langchain_community.vectorstores.zep.CollectionConfig

class langchain_community.vectorstores.zep.CollectionConfig(name: str, description: Optional[str], metadata: Optional[Dict[str, Any]], embedding_dimensions: int, is_auto_embedded: bool)[source]

Configuration for a Zep Collection.

If the collection does not exist, it will be created.

Parameters
  • name (str) –

  • description (Optional[str]) –

  • metadata (Optional[Dict[str, Any]]) –

  • embedding_dimensions (int) –

  • is_auto_embedded (bool) –

name

The name of the collection.

Type

str

description

An optional description of the collection.

Type

Optional[str]

metadata

Optional metadata for the collection.

Type

Optional[Dict[str, Any]]

embedding_dimensions

The number of dimensions for the embeddings in the collection. This should match the Zep server configuration if auto-embed is true.

Type

int

is_auto_embedded

A flag indicating whether the collection is automatically embedded by Zep.

Type

bool

Attributes

name

description

metadata

embedding_dimensions

is_auto_embedded

Methods

__init__(name, description, metadata, ...)

__init__(name: str, description: Optional[str], metadata: Optional[Dict[str, Any]], embedding_dimensions: int, is_auto_embedded: bool) None
Parameters
  • name (str) –

  • description (Optional[str]) –

  • metadata (Optional[Dict[str, Any]]) –

  • embedding_dimensions (int) –

  • is_auto_embedded (bool) –

Return type

None

Examples using CollectionConfig