mirror of
https://github.com/HKUDS/LightRAG.git
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75d1b1e9f8
- Rename OLLAMA_NUM_CTX to OLLAMA_LLM_NUM_CTX - Increase default context window size - Add requirement for minimum context size - Update documentation examples
262 lines
8.6 KiB
Plaintext
262 lines
8.6 KiB
Plaintext
### This is sample file of .env
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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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WEBUI_TITLE='My Graph KB'
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WEBUI_DESCRIPTION="Simple and Fast Graph Based RAG System"
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# WORKERS=2
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# CORS_ORIGINS=http://localhost:3000,http://localhost:8080
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### Optional SSL Configuration
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# SSL=true
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# SSL_CERTFILE=/path/to/cert.pem
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# SSL_KEYFILE=/path/to/key.pem
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### Directory Configuration (defaults to current working directory)
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### Default value is ./inputs and ./rag_storage
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# INPUT_DIR=<absolute_path_for_doc_input_dir>
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# WORKING_DIR=<absolute_path_for_working_dir>
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### Ollama Emulating Model and Tag
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# OLLAMA_EMULATING_MODEL_NAME=lightrag
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OLLAMA_EMULATING_MODEL_TAG=latest
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### Max nodes return from grap retrieval in webui
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# MAX_GRAPH_NODES=1000
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### Logging level
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# LOG_LEVEL=INFO
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# VERBOSE=False
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# LOG_MAX_BYTES=10485760
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# LOG_BACKUP_COUNT=5
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### Logfile location (defaults to current working directory)
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# LOG_DIR=/path/to/log/directory
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#####################################
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### Login and API-Key Configuration
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#####################################
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# AUTH_ACCOUNTS='admin:admin123,user1:pass456'
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# TOKEN_SECRET=Your-Key-For-LightRAG-API-Server
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# TOKEN_EXPIRE_HOURS=48
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# GUEST_TOKEN_EXPIRE_HOURS=24
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# JWT_ALGORITHM=HS256
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### API-Key to access LightRAG Server API
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# LIGHTRAG_API_KEY=your-secure-api-key-here
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# WHITELIST_PATHS=/health,/api/*
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########################
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### Query Configuration
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########################
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# LLM responde cache for query (Not valid for streaming response)
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ENABLE_LLM_CACHE=true
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# HISTORY_TURNS=0
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# COSINE_THRESHOLD=0.2
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### Number of entities or relations retrieved from KG
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# TOP_K=40
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### Maxmium number or chunks plan to send to LLM
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# CHUNK_TOP_K=10
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### control the actual enties send to LLM
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# MAX_ENTITY_TOKENS=10000
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### control the actual relations send to LLM
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# MAX_RELATION_TOKENS=10000
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### control the maximum tokens send to LLM (include entities, raltions and chunks)
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# MAX_TOTAL_TOKENS=30000
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### maximum number of related chunks per source entity or relation (higher values increase re-ranking time)
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# RELATED_CHUNK_NUMBER=5
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### Reranker configuration (Set ENABLE_RERANK to true in reranking model is configed)
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# ENABLE_RERANK=True
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### Minimum rerank score for document chunk exclusion (set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
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# MIN_RERANK_SCORE=0.0
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### Rerank model configuration (required when ENABLE_RERANK=True)
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# RERANK_MODEL=jina-reranker-v2-base-multilingual
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# RERANK_BINDING_HOST=https://api.jina.ai/v1/rerank
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# RERANK_BINDING_API_KEY=your_rerank_api_key_here
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########################################
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### Document processing configuration
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########################################
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### Language: English, Chinese, French, German ...
