List Agents

200

Successful Response

Response body

array of objects

Response List Agents

object

description

The description of the agent.

metadata_

The metadata of the agent.

user_id

The user id of the agent.

string

The human-friendly ID of the Agent

name

string

required

The name of the agent.

created_at

date-time

The datetime the agent was created.

message_ids

The ids of the messages in the agent's in-context memory.

memory

object

Represents the in-context memory of the agent. This includes both the Block objects (labelled by sections), as well as tools to edit the blocks.

Attributes:
memory (Dict[str, Block]): Mapping from memory block section to memory block.

tools

array of strings

required

The tools used by the agent.

Tools*

system

string

required

The system prompt used by the agent.

llm_config

object

required

Configuration for a Language Model (LLM) model. This object specifies all the information necessary to access an LLM model to usage with MemGPT, except for secret keys.

Attributes:
model (str): The name of the LLM model.
model_endpoint_type (str): The endpoint type for the model.
model_endpoint (str): The endpoint for the model.
model_wrapper (str): The wrapper for the model.
context_window (int): The context window size for the model.

embedding_config

object

required

Embedding model configuration. This object specifies all the information necessary to access an embedding model to usage with MemGPT, except for secret keys.

Attributes:
embedding_endpoint_type (str): The endpoint type for the model.
embedding_endpoint (str): The endpoint for the model.
embedding_model (str): The model for the embedding.
embedding_dim (int): The dimension of the embedding.
embedding_chunk_size (int): The chunk size of the embedding.
azure_endpoint (:obj:str, optional): The Azure endpoint for the model (Azure only).
azure_version (str): The Azure version for the model (Azure only).
azure_deployment (str): The Azure deployment for the model (Azure only).

200Successful Response