AutoGPTMemory#

class langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory[source]#

Bases: BaseChatMemory

Memory for AutoGPT.

param chat_memory: BaseChatMessageHistory [Optional]#
param input_key: str | None = None#
param output_key: str | None = None#
param retriever: VectorStoreRetriever [Required]#

VectorStoreRetriever object to connect to.

param return_messages: bool = False#
async aclear() → None#

Clear memory contents.

Return type:

None

async aload_memory_variables(
inputs: dict[str, Any],
) → dict[str, Any]#

Async return key-value pairs given the text input to the chain.

Parameters:

inputs (dict[str, Any]) – The inputs to the chain.

Returns:

A dictionary of key-value pairs.

Return type:

dict[str, Any]

async asave_context(
inputs: dict[str, Any],
outputs: dict[str, str],
) → None#

Save context from this conversation to buffer.

Parameters:

  • inputs (dict[str, Any])

  • outputs (dict[str, str])

Return type:

None

clear() → None#

Clear memory contents.

Return type:

None

load_memory_variables(
inputs: Dict[str, Any],
) → Dict[str, Any][source]#

Return key-value pairs given the text input to the chain.

Parameters:

inputs (Dict[str, Any]) – The inputs to the chain.

Returns:

A dictionary of key-value pairs.

Return type:

Dict[str, Any]

save_context(
inputs: dict[str, Any],
outputs: dict[str, str],
) → None#

Save context from this conversation to buffer.

Parameters:

  • inputs (dict[str, Any])

  • outputs (dict[str, str])

Return type:

None

property memory_variables: List[str]#

The string keys this memory class will add to chain inputs.