Vector Store Q&A Tool

Node catalog Artificial intelligence

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Answer questions from a vector store

Usage and specifics

Connect this tool to an agent tool port. name and description help the model select it; configure sources, templates and limits before calling. requireApproval, where available, controls operations requiring approval.

Technical type : ai_tool_vector_qa. Runtime : nodulz.

Credentials and prerequisites

Create and configure the credential : ai-model

Create credentials in your nodulz instance’s Credentials area, then select them on the node. Availability depends on ownership and sharing. See the credentials guide for access and rotation.

Parameters

Names below are technical keys. Defaults are not a ready-to-run configuration: complete fields required by your operation. Paths containing [] describe list items; some fields depend on the selected mode.

Parameter	Type	Default	Values / limits
`name`	`string`	`"vector_qa"`	-
`description`	`string`	`"Answer from vector store"`	-
`storeSource`	`string`	`""`	-
`credentialId`	`string`	-	-
`model`	`string`	`""`	-
`embeddingModel`	`string`	`"text-embedding-3-small"`	-
`embeddingCredentialId`	`string`	-	-

Initial configuration

Initial catalog configuration example, to adapt before running. Keep secrets in credentials.

json

{
  "name": "vector_qa",
  "description": "Answer from vector store",
  "storeSource": "",
  "model": "",
  "embeddingModel": "text-embedding-3-small"
}

Verification

Test with representative data. Check node output in the inspector and logs, then use editor mapping for downstream fields. A trigger test with a simulated payload does not validate external service delivery.