Google Vertex AI

Google Vertex AI is a machine learning platform that simplifies the process of building, deploying, and scaling ML models.

Google Vertex AI is a comprehensive AI platform that enables the development and deployment of machine learning models at scale. This connector allows Swimlane Turbine users to leverage Google Vertex AI's advanced capabilities for interacting with AI models, engaging in conversations, and querying reasoning engines. By integrating with Google Vertex AI, Swimlane Turbine users can enhance their security automation workflows with powerful AI-driven insights and actions, enabling more efficient threat detection and response.

Limitations

None to date.

Supported Versions

This Google Vertex AI connector uses the v1 API.

Additional Documents

Documentation Google Vertex AI

Configuration

Prerequisites

Before you can use the Google Vertex AI connector for Turbine, you'll need access to the Google Vertex AI API. This requires the following:

OAuth2.0 authentication using the following parameters:

Service Account Info: JSON key file for service account authentication.

URL: Endpoint URL for accessing Google Vertex AI services.

Scopes: Permissions required for accessing specific Google Cloud resources.

Authentication Methods

Service Account Info: Base64-encoded JSON key file for service account authentication.

URL: Endpoint URL for accessing Google Vertex AI services.

Scopes: Permissions required for accessing specific resources within Google Vertex AI.

Setup instructions

In Google Cloud, enable the Vertex AI API for your project.

Create or select a service account that can invoke Vertex AI reasoning engine endpoints.

Generate a JSON key for that service account.

Base64 encode the full JSON key file and use that value for Service Account Info.

Example: base64 -i service-account.json | tr -d '\n'

Set URL to your Vertex AI base endpoint, for example:

https://us-central1-aiplatform.googleapis.com

Set Scopes with at least:

https://www.googleapis.com/auth/cloud-platform

If authentication fails, verify the service account roles, decoded JSON validity, endpoint region, and scope list.

Capabilities

This Connector provides the following capabilities:

Ask Vertex

Chat with Claude using Vertex AI

Reasoning Engines Query

Reasoning Engines Stream Query

Reasoning Engines Query

Queries using a reasoning engine Click Here

Reasoning Engines Stream Query

Streams queries using a reasoning engine Click Here.

Ask Vertex

Ask Vertex is a tool that allows you to ask questions to a model Click Here.

Configurations

Google Vertex AI

OAuth2.0 authentication for Google Vertex AI.

Configuration Parameters

Parameter	Description	Type	Required
b64_service_info	Base64-encoded bk_credentials JSON authentication file contents.	string	Required
url	Server API Address.	string	Required
scopes	Scope to be used for authentication.	array	Required
verify_ssl	Verify SSL certificate	boolean	Optional
http_proxy	A proxy to route requests through.	string	Optional

Actions

Ask Vertex

Interact with a Google Vertex AI model by asking questions. Requires project, location, and model as path parameters, and contents in the JSON body.

Endpoint

URL: v1/projects/{{project}}/locations/{{location}}/publishers/google/models/{{model}}:generateContent

Method: POST

Input

Argument Name	Type	Required	Description
path_parameters.project	string	Required	The project ID of the project to use.
path_parameters.location	string	Required	The location of the project to use.
path_parameters.model	string	Required	The model to use.
contents	array	Optional	Response content
contents.role	string	Optional	Response content
contents.parts	array	Optional	Response content
contents.parts.text	string	Optional	Response content
cachedContent	string	Optional	Response content
tools	array	Optional	Parameter for Ask Vertex
tools.functionDeclarations	object	Optional	Parameter for Ask Vertex
tools.functionDeclarations.name	string	Optional	Name of the resource
tools.functionDeclarations.description	string	Optional	Parameter for Ask Vertex
toolConfig	object	Optional	Parameter for Ask Vertex
toolConfig.functionCallingConfig	object	Optional	Parameter for Ask Vertex
toolConfig.retrievalConfig	object	Optional	Parameter for Ask Vertex
labels	object	Optional	Parameter for Ask Vertex
labels.key	string	Optional	Parameter for Ask Vertex
safetySettings	array	Optional	Parameter for Ask Vertex
safetySettings.category	string	Optional	Parameter for Ask Vertex
safetySettings.method	string	Optional	HTTP method to use
safetySettings.threshold	string	Optional	Parameter for Ask Vertex
modelArmorConfig	object	Optional	Parameter for Ask Vertex
modelArmorConfig.promptTemplateName	string	Optional	Name of the resource
modelArmorConfig.responseTemplateName	string	Optional	Name of the resource
generationConfig	object	Optional	Parameter for Ask Vertex

