memory-onboard

To onboard a software project into a knowledge graph, you can automate the integration by defining the project scope, designing a schema with template packs, and ingesting initial documentation like READMEs via CLI commands. This ensures structured data capture and proper configuration of LLM providers.

Schema design for a memory knowledge graph involves creating and deploying a custom template pack tailored to your project's entities and relationships. It defines how core components like services and APIs are represented as structured objects for discoverability.

You can ingest project documents to populate a knowledge graph by using CLI commands to upload files like architecture diagrams. This facilitates automatic knowledge extraction and maps the defined relationships into the structured memory project.

Configuring an LLM provider is required before setting up a memory project. The onboarding process ensures proper configuration of Memory projects, LLM providers, and template pack installation to enable automatic knowledge extraction from your codebase.

Yes, you can use CLI commands to establish relationships between project services. The onboarding process connects your codebase to a Memory project, allowing you to define core components and their dependencies as structured objects in the graph.

The best way to automate project setup for a memory platform is to use a guided onboarding skill that configures the project scope, installs template packs for schema design, and triggers initial data ingestion through CLI commands.