Vertex Ai

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Overview

Client-mode REST API connectors for Google Gemini: triage alarms and summarize shift logs with generateContent (structured JSON output), create embeddings, count tokens and list models with a Gemini API key, run Gemini and custom anomaly models on Vertex AI (predict on your endpoint), and get Google OAuth 2.0 access tokens. This is one of the templates in the Google Gemini API and Vertex AI REST API app (google-gemini-api-and-vertex-ai). Deploy it alongside the other connectors of that app when they depend on each other (for example a token connector plus an API connector).

Auth

Gemini API: header x-goog-api-key {value.json.api_key} (Google AI Studio / Cloud API key; Hub secret GEMINI_API_KEY via GET SECRET). Vertex AI: Authorization: Bearer {value.json.access_token}, OAuth 2.0 access token with scope https://www.googleapis.com/auth/cloud-platform for an identity with roles/aiplatform.user (~1 h lifetime); GoogleOAuthToken connector gets it (refresh_token grant with client id/secret/refresh token, or service-account JWT bearer grant with a JWT signed outside the broker). Hub secrets GEMINI_API_KEY, GOOGLE_OAUTH_CLIENT_ID, GOOGLE_OAUTH_CLIENT_SECRET, GOOGLE_OAUTH_REFRESH_TOKEN. Never commit keys, tokens or service-account JSON. Auth headers used by the template: Authorization: Bearer {value.json.access_token}.

Template parameters

Placeholder	Type	Description	Required
`RouteName`	string	Name of the Vertex Ai connector	no
`BaseUrl`	string	Vertex Ai base URL without trailing slash (e.g. https://YOUR_REGION-aiplatform.googleapis.com)	yes

BASE_ADDRESS default: https://YOUR_REGION-aiplatform.googleapis.com.

Events

Event	Method	Endpoint	Request topic	Response topic	Payload fields
`VertexGenerateContent`	POST	`/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/publishers/google/models/{value.json.model}:generateContent`	`ai/gemini/vertex-content/generate`	`ai/gemini/vertex-content/generate/response`	`access_token`, `body`, `model`
`VertexCountTokens`	POST	`/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/publishers/google/models/{value.json.model}:countTokens`	`ai/gemini/vertex-tokens/count`	`ai/gemini/vertex-tokens/count/response`	`access_token`, `body`, `model`
`VertexEmbedPredict`	POST	`/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/publishers/google/models/{value.json.model}:predict`	`ai/gemini/vertex-embedding/predict`	`ai/gemini/vertex-embedding/predict/response`	`access_token`, `body`, `model`
`VertexEndpointPredict`	POST	`/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/endpoints/{value.json.endpoint_id}:predict`	`ai/gemini/vertex-endpoint/predict`	`ai/gemini/vertex-endpoint/predict/response`	`access_token`, `body`, `endpoint_id`
`VertexListEndpoints`	GET	`/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/endpoints?pageSize={value.json.page_size}`	`ai/gemini/vertex-endpoint/list`	`ai/gemini/vertex-endpoint/list/response`	`access_token`, `page_size`
`VertexGetEndpoint`	GET	`/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/endpoints/{value.json.endpoint_id}`	`ai/gemini/vertex-endpoint/get`	`ai/gemini/vertex-endpoint/get/response`	`access_token`, `endpoint_id`

Deploy

Get the template card (JSON with template and metadata) from the broker, then deploy the connector:

mosquitto_pub -t '$SYS/Coreflux/Command' -m "-connectorCode VERTEX_AI"

The deployable connector from the REST API app, with BASE_ADDRESS already filled in:

