Vertex AI Vector Search
A RocketRide tool node that looks up nearest neighbors in a Google Cloud Vertex AI Vector Search index. Pick it when an agent already has an embedding vector and needs the matching IDs out of an index that is deployed and managed in Vertex AI.
About Vertex AI Vector Search
Vertex AI is Google Cloud's managed platform for machine-learning models and the services around them. Vector Search, formerly called Matching Engine, is its approximate-nearest-neighbor service: an index of embedding vectors is built, then deployed onto an index endpoint that answers similarity queries at low latency. Applications on Google Cloud use it as the retrieval layer behind semantic search and recommendations.
What it does
The node connects to one deployed Vertex AI Vector Search index when the pipeline starts and holds that endpoint open for the run. It has no data lanes and no invoke connections: its entire surface is a single nearest-neighbor lookup offered to a connected agent. Reach for it when the index already lives in Vertex AI and the pipeline only needs to query it.
It is a query-only tool, not a vector-store adapter. There is no way to add, upsert, or delete vectors through this node, and it does not embed text — the caller supplies the query vector, and indexing stays in Vertex AI.
As a tool
The server-name prefix is vertex, producing this registered function.
| Function | Description |
|---|---|
search | Return the nearest neighbors of a supplied embedding vector. |
search requires query_vector, an array of numbers holding the query embedding. top_k sets how many neighbors to request and falls back to 10 when it is omitted, zero, or not a number. score_threshold is optional and defaults to 0.0.
A successful call returns a list of {id, distance} objects, one per neighbor, in the order Vertex AI returned them. Failures are not raised: a disconnected index endpoint or an error from the Vertex AI call comes back as a one-item list holding a single error key, so an agent should check for that key before treating the result as neighbors.
score_threshold is applied by the node after Vertex AI answers, and only when the value is greater than zero — a zero or negative threshold filters nothing. Neighbors whose distance is below the threshold are dropped, which assumes similarity semantics where a higher number is a better match, such as an index built with DOT_PRODUCT_DISTANCE. It is wrong for a distance metric such as SQUARED_L2_DISTANCE, where a lower number is the better match and thresholding this way discards the closest results. Because the filter runs locally on the top_k neighbors Vertex AI already returned, a threshold can return fewer than top_k results and never more.
Configuration
Point the node at one deployed index: the region it lives in, the index endpoint, and the deployed index on that endpoint. Those three, plus the credential settings under Authentication, are the whole configuration — there is a single profile and nothing else to choose.
Index Endpoint ID and Deployed Index ID
These two identify the exact index the tool queries, and both are required — startup fails with an explicit error when either is blank, and configuration validation warns about each one separately while you are still editing. The index endpoint is the deployed serving resource; the deployed index ID names one of the indexes deployed onto it, since an endpoint can carry several. Take both from the Vertex AI console rather than guessing: the deployed index ID is not the index's own resource ID.
Location
The Google Cloud region holding the index endpoint, defaulting to us-central1. It must match the region the endpoint was created in — a valid endpoint ID looked up in the wrong region simply will not be found. Change it whenever the index lives elsewhere, for example europe-west4.
Authentication
The node uses RocketRide's shared Google Cloud credential resolution and requests the https://www.googleapis.com/auth/cloud-platform scope.
Authentication Type selects between Application Default Credentials and Service Account JSON. Application Default Credentials is the default and suits an engine running on Google Cloud infrastructure with an attached service account, or any host where ADC has already been provisioned. Selecting Service Account JSON reveals Service Account Key JSON, an upload field for the key file; it is stored as a secret and is required in that mode.
Project ID is optional. Left blank, the project is taken from the uploaded key file or from the ambient default credentials; set it explicitly when the credentials could resolve to a different project than the one holding the index.
Grant the credential enough IAM to read the index endpoint and query the deployed index.
Limitations
Declared noremote: this node runs on the local engine host only and is not available for remote execution. It needs network access to the Vertex AI API and, in Application Default Credentials mode, to whatever credential source the host provides.
Notes
Startup checks
Connecting builds the index endpoint handle with the resolved project, region, and credentials passed in directly; the node deliberately avoids aiplatform.init(), which would mutate process-global SDK state and affect other nodes in the same runtime. It then lists the endpoint's deployed indexes and fails startup when the configured deployed index ID is not among them, so a wrong ID surfaces at pipeline start instead of as empty search results later. In configuration-only open mode the node skips connecting entirely.
Missing dependency
google-cloud-aiplatform is imported optionally, and its absence is reported as an explicit ImportError when the node starts rather than as a confusing failure on the first tool call.
Upstream docs
Schema
| Field | Type | Description | Default |
|---|---|---|---|
vertex.deployedIndexId | string | Deployed Index ID The ID of the deployed index. | |
vertex.indexEndpointId | string | Index Endpoint ID The ID of the Vector Search Index Endpoint. | |
vertex.location | string | Location The Google Cloud region, e.g. us-central1. | "us-central1" |
vertex.profile | string | "default" |
Dependencies
google-auth>=2.23.3google-cloud-aiplatform>=1.40.0