Langbase

Create Memory langbase.memory.create()

Create a new AI memory on Langbase using the langbase.memory.create() function.

Generate a User/Org API key

You will need to generate an API key to authenticate your requests. For more information, visit the User/Org API key documentation.

API reference

langbase.memory.create(options)

Function Signature

langbase.memory.create(options);

// with types.
langbase.memory.create(options: MemoryCreateOptions);

options

  • Name
    options
    Type
    MemoryCreateOptions
    Description

    MemoryCreateOptions Object

    interface MemoryCreateOptions {
	name: string;
	description?: string;
	embedding_model?:
		| 'openai:text-embedding-3-large'
		| 'cohere:embed-multilingual-v3.0'
		| 'cohere:embed-multilingual-light-v3.0'
		| 'google:text-embedding-004';
}

    Following are the properties of the options object.

  • Name
    name
    Type
    string
    Required
    Required
    Description

    Name of the memory.

  • Name
    description
    Type
    string
    Description

    Description of the memory.

  • Name
    embedding_model
    Type
    string
    Description

    The model to use for text embeddings. Available options:

    • openai:text-embedding-3-large
    • cohere:embed-multilingual-v3.0
    • cohere:embed-multilingual-light-v3.0
    • google:text-embedding-004

    Default: openai:text-embedding-3-large

Usage example

Install the SDK

npm i langbase

Environment variables

.env file

LANGBASE_API_KEY="<USER/ORG-API-KEY>"

Create memory

Create memory on Langbase

import {Langbase} from 'langbase';

const langbase = new Langbase({
	apiKey: process.env.LANGBASE_API_KEY!,
});

const response = await langbase.memory.create({
	name: 'knowledge-base',
	description: 'An AI memory for storing company internal docs.',
});

Response

  • Name
    MemoryCreateResponse
    Type
    object
    Description

    The response object returned by the langbase.memory.create() function.

    MemoryCreateResponse

    interface MemoryCreateResponse {
	name: string;
	description: string;
	owner_login: string;
	url: string;
	embedding_model:
		| 'openai:text-embedding-3-large'
		| 'cohere:embed-multilingual-v3.0'
		| 'cohere:embed-multilingual-light-v3.0';
}
    • Name
      name
      Type
      string
      Description

      Name of the memory.

    • Name
      description
      Type
      string
      Description

      Description of the AI memory.

    • Name
      owner_login
      Type
      string
      Description

      Login of the memory owner.

    • Name
      url
      Type
      string
      Description

      Memory access URL.

    • Name
      embedding_model
      Type
      string
      Description

      The embedding model used by the AI memory.

      • openai:text-embedding-3-large
      • cohere:embed-multilingual-v3.0
      • cohere:embed-multilingual-light-v3.0

Response of langbase.memory.create()

{
	"name": "knowledge-base",
	"description": "An AI memory for storing company internal docs.",
	"owner_login": "user123",
	"url": "https://langbase.com/user123/document-memory",
	"embedding_model": "openai:text-embedding-3-large"
}