env.example

### This is sample file of .env
OPENAI_API_KEY="your key"

### Settings for RAG query
# HISTORY_TURNS=3
# COSINE_THRESHOLD=0.2
# TOP_K=60
# MAX_TOKEN_TEXT_CHUNK=4000
# MAX_TOKEN_RELATION_DESC=4000
# MAX_TOKEN_ENTITY_DESC=4000

### Entity and ralation summarization configuration
### Language: English, Chinese, French, German ...
SUMMARY_LANGUAGE=English
### Number of duplicated entities/edges to trigger LLM re-summary on merge ( at least 3 is recommented)
# FORCE_LLM_SUMMARY_ON_MERGE=6
### Max tokens for entity/relations description after merge
# MAX_TOKEN_SUMMARY=500

### Number of parallel processing documents(Less than MAX_ASYNC/2 is recommended)
# MAX_PARALLEL_INSERT=2
### Chunk size for document splitting, 500~1500 is recommended
# CHUNK_SIZE=1200
# CHUNK_OVERLAP_SIZE=100

### 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: set as num_ctx option for Ollama by API Server
MAX_TOKENS=32768


### Embedding Configuration
EMBEDDING_MODEL=bge-m3:latest
### you have to change dim of embeedding size if ypu want to change the mebeddiong model 
EMBEDDING_DIM=1024
EMBEDDING_BINDING_API_KEY=your_api_key
### Num of chunks send to Embedding in single request
# EMBEDDING_BATCH_NUM=32
### Max concurrency requests for Embedding
# EMBEDDING_FUNC_MAX_ASYNC=16
### Maximum tokens sent to Embedding for each chunk (no longer in use?)
# MAX_EMBED_TOKENS=8192



### Neo4j Configuration
NEO4J_URI=neo4j+s://xxxxxxxx.databases.neo4j.io
NEO4J_USERNAME=neo4j
NEO4J_PASSWORD='your_password'


### Qdrant
QDRANT_URL=http://localhost:16333
# QDRANT_API_KEY=your-api-key