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MemoryMesh is a local knowledge graph server for AI models, especially suited for text-based RPGs, enabling structured memory and dynamic interactions.
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MemoryMesh is a local knowledge graph server for AI models, especially suited for text-based RPGs, enabling structured memory and dynamic interactions.
MemoryMesh is relatively safe in isolated environments with trusted users. However, the lack of authentication and potential for destructive operations make it risky in multi-user or untrusted environments. Ensure schemas are well-defined to limit potential damage from AI interactions.
Performance depends on the size of the knowledge graph and the complexity of the schemas. Large graphs may require optimization for efficient querying and updates. Memory usage can become a factor with very large graphs.
Since MemoryMesh is a local server, there are no direct API call costs. However, consider the computational resources required to run the server and the potential cost of data storage.
npx -yadd_npcAdds a new NPC node to the knowledge graph.
Adds data to the graph, but is constrained by the schema.
update_npcUpdates an existing NPC node in the knowledge graph.
Modifies existing data, potentially causing inconsistencies.
delete_npcDeletes an NPC node from the knowledge graph.
Irreversibly removes data from the graph.
add_locationAdds a new location node to the knowledge graph.
Adds data to the graph, but is constrained by the schema.
update_locationUpdates an existing location node in the knowledge graph.
Modifies existing data, potentially causing inconsistencies.
delete_locationDeletes a location node from the knowledge graph.
Irreversibly removes data from the graph.
None
cloud
MemoryMesh is relatively safe in isolated environments with trusted users. However, the lack of authentication and potential for destructive operations make it risky in multi-user or untrusted environments. Ensure schemas are well-defined to limit potential damage from AI interactions.
AI agents have full read/write access to the knowledge graph by default, with no sandboxing or rollback mechanisms. Exercise caution when granting autonomy.
Production Tip
Implement robust schema validation and monitoring to prevent data corruption and ensure the integrity of the knowledge graph.
Schema files (.schema.json) should be placed in the `dist/data/schemas` directory.
Use the Memory Viewer tool, a standalone web application, to visualize and inspect the `memory.json` file.
Relationships are defined in the schemas using the `relationship` property, which specifies the `edgeType` and `description` of the connection.
Yes, MemoryMesh is adaptable and can be used for various applications involving structured data, such as social network simulations or organizational planning.
No, MemoryMesh does not have built-in authentication or access control mechanisms.
Define clear and restrictive schemas, and monitor the event system to track modifications. Consider implementing validation on the AI's output before applying changes.
MemoryMesh provides error feedback to the AI, allowing it to learn from mistakes and adjust its interactions.