graphrag/docsite/posts/query/3-cli.md

title	navtitle	layout	tags	date
Query CLI	CLI	page	post orchestration	2024-27-03

The GraphRAG query CLI allows for no-code usage of the GraphRAG Query engine.

python -m graphrag.query --config <config_file.yml> --data <path-to-data> --community_level <comunit-level> --response_type <response-type> --method <"local"|"global"> <query>

CLI Arguments

• --config <config_file.yml> - The configuration yaml file to use when running the query. If this is used, then none of the environment-variables below will apply.
• --data <path-to-data> - Folder containing the .parquet output files from running the Indexer.
• --community_level <community-level> - Community level in the Leiden community hierarchy from which we will load the community reports higher value means we use reports on smaller communities. Default: 2
• --response_type <response-type> - Free form text describing the response type and format, can be anything, e.g. Multiple Paragraphs, Single Paragraph, Single Sentence, List of 3-7 Points, Single Page, Multi-Page Report. Default: Multiple Paragraphs.
• --method <"local"|"global"> - Method to use to answer the query, one of local or global. For more information check Overview
• --streaming - Stream back the LLM response

Env Variables

Required environment variables to execute:

• GRAPHRAG_API_KEY - API Key for executing the model, will fallback to OPENAI_API_KEY if one is not provided.
• GRAPHRAG_LLM_MODEL - Model to use for Chat Completions.
• GRAPHRAG_EMBEDDING_MODEL - Model to use for Embeddings.

You can further customize the execution by providing these environment variables:

• GRAPHRAG_LLM_API_BASE - The API Base URL. Default: None
• GRAPHRAG_LLM_TYPE - The LLM operation type. Either openai_chat or azure_openai_chat. Default: openai_chat
• GRAPHRAG_LLM_MAX_RETRIES - The maximum number of retries to attempt when a request fails. Default: 20
• GRAPHRAG_EMBEDDING_API_BASE - The API Base URL. Default: None
• GRAPHRAG_EMBEDDING_TYPE - The embedding client to use. Either openai_embedding or azure_openai_embedding. Default: openai_embedding
• GRAPHRAG_EMBEDDING_MAX_RETRIES - The maximum number of retries to attempt when a request fails. Default: 20
• GRAPHRAG_LOCAL_SEARCH_TEXT_UNIT_PROP - Proportion of context window dedicated to related text units. Default: 0.5
• GRAPHRAG_LOCAL_SEARCH_COMMUNITY_PROP - Proportion of context window dedicated to community reports. Default: 0.1
• GRAPHRAG_LOCAL_SEARCH_CONVERSATION_HISTORY_MAX_TURNS - Maximum number of turns to include in the conversation history. Default: 5
• GRAPHRAG_LOCAL_SEARCH_TOP_K_ENTITIES - Number of related entities to retrieve from the entity description embedding store. Default: 10
• GRAPHRAG_LOCAL_SEARCH_TOP_K_RELATIONSHIPS - Control the number of out-of-network relationships to pull into the context window. Default: 10
• GRAPHRAG_LOCAL_SEARCH_MAX_TOKENS - Change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000). Default: 12000
• GRAPHRAG_LOCAL_SEARCH_LLM_MAX_TOKENS - Change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 1000=1500). Default: 2000
• GRAPHRAG_GLOBAL_SEARCH_MAX_TOKENS - Change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000). Default: 12000
• GRAPHRAG_GLOBAL_SEARCH_DATA_MAX_TOKENS - Change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 5000). Default: 12000
• GRAPHRAG_GLOBAL_SEARCH_MAP_MAX_TOKENS - Default: 500
• GRAPHRAG_GLOBAL_SEARCH_REDUCE_MAX_TOKENS - Change this based on the token limit you have on your model (if you are using a model with 8k limit, a good setting could be 1000-1500). Default: 2000
• GRAPHRAG_GLOBAL_SEARCH_CONCURRENCY - Default: 32