The app id that the knowledge base belongs to.
The model name that should be used when asking questions of this knowledge base.
OptionalcontextualLifetime LLM usage of the contextual-RAG situating-blurb calls on this KB (server-managed; ignored on upsert). Persisted on the KB itself so the record survives Core restarts and covers any vector store. Under the combined-ingest strategy this stays ≈0 — growth is a visible fallback-rate signal.
The user's description of the knowledge base
The embedding model that should be used for this knowledge base.
OptionalgraphOpt-in GraphRAG configuration. Only honored for vectorDbType:'mongoAtlas' KBs; enables
per-chunk entity/relationship extraction at ingest and searchMode:'graph' at query time.
The unique identifier of the knowledge base.
A set of predefined metadata fields for the knowledge base that can be used for filtering.
OptionalragDefault RAG strategy for newly ingested contexts; a per-request options.ragType overrides it.
Omitted ⇒ the server default ('basic'). Changing it affects future ingests only — existing chunks
are not re-processed.
The timestamp the knowledge base was last updated
OptionalvectorThe vector store backend this knowledge base reads/writes from. Set at creation (defaulting to
the server's SQUID_DEFAULT_VECTOR_DB_TYPE, otherwise 'postgres') and immutable thereafter.
Optional on the read type for backwards compatibility with older records.
Represents an AI knowledge base that can be attached to an AI agent.