langchain.schema.memory.BaseMemory

class langchain.schema.memory.BaseMemory

Bases: Serializable, ABC

Abstract base class for memory in Chains.

Memory refers to state in Chains. Memory can be used to store information about

past executions of a Chain and inject that information into the inputs of future executions of the Chain. For example, for conversational Chains Memory can be used to store conversations and automatically add them to future model prompts so that the model has the necessary context to respond coherently to the latest input.

Example

class SimpleMemory(BaseMemory):
    memories: Dict[str, Any] = dict()

    @property
    def memory_variables(self) -> List[str]:
        return list(self.memories.keys())

    def load_memory_variables(self, inputs: Dict[str, Any]) -> Dict[str, str]:
        return self.memories

    def save_context(self, inputs: Dict[str, Any], outputs: Dict[str, str]) -> None:
        pass

    def clear(self) -> None:
        pass

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.

abstract clear() → None

Clear memory contents.

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

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

abstract save_context(inputs: Dict[str, Any], outputs: Dict[str, str]) → None

Save the context of this chain run to memory.

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.

abstract property memory_variables: List[str]

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

model Config

Bases: object

Configuration for this pydantic object.

arbitrary_types_allowed = True

Examples using BaseMemory

• How to create a custom Memory class