Update env.example
This commit is contained in:
yangdx
parent
47341d3a71
commit
26865c2cd0
1 changed files with 82 additions and 63 deletions
145
env.example
145
env.example
|
|
@ -1,6 +1,8 @@
|
|||
### This is sample file of .env
|
||||
|
||||
###########################
|
||||
### Server Configuration
|
||||
###########################
|
||||
HOST=0.0.0.0
|
||||
PORT=9621
|
||||
WEBUI_TITLE='My Graph KB'
|
||||
|
|
@ -9,29 +11,17 @@ OLLAMA_EMULATING_MODEL_TAG=latest
|
|||
# WORKERS=2
|
||||
# CORS_ORIGINS=http://localhost:3000,http://localhost:8080
|
||||
|
||||
### Login 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/*
|
||||
|
||||
### Optional SSL Configuration
|
||||
# SSL=true
|
||||
# SSL_CERTFILE=/path/to/cert.pem
|
||||
# SSL_KEYFILE=/path/to/key.pem
|
||||
|
||||
### Directory Configuration (defaults to current working directory)
|
||||
### Should not be set if deploy by docker (Set by Dockerfile instead of .env)
|
||||
### Default value is ./inputs and ./rag_storage
|
||||
# INPUT_DIR=<absolute_path_for_doc_input_dir>
|
||||
# WORKING_DIR=<absolute_path_for_working_dir>
|
||||
|
||||
### Max nodes return from grap retrieval
|
||||
### Max nodes return from grap retrieval in webui
|
||||
# MAX_GRAPH_NODES=1000
|
||||
|
||||
### Logging level
|
||||
|
|
@ -42,68 +32,95 @@ OLLAMA_EMULATING_MODEL_TAG=latest
|
|||
### Logfile location (defaults to current working directory)
|
||||
# LOG_DIR=/path/to/log/directory
|
||||
|
||||
### RAG Configuration
|
||||
### Chunk size for document splitting, 500~1500 is recommended
|
||||
# CHUNK_SIZE=1200
|
||||
# CHUNK_OVERLAP_SIZE=100
|
||||
#####################################
|
||||
### 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
|
||||
|
||||
### RAG Query Configuration
|
||||
### 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=3
|
||||
|
||||
### These parameters provide more precise control over total token usage
|
||||
# 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
|
||||
|
||||
# COSINE_THRESHOLD=0.2
|
||||
### Number of entities or relations to retrieve from KG
|
||||
# TOP_K=40
|
||||
### Number of text chunks to retrieve initially from vector search and keep after reranking
|
||||
# CHUNK_TOP_K=10
|
||||
|
||||
### Enable reranking for retrieved text chunks (default: true)
|
||||
# ENABLE_RERANK=true
|
||||
|
||||
### Rerank Configuration
|
||||
### Rerank model configuration (required when enable_rerank=true in query parameters)
|
||||
### 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
|
||||
|
||||
### Entity and relation summarization configuration
|
||||
########################################
|
||||
### 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=6
|
||||
# FORCE_LLM_SUMMARY_ON_MERGE=4
|
||||
### Maximum number of entity extraction attempts for ambiguous content
|
||||
# MAX_GLEANING=1
|
||||
|
||||
### Number of parallel processing documents(Less than MAX_ASYNC/2 is recommended)
|
||||
# MAX_PARALLEL_INSERT=2
|
||||
###############################
|
||||
### 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
|
||||
ENABLE_LLM_CACHE=true
|
||||
ENABLE_LLM_CACHE_FOR_EXTRACT=true
|
||||
#######################
|
||||
### 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
|
||||
### Max concurrency requests of LLM
|
||||
MAX_ASYNC=4
|
||||
### MAX_TOKENS: max tokens send to LLM for entity relation summaries (less than context size of the model)
|
||||
MAX_TOKENS=32000
|
||||
### 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
|
||||
### set as num_ctx option for Ollama LLM
|
||||
# OLLAMA_NUM_CTX=32768
|
||||
|
||||
### Embedding Configuration
|
||||
####################################################################################
|
||||
### Embedding Configuration (Should not be changed after the first file processed)
|
||||
####################################################################################
|
||||
### Embedding Binding type: openai, ollama, lollms, azure_openai
|
||||
EMBEDDING_BINDING=ollama
|
||||
EMBEDDING_MODEL=bge-m3:latest
|
||||
|
|
@ -111,51 +128,53 @@ 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
|
||||
### Num of chunks send to Embedding in single request
|
||||
# EMBEDDING_BATCH_NUM=10
|
||||
### Max concurrency requests for Embedding
|
||||
# EMBEDDING_FUNC_MAX_ASYNC=8
|
||||
### 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
|
||||
|
||||
###########################
|
||||
############################
|
||||
### Data storage selection
|
||||
###########################
|
||||
### In-memory database with local file persistence(Recommended for small scale deployment)
|
||||
############################
|
||||
### 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
|
||||
### 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
|
||||
### Graph Storage (Recommended for production deployment)
|
||||
# LIGHTRAG_GRAPH_STORAGE=Neo4JStorage
|
||||
# LIGHTRAG_GRAPH_STORAGE=MemgraphStorage
|
||||
|
||||
####################################################################
|
||||
### Default workspace for all storage types
|
||||
### For the purpose of isolation of data for each LightRAG instance
|
||||
### Valid characters: a-z, A-Z, 0-9, and _
|
||||
### 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
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue