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.

The tools used by the agent.

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 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).