memoryscope.core.storage.dummy_memory_store

class memoryscope.core.storage.dummy_memory_store.DummyMemoryStore(embedding_model: BaseModel, **kwargs)

Bases: BaseMemoryStore

Placeholder implementation of a memory storage system interface. Defines methods for querying, updating, and closing memory nodes with asynchronous capabilities, leveraging an embedding model for potential semantic retrieval. Actual storage operations are not implemented.

__init__(embedding_model: BaseModel, **kwargs)

Initializes the DummyMemoryStore with an embedding model and additional keyword arguments.

Parameters:

• embedding_model (BaseModel) – The model used to embed data for potential similarity-based retrieval.

• **kwargs – Additional keyword arguments for configuration or future expansion.

retrieve_memories(query: str = '', top_k: int = 3, filter_dict: Dict[str, List[str]] | None = None) → List[MemoryNode]

Retrieves a list of MemoryNode objects that are most relevant to the query, considering a filter dictionary for additional constraints. The number of nodes returned is limited by top_k.

Parameters:

• query (str) – The query string used to find relevant memories.

• top_k (int) – The maximum number of MemoryNode objects to return.

• filter_dict (Dict[str, List[str]]) – A dictionary with keys representing filter fields and values as lists of strings for filtering criteria.

Returns:

A list of MemoryNode objects sorted by relevance to the query,

limited to top_k items.

Return type:

List[MemoryNode]

async a_retrieve_memories(query: str = '', top_k: int = 3, filter_dict: Dict[str, List[str]] | None = None) → List[MemoryNode]

Asynchronously retrieves a list of MemoryNode objects that best match the query, respecting a filter dictionary, with the result size capped at top_k.

Parameters:

• query (str) – The text to search for in memory nodes.

• top_k (int) – Maximum number of nodes to return.

• filter_dict (Dict[str, List[str]]) – Filters to apply on memory nodes.

Returns:

A list of up to top_k MemoryNode objects matching the criteria.

Return type:

List[MemoryNode]

batch_insert(nodes: List[MemoryNode])

batch_update(nodes: List[MemoryNode], update_embedding: bool = True)

batch_delete(nodes: List[MemoryNode])

close()

Closes the memory store, releasing any resources associated with it. Subclasses must implement this method to define how the memory store is properly closed.