Memories

What are Memories?

Memories are discrete pieces of information extracted from user conversations. They complement traits by storing:

Specific facts that don’t fit trait schemas
Events and experiences mentioned
Contextual information for future conversations

Memory Structure

interface Memory {
  id: string;
  profileId: string;
  content: string;          // The extracted information
  type: 'fact' | 'preference' | 'event' | 'context';
  importance: number;       // 0.0 - 1.0
  decayFactor: number;      // Decreases over time
  sourceMessageIds: string[];
  createdAt: Date;
  lastAccessedAt: Date | null;
}

Memory Types

Fact

Concrete information: “Works at Acme Corp as a senior engineer”

Preference

Likes and dislikes: “Prefers dark mode IDEs”

Event

Things that happened: “Started a new project last week”

Context

Situational info: “Currently debugging a production issue”

Importance Scoring

Memories are scored by likely future relevance:

Score	Description	Examples
0.8+	Core identity/role	Job title, primary tech stack
0.6-0.8	Ongoing projects	Current goals, active work
0.4-0.6	Preferences	Tool preferences, working style
< 0.4	Ephemeral context	Today’s specific task

Memory Decay

Over time, memories become less relevant. The decayFactor (starting at 1.0) decreases:

Unused memories decay faster
Accessed memories are “refreshed”
Low importance memories decay faster

This ensures recent and frequently-relevant information takes priority.

Memory Retrieval

When building context for a request, GetProfile retrieves memories based on:

Recency: More recent memories score higher
Importance: Higher importance memories are prioritized
Relevance: (Future) Semantic similarity to the current query
Access patterns: Frequently accessed memories are boosted

Example: Memory Extraction

Given this conversation:

User: I'm working on migrating our monolith to microservices at work. 
      We're using Kubernetes and having some issues with the service mesh.
      By the way, I'll be on vacation next week.

GetProfile extracts:

[
  {
    "content": "Working on migrating a monolith to microservices",
    "type": "event",
    "importance": 0.8
  },
  {
    "content": "Uses Kubernetes at work",
    "type": "fact",
    "importance": 0.7
  },
  {
    "content": "Experiencing issues with service mesh",
    "type": "context",
    "importance": 0.6
  },
  {
    "content": "Will be on vacation next week",
    "type": "event",
    "importance": 0.4
  }
]

Deduplication

GetProfile automatically handles duplicate memories:

Identical content is merged
Similar memories may be consolidated
Source messages are aggregated

Getting Started

Core Concepts

Client SDKs

Configuration

Deployment

What are Memories?

Memory Structure

Memory Types

Fact

Preference

Event

Context

Importance Scoring

Memory Decay

Memory Retrieval

Example: Memory Extraction

Deduplication

​What are Memories?

​Memory Structure

​Memory Types

Fact

Preference

Event

Context

​Importance Scoring

​Memory Decay

​Memory Retrieval

​Example: Memory Extraction

​Deduplication

What are Memories?

Memory Structure

Memory Types

Importance Scoring

Memory Decay

Memory Retrieval

Example: Memory Extraction

Deduplication