Graph Memory FAQs

Question 1

What tools are available for AI agents to interact with Graph Memory?

Accepted Answer

AI agents interact through a set of dedicated tools. These include functions like `memory_create_entities`, `memory_create_relations`, `memory_add_observations`, and `memory_search_nodes` to build, query, and manage the knowledge graph elements effectively.

Question 2

Does Graph Memory include any data safety features?

Accepted Answer

Yes, Graph Memory incorporates a `bm_gm` safety system. It utilizes specific naming conventions for directories and tools, and crucially, every memory file must begin with a unique safety marker (`_bm_gm`) to prevent data corruption during writes.

Question 3

What is Graph Memory?

Accepted Answer

Graph Memory provides a persistent, indexed knowledge graph specifically designed for AI agents. It enables AI to store, retrieve, and organize information using entities, relationships, and observations for enhanced intelligence and context.

Question 4

What is the role of the 'main' database in Graph Memory?

Accepted Answer

The 'main' database acts as the core index and routing table for your AI's entire memory system. It stores critical, high-level information and a manifest of all other specialized memory contexts, ensuring this essential data is always visible to the AI.

Question 5

How does Graph Memory organize specialized information?

Accepted Answer

Graph Memory uses 'contexts' to organize specialized information. These are separate memory files for specific topics (e.g., 'work', 'personal', 'project-alpha'), allowing for detailed, topic-specific storage while keeping the 'main' database focused on core indexing.

Graph Memory

Graph Memory

Características Principales

Casos de Uso

Características Principales

Casos de Uso