Input Example

{"json_body":{"contents":[{"role":"user","parts":[{"text":"What is the capital of France?"}]}],"cachedContent":"projects/{project}/locations/{location}/cachedContents/{cachedContent}","tools":[{"functionDeclarations":{"name":"get_current_weather","description":"Get the current weather for a given location"}}],"toolConfig":{"functionCallingConfig":{},"retrievalConfig":{}},"labels":{"key":"value"},"safetySettings":[{"category":"HARM_CATEGORY_HATE_SPEECH","method":"HARM_BLOCK_METHOD_UNSPECIFIED","threshold":"HARM_BLOCK_THRESHOLD_UNSPECIFIED"}],"modelArmorConfig":{"promptTemplateName":"","responseTemplateName":""},"generationConfig":{"temperature":0.7,"maxOutputTokens":1024},"systemInstruction":{}},"path_parameters":{"project":"project-8bb1fbea-bfe5-4ef6-a06","location":"us-central1","model":"gemini-2.5-flash"}}

Output

Parameter	Type	Description
status_code	number	HTTP status code of the response
reason	string	Response reason phrase
candidates	array	Unique identifier
candidates.content	object	Unique identifier
candidates.content.role	string	Unique identifier
candidates.content.parts	array	Unique identifier
candidates.content.parts.text	string	Unique identifier
candidates.finishReason	string	Unique identifier
candidates.avgLogprobs	number	Unique identifier
usageMetadata	object	Response data
usageMetadata.promptTokenCount	number	Response data
usageMetadata.candidatesTokenCount	number	Response data
usageMetadata.totalTokenCount	number	Response data
usageMetadata.trafficType	string	Response data
usageMetadata.promptTokensDetails	array	Response data
usageMetadata.promptTokensDetails.modality	string	Response data
usageMetadata.promptTokensDetails.tokenCount	number	Response data
usageMetadata.candidatesTokensDetails	array	Response data
usageMetadata.candidatesTokensDetails.modality	string	Response data
usageMetadata.candidatesTokensDetails.tokenCount	number	Response data
usageMetadata.thoughtsTokenCount	number	Response data
modelVersion	string	Output field: modelVersion
createTime	string	Time value
responseId	string	Unique identifier

Output Example

{"status_code":200,"response_headers":{"Content-Type":"application/json; charset=UTF-8","Vary":"Origin, X-Origin, Referer","Content-Encoding":"gzip","Date":"Wed, 29 Apr 2026 07:09:08 GMT","Server":"scaffolding on HTTPServer2","X-XSS-Protection":"0","X-Frame-Options":"SAMEORIGIN","X-Content-Type-Options":"nosniff","Alt-Svc":"h3=\":443\"; ma=2592000,h3-29=\":443\"; ma=2592000","Transfer-Encoding":"chunked"},"reason":"OK","json_body":{"candidates":[{}],"usageMetadata":{"promptTokenCount":7,"candida...

Chat with Claude using Vertex AI

Engage in a conversation with Claude using Google Vertex AI. Requires project, location, and model as path parameters, and anthropic_version, messages, and max_tokens in the JSON body.

Endpoint

URL: v1/projects/{{project}}/locations/{{location}}/publishers/anthropic/models/{{model}}:rawPredict

Method: POST

Input

Argument Name	Type	Required	Description
path_parameters.project	string	Required	The project ID of the project to use.
path_parameters.location	string	Required	The location of the project to use.
path_parameters.model	string	Required	The model to use.
anthropic_version	string	Optional	The version of the Anthropic API to use.
messages	array	Optional	The messages to send to the model.
messages.role	string	Required	The role of the message.
messages.content	string	Required	The content of the message.
max_tokens	number	Optional	The maximum number of tokens to generate.
temperature	number	Optional	The temperature to use for the generation.

