langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory¶
- class langchain_experimental.autonomous_agents.autogpt.memory.AutoGPTMemory(*, chat_memory: BaseChatMessageHistory = None, output_key: Optional[str] = None, input_key: Optional[str] = None, return_messages: bool = False, retriever: VectorStoreRetriever)[source]¶
Bases:
BaseChatMemoryMemory for AutoGPT.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- param chat_memory: BaseChatMessageHistory [Optional]¶
- param input_key: Optional[str] = None¶
- param output_key: Optional[str] = None¶
- param retriever: langchain.vectorstores.base.VectorStoreRetriever [Required]¶
VectorStoreRetriever object to connect to.
- param return_messages: bool = False¶
- clear() None¶
Clear memory contents.
- load_memory_variables(inputs: Dict[str, Any]) Dict[str, Any][source]¶
Return key-value pairs given the text input to the chain.
- save_context(inputs: Dict[str, Any], outputs: Dict[str, str]) None¶
Save context from this conversation to buffer.
- to_json() Union[SerializedConstructor, SerializedNotImplemented]¶
- to_json_not_implemented() SerializedNotImplemented¶
- property lc_attributes: Dict¶
Return a list of attribute names that should be included in the serialized kwargs. These attributes must be accepted by the constructor.
- property lc_namespace: List[str]¶
Return the namespace of the langchain object. eg. [“langchain”, “llms”, “openai”]
- property lc_secrets: Dict[str, str]¶
Return a map of constructor argument names to secret ids. eg. {“openai_api_key”: “OPENAI_API_KEY”}
- property lc_serializable: bool¶
Return whether or not the class is serializable.
- property memory_variables: List[str]¶
The string keys this memory class will add to chain inputs.