Overview
The SearchMemoriesOptions interface allows you to refine how the memory engine retrieves and ranks results. It is used as the optional second argument in the MemMachineMemory.search() method.
Properties
All properties in this interface are optional.
| Property | Type | Description |
|---|
top_k | number | The maximum number of relevant memories to return. |
score_threshold | number | The minimum similarity score required for a memory to be included in results. |
filter | string | A metadata-based filter string to narrow the search scope. |
expand_context | number | The number of surrounding chronological episodes to retrieve for each hit. |
types | MemoryType[] | Restricts the search to specific memory classifications (e.g., semantic). |
Usage Example
The following example demonstrates how to perform a filtered search with a specific limit and context expansion.
import { SearchMemoriesOptions } from '@memmachine/client';
const memory = project.memory();
const searchConfig: SearchMemoriesOptions = {
top_k: 5,
score_threshold: 0.75,
expand_context: 2, // Get 2 messages before and after each hit
types: ['episodic']
};
const results = await memory.search(
'What are the user preferences for UI themes?',
searchConfig
);
Use expand_context when you need the LLM to understand the conversation flow surrounding a specific memory hit, rather than just the hit itself.
