InMemoryDBModel

class langchain_aws.vectorstores.inmemorydb.schema.InMemoryDBModel

Bases: BaseModel

Schema for MemoryDB index.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

param content_key: str = 'content'

param content_vector_key: str = 'content_vector'

param extra: List[InMemoryDBField] | None = None

param numeric: List[NumericFieldSchema] | None = None

param tag: List[TagFieldSchema] | None = None

param text: List[TextFieldSchema] = [TextFieldSchema(name='content', weight=1, no_stem=False, phonetic_matcher=None, withsuffixtrie=False, no_index=False, sortable=False)]

param vector: List[FlatVectorField | HNSWVectorField] | None = None

add_content_field() → None

Return type:

None

add_vector_field(vector_field: Dict[str, Any]) → None

Parameters:

vector_field (Dict[str, Any])

Return type:

None

as_dict() → Dict[str, List[Any]]

Return type:

Dict[str, List[Any]]

get_fields() → List[InMemoryDBField]

Return type:

List[InMemoryDBField]

property content_vector: FlatVectorField | HNSWVectorField

property is_empty: bool

property metadata_keys: List[str]

property vector_dtype: dtype