Tool Infrastructure
One authority for reusable vector infrastructure. These settings are consumed by multiple agent subsystems rather than belonging to Tool Retrieval alone.
Embedding
configured ·
text-embedding-qwen3-embedding-4bNative vector store
healthy · native-sqlite
Vector collections
4
Config
a56ef2fa9aa0b03bEmbedding service
Shared OpenAI-compatible embedding authority used by tool search, procedure search, context/chat recall, semantic entities, and memory stores.
Last successful embedding: — · dimensions: —
Native vector storage
The shared runtime uses an in-process SQLite vector store for context, tool, procedure, chat, and semantic-entity vectors. This page reports the persistent local topology.
Shared vector collections (4)
context_4ebe9306c3798242 procedure_4ebe9306c3798242 tool_active_4ebe9306c3798242 workflow_run_4ebe9306c3798242
Memory stores intentionally retain isolated vector databases under
/context/memory_stores/<store_id>/vectors. They use this shared embedding service but do not share one memory-vector collection.Consumers
Changing the embedding model changes the vector space used by these consumers. Derived indexes rebuild or migrate according to their own contracts.
| Consumer | Embedding | Vector storage | Notes |
|---|---|---|---|
| Tool Retrieval | shared | shared vector store | semantic candidate generation; deterministic rank remains on Tool Retrieval |
| Procedure Search | shared | shared vector store | verified procedure semantic index |
| Context Retrieval | shared | shared vector store | indexed context chunks |
| Workflow runs / semantic recall | shared | shared vector store | sealed WorkflowRunRecord and semantic-entity vectors; raw chat is not indexed |
| Memory stores | shared | isolated per-store vector store | memory settings enforce model/dimension compatibility |