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c644338bae
* Refactor config
- Add new ModelConfig to represent LLM settings
- Combines LLMParameters, ParallelizationParameters, encoding_model, and async_mode
- Add top level models config that is a list of available LLM ModelConfigs
- Remove LLMConfig inheritance and delete LLMConfig
- Replace the inheritance with a model_id reference to the ModelConfig listed in the top level models config
- Remove all fallbacks and hydration logic from create_graphrag_config
- This removes the automatic env variable overrides
- Support env variables within config files using Templating
- This requires "$" to be escaped with extra "$" so ".*\\.txt$" becomes ".*\\.txt$$"
- Update init content to initialize new config file with the ModelConfig structure
* Use dict of ModelConfig instead of list
* Add model validations and unit tests
* Fix ruff checks
* Add semversioner change
* Fix unit tests
* validate root_dir in pydantic model
* Rename ModelConfig to LanguageModelConfig
* Rename ModelConfigMissingError to LanguageModelConfigMissingError
* Add validationg for unexpected API keys
* Allow skipping pydantic validation for testing/mocking purposes.
* Add default lm configs to verb tests
* smoke test
* remove config from flows to fix llm arg mapping
* Fix embedding llm arg mapping
* Remove timestamp from smoke test outputs
* Remove unused "subworkflows" smoke test properties
* Add models to smoke test configs
* Update smoke test output path
* Send logs to logs folder
* Fix output path
* Fix csv test file pattern
* Update placeholder
* Format
* Instantiate default model configs
* Fix unit tests for config defaults
* Fix migration notebook
* Remove create_pipeline_config
* Remove several unused config models
* Remove indexing embedding and input configs
* Move embeddings function to config
* Remove skip_workflows
* Remove skip embeddings in favor of explicit naming
* fix unit test spelling mistake
* self.models[model_id] is already a language model. Remove redundant casting.
* update validation errors to instruct users to rerun graphrag init
* instantiate LanguageModelConfigs with validation
* skip validation in unit tests
* update verb tests to use default model settings instead of skipping validation
* test using llm settings
* cleanup verb tests
* remove unsafe default model config
* remove the ability to skip pydantic validation
* remove None union types when default values are set
* move vector_store from embeddings to top level of config and delete resolve_paths
* update vector store settings
* fix vector store and smoke tests
* fix serializing vector_store settings
* fix vector_store usage
* fix vector_store type
* support cli overrides for loading graphrag config
* rename storage to output
* Add --force flag to init
* Remove run_id and resume, fix Drift config assignment
* Ruff
---------
Co-authored-by: Nathan Evans <github@talkswithnumbers.com>
Co-authored-by: Alonso Guevara <alonsog@microsoft.com>
55 lines
1.4 KiB
YAML
55 lines
1.4 KiB
YAML
models:
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default_chat_model:
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type: ${GRAPHRAG_LLM_TYPE}
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api_key: ${GRAPHRAG_API_KEY}
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api_base: ${GRAPHRAG_API_BASE}
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api_version: ${GRAPHRAG_API_VERSION}
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deployment_name: ${GRAPHRAG_LLM_DEPLOYMENT_NAME}
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model: ${GRAPHRAG_LLM_MODEL}
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tokens_per_minute: ${GRAPHRAG_LLM_TPM}
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requests_per_minute: ${GRAPHRAG_LLM_RPM}
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model_supports_json: true
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parallelization_num_threads: 50
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parallelization_stagger: 0.3
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async_mode: threaded
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default_embedding_model:
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type: ${GRAPHRAG_EMBEDDING_TYPE}
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api_key: ${GRAPHRAG_API_KEY}
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api_base: ${GRAPHRAG_API_BASE}
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api_version: ${GRAPHRAG_API_VERSION}
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deployment_name: ${GRAPHRAG_EMBEDDING_DEPLOYMENT_NAME}
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model: ${GRAPHRAG_EMBEDDING_MODEL}
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tokens_per_minute: ${GRAPHRAG_EMBEDDING_TPM}
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requests_per_minute: ${GRAPHRAG_EMBEDDING_RPM}
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parallelization_num_threads: 50
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parallelization_stagger: 0.3
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async_mode: threaded
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vector_store:
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type: "azure_ai_search"
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url: ${AZURE_AI_SEARCH_URL_ENDPOINT}
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api_key: ${AZURE_AI_SEARCH_API_KEY}
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container_name: "simple_text_ci"
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claim_extraction:
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enabled: true
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embeddings:
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model_id: "default_embedding_model"
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community_reports:
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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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storage:
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type: file
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base_dir: "output"
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reporting:
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type: file
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base_dir: "logs"
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snapshots:
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embeddings: True |