naas.ai Docs

EngineConfiguration_VectorStoreService

2 min read

EngineConfiguration_VectorStoreService

What it is

Pydantic-based configuration models to validate and construct a VectorStoreService with a pluggable vector store adapter (qdrant, qdrant_in_memory, or custom).

Public API

  • class VectorStoreAdapterQdrantConfiguration(BaseModel)

    • Validates configuration for the qdrant adapter.
    • Fields:
      • host: str = "localhost"
      • port: int = 6333
      • api_key: str | None = None
      • https: bool = False
      • timeout: int = 30
    • extra="forbid" (unknown fields rejected).

  • class VectorStoreAdapterQdrantInMemoryConfiguration(BaseModel)

    • Validates configuration for the qdrant_in_memory adapter.
    • No fields; extra="forbid".

  • class VectorStoreAdapterConfiguration(GenericLoader)

    • Selects an adapter and validates its config.
    • Fields:
      • adapter: Literal["qdrant", "qdrant_in_memory", "custom"]
      • config: dict | None = None
    • Methods:
      • validate_adapter(self) -> VectorStoreAdapterConfiguration (Pydantic @model_validator(mode="after"))
        • Requires config when adapter != "custom".
        • Validates config against the adapter-specific Pydantic model via pydantic_model_validator(...).
      • load(self) -> IVectorStorePort
        • For qdrant: lazily imports and instantiates QdrantAdapter(**config).
        • For qdrant_in_memory: lazily imports and instantiates QdrantInMemoryAdapter(**config).
        • For custom: delegates to GenericLoader.load().

  • class VectorStoreServiceConfiguration(BaseModel)

    • Fields:
      • vector_store_adapter: VectorStoreAdapterConfiguration
    • Methods:
      • load(self) -> VectorStoreService
        • Returns VectorStoreService(adapter=self.vector_store_adapter.load()).

Configuration/Dependencies

  • Depends on:
    • pydantic (BaseModel, ConfigDict, model_validator)
    • naas_abi_core.services.vector_store.VectorStoreService
    • naas_abi_core.services.vector_store.IVectorStorePort
    • Adapter implementations are lazily imported:
      • naas_abi_core.services.vector_store.adapters.QdrantAdapter.QdrantAdapter
      • naas_abi_core.services.vector_store.adapters.QdrantInMemoryAdapter.QdrantInMemoryAdapter
  • Validation helper:
    • pydantic_model_validator(model_cls, data, message) is used to validate adapter config.

Usage

from naas_abi_core.engine.engine_configuration.EngineConfiguration_VectorStoreService import (
    VectorStoreServiceConfiguration,
)
 
cfg = VectorStoreServiceConfiguration.model_validate(
    {
        "vector_store_adapter": {
            "adapter": "qdrant",
            "config": {
                "host": "localhost",
                "port": 6333,
                "api_key": None,
                "https": False,
                "timeout": 30,
            },
        }
    }
)
 
vector_store_service = cfg.load()

Caveats

  • config is required for all adapters except custom; missing config triggers an AssertionError.
  • For qdrant and qdrant_in_memory, extra/unknown keys in config are rejected (extra="forbid").
  • custom adapter behavior depends on GenericLoader.load() (not defined in this module).

Graph View