feat: allow to use customized GraphRAG settings.yaml (#387) bump:patch
* allow to use customized GraphRAG settings.yaml * adjust import style * fix typo * Added GraphRAG original documentation reference. * feat: allow to use customized GraphRAG settings.yaml (#387) --------- Co-authored-by: Chen, Ron Gang <git@git.com>
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settings.yaml.example
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settings.yaml.example
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# This is a sample GraphRAG settings.yaml file that allows users to run the GraphRAG index process with their customized parameters.
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# The parameters in this file will only take effect when the USE_CUSTOMIZED_GRAPHRAG_SETTING is true in .env file.
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# For a comprehensive understanding of GraphRAG parameters, please refer to: https://microsoft.github.io/graphrag/config/json_yaml/.
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encoding_model: cl100k_base
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skip_workflows: []
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llm:
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api_key: ${GRAPHRAG_API_KEY}
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type: openai_chat # or azure_openai_chat
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api_base: http://127.0.0.1:11434/v1
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model: qwen2
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model_supports_json: true # recommended if this is available for your model.
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# max_tokens: 4000
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request_timeout: 1800.0
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# api_base: https://<instance>.openai.azure.com
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# api_version: 2024-02-15-preview
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# organization: <organization_id>
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# deployment_name: <azure_model_deployment_name>
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# tokens_per_minute: 150_000 # set a leaky bucket throttle
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# requests_per_minute: 10_000 # set a leaky bucket throttle
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# max_retries: 10
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# max_retry_wait: 10.0
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# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
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concurrent_requests: 5 # the number of parallel inflight requests that may be made
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# temperature: 0 # temperature for sampling
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# top_p: 1 # top-p sampling
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# n: 1 # Number of completions to generate
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parallelization:
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stagger: 0.3
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# num_threads: 50 # the number of threads to use for parallel processing
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async_mode: threaded # or asyncio
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embeddings:
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## parallelization: override the global parallelization settings for embeddings
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async_mode: threaded # or asyncio
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# target: required # or all
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# batch_size: 16 # the number of documents to send in a single request
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# batch_max_tokens: 8191 # the maximum number of tokens to send in a single request
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llm:
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api_base: http://localhost:11434/v1
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api_key: ${GRAPHRAG_API_KEY}
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model: nomic-embed-text
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type: openai_embedding
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# api_base: https://<instance>.openai.azure.com
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# api_version: 2024-02-15-preview
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# organization: <organization_id>
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# deployment_name: <azure_model_deployment_name>
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# tokens_per_minute: 150_000 # set a leaky bucket throttle
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# requests_per_minute: 10_000 # set a leaky bucket throttle
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# max_retries: 10
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# max_retry_wait: 10.0
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# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
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# concurrent_requests: 25 # the number of parallel inflight requests that may be made
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chunks:
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size: 1200
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overlap: 100
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group_by_columns: [id] # by default, we don't allow chunks to cross documents
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input:
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type: file # or blob
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file_type: text # or csv
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base_dir: "input"
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file_encoding: utf-8
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file_pattern: ".*\\.txt$"
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cache:
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type: file # or blob
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base_dir: "cache"
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# connection_string: <azure_blob_storage_connection_string>
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# container_name: <azure_blob_storage_container_name>
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storage:
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type: file # or blob
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base_dir: "output"
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# connection_string: <azure_blob_storage_connection_string>
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# container_name: <azure_blob_storage_container_name>
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reporting:
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type: file # or console, blob
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base_dir: "output"
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# connection_string: <azure_blob_storage_connection_string>
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# container_name: <azure_blob_storage_container_name>
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entity_extraction:
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## strategy: fully override the entity extraction strategy.
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## type: one of graph_intelligence, graph_intelligence_json and nltk
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## llm: override the global llm settings for this task
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## parallelization: override the global parallelization settings for this task
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## async_mode: override the global async_mode settings for this task
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prompt: "prompts/entity_extraction.txt"
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entity_types: [organization,person,geo,event]
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max_gleanings: 1
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summarize_descriptions:
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## llm: override the global llm settings for this task
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## parallelization: override the global parallelization settings for this task
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## async_mode: override the global async_mode settings for this task
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prompt: "prompts/summarize_descriptions.txt"
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max_length: 500
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claim_extraction:
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## llm: override the global llm settings for this task
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## parallelization: override the global parallelization settings for this task
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## async_mode: override the global async_mode settings for this task
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# enabled: true
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prompt: "prompts/claim_extraction.txt"
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description: "Any claims or facts that could be relevant to information discovery."
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max_gleanings: 1
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community_reports:
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## llm: override the global llm settings for this task
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## parallelization: override the global parallelization settings for this task
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## async_mode: override the global async_mode settings for this task
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prompt: "prompts/community_report.txt"
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max_length: 2000
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max_input_length: 8000
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cluster_graph:
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max_cluster_size: 10
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embed_graph:
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enabled: false # if true, will generate node2vec embeddings for nodes
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# num_walks: 10
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# walk_length: 40
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# window_size: 2
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# iterations: 3
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# random_seed: 597832
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umap:
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enabled: false # if true, will generate UMAP embeddings for nodes
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snapshots:
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graphml: false
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raw_entities: false
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top_level_nodes: false
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local_search:
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# text_unit_prop: 0.5
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# community_prop: 0.1
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# conversation_history_max_turns: 5
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# top_k_mapped_entities: 10
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# top_k_relationships: 10
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# llm_temperature: 0 # temperature for sampling
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# llm_top_p: 1 # top-p sampling
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# llm_n: 1 # Number of completions to generate
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# max_tokens: 12000
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global_search:
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# llm_temperature: 0 # temperature for sampling
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# llm_top_p: 1 # top-p sampling
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# llm_n: 1 # Number of completions to generate
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# max_tokens: 12000
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# data_max_tokens: 12000
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# map_max_tokens: 1000
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# reduce_max_tokens: 2000
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# concurrency: 32
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