DEFINE CONNECTOR VertexAiRestApi WITH TYPE REST_API
    ADD REST_API_CONFIG
        WITH BASE_ADDRESS "https://YOUR_REGION-aiplatform.googleapis.com"
        WITH ENABLE_CLIENT "true"
        WITH USE_SSL "true"
        WITH REQUEST_TIMEOUT '120'
        WITH DEFAULT_CONTENT_TYPE "application/json"
    ADD EVENT VertexGenerateContent
        WITH SOURCE_TOPIC "ai/gemini/vertex-content/generate"
        WITH DESTINATION_TOPIC "ai/gemini/vertex-content/generate/response"
        WITH METHOD "POST"
        WITH ENDPOINT "/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/publishers/google/models/{value.json.model}:generateContent"
        WITH HEADERS
            ADD "Accept" "application/json"
            ADD "Content-Type" "application/json"
            ADD "Authorization" "Bearer {value.json.access_token}"
        WITH BODY "{value.json.body}"
    ADD EVENT VertexCountTokens
        WITH SOURCE_TOPIC "ai/gemini/vertex-tokens/count"
        WITH DESTINATION_TOPIC "ai/gemini/vertex-tokens/count/response"
        WITH METHOD "POST"
        WITH ENDPOINT "/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/publishers/google/models/{value.json.model}:countTokens"
        WITH HEADERS
            ADD "Accept" "application/json"
            ADD "Content-Type" "application/json"
            ADD "Authorization" "Bearer {value.json.access_token}"
        WITH BODY "{value.json.body}"
    ADD EVENT VertexEmbedPredict
        WITH SOURCE_TOPIC "ai/gemini/vertex-embedding/predict"
        WITH DESTINATION_TOPIC "ai/gemini/vertex-embedding/predict/response"
        WITH METHOD "POST"
        WITH ENDPOINT "/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/publishers/google/models/{value.json.model}:predict"
        WITH HEADERS
            ADD "Accept" "application/json"
            ADD "Content-Type" "application/json"
            ADD "Authorization" "Bearer {value.json.access_token}"
        WITH BODY "{value.json.body}"
    ADD EVENT VertexEndpointPredict
        WITH SOURCE_TOPIC "ai/gemini/vertex-endpoint/predict"
        WITH DESTINATION_TOPIC "ai/gemini/vertex-endpoint/predict/response"
        WITH METHOD "POST"
        WITH ENDPOINT "/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/endpoints/{value.json.endpoint_id}:predict"
        WITH HEADERS
            ADD "Accept" "application/json"
            ADD "Content-Type" "application/json"
            ADD "Authorization" "Bearer {value.json.access_token}"
        WITH BODY "{value.json.body}"
    ADD EVENT VertexListEndpoints
        WITH SOURCE_TOPIC "ai/gemini/vertex-endpoint/list"
        WITH DESTINATION_TOPIC "ai/gemini/vertex-endpoint/list/response"
        WITH METHOD "GET"
        WITH ENDPOINT "/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/endpoints?pageSize={value.json.page_size}"
        WITH HEADERS
            ADD "Accept" "application/json"
            ADD "Authorization" "Bearer {value.json.access_token}"
    ADD EVENT VertexGetEndpoint
        WITH SOURCE_TOPIC "ai/gemini/vertex-endpoint/get"
        WITH DESTINATION_TOPIC "ai/gemini/vertex-endpoint/get/response"
        WITH METHOD "GET"
        WITH ENDPOINT "/v1/projects/YOUR_PROJECT_ID/locations/YOUR_REGION/endpoints/{value.json.endpoint_id}"
        WITH HEADERS
            ADD "Accept" "application/json"
            ADD "Authorization" "Bearer {value.json.access_token}"

Deploy it with -addConnector (do not include ADD METADATA).

Usage example

Call VertexGenerateContent by publishing a JSON payload to its request topic, and read the reply on the response topic:

mosquitto_sub -t 'ai/gemini/vertex-content/generate/response' &
mosquitto_pub -t 'ai/gemini/vertex-content/generate' -m '{"access_token": "<access_token>", "body": {}, "model": "<model>"}'

Last modified on October 26, 2026

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