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SUMMARY_LANGUAGE=English
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ENABLE_LLM_CACHE_FOR_EXTRACT=true
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### Chunk size for document splitting, 500~1500 is recommended
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# CHUNK_SIZE=1200
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# CHUNK_OVERLAP_SIZE=100
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### Entity and relation summarization configuration
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### Number of duplicated entities/edges to trigger LLM re-summary on merge (at least 3 is recommented)， and max tokens send to LLM
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# FORCE_LLM_SUMMARY_ON_MERGE=4
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# MAX_TOKENS=10000
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### Maximum number of entity extraction attempts for ambiguous content
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# MAX_GLEANING=1
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###############################
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### Concurrency Configuration
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###############################
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### Max concurrency requests of LLM (for both query and document processing)
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MAX_ASYNC=4
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### Number of parallel processing documents(between 2~10, MAX_ASYNC/3 is recommended)
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MAX_PARALLEL_INSERT=2
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### Max concurrency requests for Embedding
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# EMBEDDING_FUNC_MAX_ASYNC=8
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### Num of chunks send to Embedding in single request
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# EMBEDDING_BATCH_NUM=10
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#######################
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### LLM Configuration
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#######################
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### Time out in seconds for LLM, None for infinite timeout
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TIMEOUT=240
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### Some models like o1-mini require temperature to be set to 1
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TEMPERATURE=0
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### LLM Binding type: openai, ollama, lollms, azure_openai
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LLM_BINDING=openai
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LLM_MODEL=gpt-4o
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LLM_BINDING_HOST=https://api.openai.com/v1
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LLM_BINDING_API_KEY=your_api_key
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### Set as num_ctx option for Ollama LLM (Must be larger than MAX_TOTAL_TOKENS+2000)
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### see also env.ollama-binding-options.example for fine tuning ollama
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# OLLAMA_LLM_NUM_CTX=32768
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### Optional for Azure
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# AZURE_OPENAI_API_VERSION=2024-08-01-preview
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# AZURE_OPENAI_DEPLOYMENT=gpt-4o
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####################################################################################
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### Embedding Configuration (Should not be changed after the first file processed)
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####################################################################################
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### Embedding Binding type: openai, ollama, lollms, azure_openai, jina
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EMBEDDING_BINDING=ollama
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EMBEDDING_MODEL=bge-m3:latest
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EMBEDDING_DIM=1024
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EMBEDDING_BINDING_API_KEY=your_api_key
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# If the embedding service is deployed within the same Docker stack, use host.docker.internal instead of localhost
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EMBEDDING_BINDING_HOST=http://localhost:11434
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### Maximum tokens sent to Embedding for each chunk (no longer in use?)
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# MAX_EMBED_TOKENS=8192
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### OpenAI compatible
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# EMBEDDING_BINDING=openai
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# EMBEDDING_MODEL=text-embedding-3-large
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# EMBEDDING_DIM=3072
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# EMBEDDING_BINDING_HOST=https://api.openai.com
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# EMBEDDING_BINDING_API_KEY=your_api_key
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### Optional for Azure
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# AZURE_EMBEDDING_DEPLOYMENT=text-embedding-3-large
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# AZURE_EMBEDDING_API_VERSION=2023-05-15
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# AZURE_EMBEDDING_ENDPOINT=your_endpoint
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# AZURE_EMBEDDING_API_KEY=your_api_key
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### Jina AI Embedding
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EMBEDDING_BINDING=jina
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EMBEDDING_BINDING_HOST=https://api.jina.ai/v1/embeddings
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EMBEDDING_MODEL=jina-embeddings-v4
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EMBEDDING_DIM=2048
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EMBEDDING_BINDING_API_KEY=your_api_key
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####################################################################
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### WORKSPACE setting workspace name for all storage types
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### in the purpose of isolating data from LightRAG instances.
