3b8b839057
<!-- .github/pull_request_template.md --> ## Description Fix latest pydantic version issues ## Type of Change <!-- Please check the relevant option --> - [ ] Bug fix (non-breaking change that fixes an issue) - [ ] New feature (non-breaking change that adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to change) - [ ] Documentation update - [ ] Code refactoring - [ ] Performance improvement - [ ] Other (please specify): ## Screenshots/Videos (if applicable) <!-- Add screenshots or videos to help explain your changes --> ## Pre-submission Checklist <!-- Please check all boxes that apply before submitting your PR --> - [ ] **I have tested my changes thoroughly before submitting this PR** - [ ] **This PR contains minimal changes necessary to address the issue/feature** - [ ] My code follows the project's coding standards and style guidelines - [ ] I have added tests that prove my fix is effective or that my feature works - [ ] I have added necessary documentation (if applicable) - [ ] All new and existing tests pass - [ ] I have searched existing PRs to ensure this change hasn't been submitted already - [ ] I have linked any relevant issues in the description - [ ] My commits have clear and descriptive messages ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin.
90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
import os
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import pydantic
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from pathlib import Path
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from functools import lru_cache
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from pydantic_settings import BaseSettings, SettingsConfigDict
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from cognee.base_config import get_base_config
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from cognee.root_dir import ensure_absolute_path
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class VectorConfig(BaseSettings):
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"""
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Manage the configuration settings for the vector database.
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Public methods:
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- to_dict: Convert the configuration to a dictionary.
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Instance variables:
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- vector_db_url: The URL of the vector database.
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- vector_db_port: The port for the vector database.
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- vector_db_key: The key for accessing the vector database.
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- vector_db_provider: The provider for the vector database.
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"""
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vector_db_url: str = ""
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vector_db_port: int = 1234
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vector_db_key: str = ""
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vector_db_provider: str = "lancedb"
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model_config = SettingsConfigDict(env_file=".env", extra="allow")
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@pydantic.model_validator(mode="after")
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def validate_paths(self):
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base_config = get_base_config()
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# If vector_db_url is provided and is not a path skip checking if path is absolute (as it can also be a url)
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if self.vector_db_url and Path(self.vector_db_url).exists():
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# Relative path to absolute
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self.vector_db_url = ensure_absolute_path(
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self.vector_db_url,
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)
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elif not self.vector_db_url:
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# Default path
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databases_directory_path = os.path.join(base_config.system_root_directory, "databases")
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self.vector_db_url = os.path.join(databases_directory_path, "cognee.lancedb")
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return self
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def to_dict(self) -> dict:
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"""
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Convert the configuration settings to a dictionary.
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Returns:
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--------
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- dict: A dictionary containing the vector database configuration settings.
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"""
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return {
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"vector_db_url": self.vector_db_url,
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"vector_db_port": self.vector_db_port,
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"vector_db_key": self.vector_db_key,
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"vector_db_provider": self.vector_db_provider,
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}
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@lru_cache
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def get_vectordb_config():
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"""
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Retrieve the cached vector database configuration.
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This function uses the LRU cache to store the instance of `VectorConfig`, allowing for
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efficient reuse without needing to recreate the object multiple times. If a
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configuration is already cached, it returns that instead of creating a new one.
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Returns:
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--------
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- VectorConfig: An instance of `VectorConfig` containing the vector database
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configuration.
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"""
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return VectorConfig()
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def get_vectordb_context_config():
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"""This function will get the appropriate vector db config based on async context."""
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from cognee.context_global_variables import vector_db_config
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if vector_db_config.get():
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return vector_db_config.get()
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return get_vectordb_config().to_dict()
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