torchcell.knowledge_graphs.kg_manifest.KgBuildManifest

class KgBuildManifest(*, manifest_schema_version: int = 1, database: str, store_host: str, neo4j_version: str, biocypher_version: str, torchcell_commit: str | None, version: str | None = None, release: str | None = None, torchcell_version: str | None = None, torchcell_tag: str | None = None, graph_schema: dict[str, ~torchcell.knowledge_graphs.kg_manifest.GraphSchemaEntry], cell_adapter_methods: dict[str, str], cell_adapter_table: dict[str, str], adapter_files: dict[str, str], value_surface: dict[str, str] = <factory>, organisms: list[~typing.Literal['scerevisiae', 'ecoli', 'pputida']] | None = None, generation: ~torchcell.knowledge_graphs.kg_manifest.GenerationRecord | None = None, datasets: dict[str, ~torchcell.knowledge_graphs.kg_manifest.KgDatasetEntry], events: list[~torchcell.knowledge_graphs.kg_manifest.KgEvent], created_at: str, updated_at: str)

Bases: BaseModel

What the served knowledge graph was built from, dataset by dataset.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].