<!-- .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.
148 lines
5.2 KiB
Python
148 lines
5.2 KiB
Python
"""This module contains the configuration for the graph database."""
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import os
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from functools import lru_cache
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from pydantic_settings import BaseSettings, SettingsConfigDict
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import pydantic
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from pydantic import Field
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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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from cognee.shared.data_models import KnowledgeGraph
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class GraphConfig(BaseSettings):
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"""
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Represents the configuration for a graph system, including parameters for graph file
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storage and database connections.
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Public methods:
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- to_dict
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- to_hashable_dict
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Instance variables:
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- graph_filename
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- graph_database_provider
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- graph_database_url
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- graph_database_username
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- graph_database_password
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- graph_database_port
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- graph_file_path
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- graph_model
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- graph_topology
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- model_config
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"""
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# Using Field we are able to dynamically load current GRAPH_DATABASE_PROVIDER value in the model validator part
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# and determine default graph db file and path based on this parameter if no values are provided
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graph_database_provider: str = Field("kuzu", env="GRAPH_DATABASE_PROVIDER")
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graph_database_url: str = ""
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graph_database_name: str = ""
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graph_database_username: str = ""
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graph_database_password: str = ""
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graph_database_port: int = 123
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graph_file_path: str = ""
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graph_filename: str = ""
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graph_model: object = KnowledgeGraph
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graph_topology: object = KnowledgeGraph
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model_config = SettingsConfigDict(env_file=".env", extra="allow", populate_by_name=True)
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# Model validator updates graph_filename and path dynamically after class creation based on current database provider
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# If no specific graph_filename or path are provided
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@pydantic.model_validator(mode="after")
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def fill_derived(self):
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provider = self.graph_database_provider.lower()
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base_config = get_base_config()
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# Set default filename if no filename is provided
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if not self.graph_filename:
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self.graph_filename = f"cognee_graph_{provider}"
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# Handle graph file path
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if self.graph_file_path:
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# Check if absolute path is provided
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self.graph_file_path = ensure_absolute_path(
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os.path.join(self.graph_file_path, self.graph_filename)
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)
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else:
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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.graph_file_path = os.path.join(databases_directory_path, self.graph_filename)
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return self
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def to_dict(self) -> dict:
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"""
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Return the configuration as a dictionary.
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This dictionary contains all the configurations related to the graph, which includes
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details for file storage and database connectivity.
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Returns:
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--------
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- dict: A dictionary representation of the configuration settings.
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"""
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return {
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"graph_filename": self.graph_filename,
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"graph_database_provider": self.graph_database_provider,
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"graph_database_url": self.graph_database_url,
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"graph_database_username": self.graph_database_username,
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"graph_database_password": self.graph_database_password,
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"graph_database_port": self.graph_database_port,
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"graph_file_path": self.graph_file_path,
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"graph_model": self.graph_model,
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"graph_topology": self.graph_topology,
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"model_config": self.model_config,
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}
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def to_hashable_dict(self) -> dict:
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"""
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Return a hashable dictionary with essential database configuration parameters.
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This dictionary excludes certain non-hashable objects and focuses on unique identifiers
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for database configurations.
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Returns:
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--------
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- dict: A dictionary representation of the essential database configuration
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settings.
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"""
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return {
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"graph_database_provider": self.graph_database_provider,
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"graph_database_url": self.graph_database_url,
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"graph_database_name": self.graph_database_name,
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"graph_database_username": self.graph_database_username,
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"graph_database_password": self.graph_database_password,
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"graph_database_port": self.graph_database_port,
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"graph_file_path": self.graph_file_path,
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}
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@lru_cache
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def get_graph_config():
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"""
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Retrieve the graph configuration. This function utilizes caching to return a singleton
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instance of the GraphConfig class for efficiency.
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It creates and returns a GraphConfig object, which contains various settings related to
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graph configuration.
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Returns:
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--------
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- GraphConfig: A GraphConfig instance containing the graph configuration settings.
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"""
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return GraphConfig()
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def get_graph_context_config():
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"""This function will get the appropriate graph db config based on async context.
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This allows the use of multiple graph databases for different threads, async tasks and parallelization
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"""
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from cognee.context_global_variables import graph_db_config
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if graph_db_config.get():
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return graph_db_config.get()
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return get_graph_config().to_hashable_dict()
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