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### Valid workspace name constraints: a-z, A-Z, 0-9, and _
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####################################################################
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# WORKSPACE=space1
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############################
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### Data storage selection
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############################
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### Default storage (Recommended for small scale deployment)
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# LIGHTRAG_KV_STORAGE=JsonKVStorage
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# LIGHTRAG_DOC_STATUS_STORAGE=JsonDocStatusStorage
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# LIGHTRAG_GRAPH_STORAGE=NetworkXStorage
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# LIGHTRAG_VECTOR_STORAGE=NanoVectorDBStorage
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### Redis Storage (Recommended for production deployment)
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# LIGHTRAG_KV_STORAGE=RedisKVStorage
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# LIGHTRAG_DOC_STATUS_STORAGE=RedisDocStatusStorage
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### Vector Storage (Recommended for production deployment)
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# LIGHTRAG_VECTOR_STORAGE=MilvusVectorDBStorage
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# LIGHTRAG_VECTOR_STORAGE=QdrantVectorDBStorage
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# LIGHTRAG_VECTOR_STORAGE=FaissVectorDBStorage
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### Graph Storage (Recommended for production deployment)
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# LIGHTRAG_GRAPH_STORAGE=Neo4JStorage
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# LIGHTRAG_GRAPH_STORAGE=MemgraphStorage
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### PostgreSQL
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# LIGHTRAG_KV_STORAGE=PGKVStorage
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# LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage
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# LIGHTRAG_GRAPH_STORAGE=PGGraphStorage
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# LIGHTRAG_VECTOR_STORAGE=PGVectorStorage
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### MongoDB (Vector storage only available on Atlas Cloud)
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# LIGHTRAG_KV_STORAGE=MongoKVStorage
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# LIGHTRAG_DOC_STATUS_STORAGE=MongoDocStatusStorage
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# LIGHTRAG_GRAPH_STORAGE=MongoGraphStorage
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# LIGHTRAG_VECTOR_STORAGE=MongoVectorDBStorage
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### PostgreSQL Configuration
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POSTGRES_HOST=localhost
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POSTGRES_PORT=5432
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POSTGRES_USER=your_username
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POSTGRES_PASSWORD='your_password'
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POSTGRES_DATABASE=your_database
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POSTGRES_MAX_CONNECTIONS=12
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# POSTGRES_WORKSPACE=forced_workspace_name
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### PostgreSQL SSL Configuration (Optional)
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# POSTGRES_SSL_MODE=require
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# POSTGRES_SSL_CERT=/path/to/client-cert.pem
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# POSTGRES_SSL_KEY=/path/to/client-key.pem
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# POSTGRES_SSL_ROOT_CERT=/path/to/ca-cert.pem
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# POSTGRES_SSL_CRL=/path/to/crl.pem
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### Neo4j Configuration
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NEO4J_URI=neo4j+s://xxxxxxxx.databases.neo4j.io
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NEO4J_USERNAME=neo4j
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NEO4J_PASSWORD='your_password'
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NEO4J_MAX_CONNECTION_POOL_SIZE=100
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NEO4J_CONNECTION_TIMEOUT=30
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NEO4J_CONNECTION_ACQUISITION_TIMEOUT=30
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MAX_TRANSACTION_RETRY_TIME=30
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# NEO4J_WORKSPACE=forced_workspace_name
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### MongoDB Configuration
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MONGO_URI=mongodb://root:root@localhost:27017/
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#MONGO_URI=mongodb+srv://xxxx
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MONGO_DATABASE=LightRAG
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# MONGODB_WORKSPACE=forced_workspace_name
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### Milvus Configuration
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MILVUS_URI=http://localhost:19530
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MILVUS_DB_NAME=lightrag
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# MILVUS_USER=root
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# MILVUS_PASSWORD=your_password
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# MILVUS_TOKEN=your_token
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# MILVUS_WORKSPACE=forced_workspace_name
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### Qdrant
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QDRANT_URL=http://localhost:6333
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# QDRANT_API_KEY=your-api-key
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# QDRANT_WORKSPACE=forced_workspace_name
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### Redis
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REDIS_URI=redis://localhost:6379
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REDIS_SOCKET_TIMEOUT=30
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REDIS_CONNECT_TIMEOUT=10
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REDIS_MAX_CONNECTIONS=100
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REDIS_RETRY_ATTEMPTS=3
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# REDIS_WORKSPACE=forced_workspace_name
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### Memgraph Configuration
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MEMGRAPH_URI=bolt://localhost:7687
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MEMGRAPH_USERNAME=
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MEMGRAPH_PASSWORD=
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MEMGRAPH_DATABASE=memgraph
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# MEMGRAPH_WORKSPACE=forced_workspace_name
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