoKVStorage # LIGHTRAG_DOC_STATUS_STORAGE=MongoDocStatusStorage # LIGHTRAG_GRAPH_STORAGE=MongoGraphStorage # LIGHTRAG_VECTOR_STORAGE=MongoVectorDBStorage #################################################################### ### WORKSPACE setting workspace name for all storage types ### in the purpose of isolating data from LightRAG instances. ### Valid workspace name constraints: a-z, A-Z, 0-9, and _ #################################################################### # WORKSPACE=space1 ### PostgreSQL Configuration POSTGRES_HOST=localhost POSTGRES_PORT=5432 POSTGRES_USER=your_username POSTGRES_PASSWORD='your_password' POSTGRES_DATABASE=your_database POSTGRES_MAX_CONNECTIONS=12 # POSTGRES_WORKSPACE=forced_workspace_name ### PostgreSQL SSL Configuration (Optional) # POSTGRES_SSL_MODE=require # POSTGRES_SSL_CERT=/path/to/client-cert.pem # POSTGRES_SSL_KEY=/path/to/client-key.pem # POSTGRES_SSL_ROOT_CERT=/path/to/ca-cert.pem # POSTGRES_SSL_CRL=/path/to/crl.pem ### Neo4j Configuration NEO4J_URI=neo4j+s://xxxxxxxx.databases.neo4j.io NEO4J_USERNAME=neo4j NEO4J_PASSWORD='your_password' NEO4J_MAX_CONNECTION_POOL_SIZE=100 NEO4J_CONNECTION_TIMEOUT=30 NEO4J_CONNECTION_ACQUISITION_TIMEOUT=30 MAX_TRANSACTION_RETRY_TIME=30 # NEO4J_WORKSPACE=forced_workspace_name ### MongoDB Configuration MONGO_URI=mongodb://root:root@localhost:27017/ #MONGO_URI=mongodb+srv://xxxx MONGO_DATABASE=LightRAG # MONGODB_WORKSPACE=forced_workspace_name ### Milvus Configuration MILVUS_URI=http://localhost:19530 MILVUS_DB_NAME=lightrag # MILVUS_USER=root # MILVUS_PASSWORD=your_password # MILVUS_TOKEN=your_token # MILVUS_WORKSPACE=forced_workspace_name ### Qdrant QDRANT_URL=http://localhost:6333 # QDRANT_API_KEY=your-api-key # QDRANT_WORKSPACE=forced_workspace_name ### Redis REDIS_URI=redis://localhost:6379 REDIS_SOCKET_TIMEOUT=30 REDIS_CONNECT_TIMEOUT=10 REDIS_MAX_CONNECTIONS=100 REDIS_RETRY_ATTEMPTS=3 # REDIS_WORKSPACE=forced_workspace_name ### Memgraph Configuration MEMGRAPH_URI=bolt://localhost:7687 MEMGRAPH_USERNAME= MEMGRAPH_PASSWORD= MEMGRAPH_DATABASE=memgraph # MEMGRAPH_WORKSPACE=forced_workspace_name