Input Example

{"json_body":{"anthropic_version":"vertex-2023-10-16","messages":[{"role":"user","content":"Hello, how are you?"}],"max_tokens":1024,"temperature":0.7},"path_parameters":{"project":"project-8bb1fbea-bfe5-4ef6-a06","location":"global","model":"claude-sonnet-4-6"}}

Output

Parameter	Type	Description
status_code	number	HTTP status code of the response
reason	string	Response reason phrase

Output Example

{"status_code":200,"response_headers":{"Content-Type":"application/json; charset=UTF-8","Vary":"Origin, X-Origin, Referer","Content-Encoding":"gzip","Date":"Tue, 28 Apr 2026 07:43:52 GMT","Server":"scaffolding on HTTPServer2","X-XSS-Protection":"0","X-Frame-Options":"SAMEORIGIN","X-Content-Type-Options":"nosniff","Alt-Svc":"h3=\":443\"; ma=2592000,h3-29=\":443\"; ma=2592000","Transfer-Encoding":"chunked"},"reason":"OK","json_body":{}}

Reasoning Engines Query

Query a reasoning engine in Google Vertex AI using specified project, location, and reasoning engine path parameters.

Endpoint

URL: v1/projects/{{project}}/locations/{{location}}/reasoningEngines/{{reasoningEngine}}:query

Method: POST

Input

Argument Name	Type	Required	Description
path_parameters.project	string	Required	The project ID.
path_parameters.location	string	Required	The location of the project.
path_parameters.reasoningEngine	string	Required	The reasoning engine ID.
classMethod	string	Optional	The method to call on the class.
input	object	Optional	Input data for the action
input.input	object	Optional	Input data for the action
input.input.text	string	Optional	The text to query.

Input Example

{"path_parameters":{"project":"project-8bb1fbea-bfe5-4ef6-a06","location":"us-central1","reasoningEngine":"8068625892701634560"}}

Output

Parameter	Type	Description
status_code	number	HTTP status code of the response
reason	string	Response reason phrase
output	object	Output field: output
output.result	number	Result of the operation

Output Example

{"status_code":200,"response_headers":{"Content-Type":"application/json; charset=UTF-8","Vary":"Origin, X-Origin, Referer","Content-Encoding":"gzip","Date":"Tue, 28 Apr 2026 07:43:52 GMT","Server":"scaffolding on HTTPServer2","X-XSS-Protection":"0","X-Frame-Options":"SAMEORIGIN","X-Content-Type-Options":"nosniff","Alt-Svc":"h3=\":443\"; ma=2592000,h3-29=\":443\"; ma=2592000","Transfer-Encoding":"chunked"},"reason":"OK","json_body":{"output":{"result":12}}}

Reasoning Engines Stream Query

Stream queries using a reasoning engine in Google Vertex AI. Requires path parameters: project, location, and reasoningEngine.

Endpoint

URL: v1/projects/{{project}}/locations/{{location}}/reasoningEngines/{{reasoningEngine}}:streamQuery

Method: POST

Input

Argument Name	Type	Required	Description
path_parameters.project	string	Required	The project ID.
path_parameters.location	string	Required	The location of the project.
path_parameters.reasoningEngine	string	Required	The reasoning engine ID.
classMethod	string	Optional	The method to call on the class.
input	object	Optional	Input data for the action
input.input	object	Optional	The input to the method.
input.input.text	string	Optional	The text to query.

Input Example

{"path_parameters":{"project":"project-8bb1fbea-bfe5-4ef6-a06","location":"us-central1","reasoningEngine":"2751000632683921408"}}

Output

Parameter	Type	Description
status_code	number	HTTP status code of the response
reason	string	Response reason phrase
output	object	Output field: output
output.result	number	Result of the operation

Output Example

{"status_code":200,"response_headers":{"Content-Type":"application/json; charset=UTF-8","Vary":"Origin, X-Origin, Referer","Content-Encoding":"gzip","Date":"Tue, 28 Apr 2026 07:43:52 GMT","Server":"scaffolding on HTTPServer2","X-XSS-Protection":"0","X-Frame-Options":"SAMEORIGIN","X-Content-Type-Options":"nosniff","Alt-Svc":"h3=\":443\"; ma=2592000,h3-29=\":443\"; ma=2592000","Transfer-Encoding":"chunked"},"reason":"OK","json_body":{"output":{"result":12}}}

Response Headers

Header	Description	Example
Alt-Svc	HTTP response header: Alt-Svc	h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
Content-Encoding	HTTP response header: Content-Encoding	gzip
Content-Type	The media type of the resource	application/json; charset=UTF-8
Date	The date and time at which the message was originated	Wed, 29 Apr 2026 07:09:08 GMT
Server	Information about the software used by the origin server	scaffolding on HTTPServer2
Transfer-Encoding	HTTP response header: Transfer-Encoding	chunked
Vary	HTTP response header: Vary	Origin, X-Origin, Referer
X-Content-Type-Options	HTTP response header: X-Content-Type-Options	nosniff
X-Frame-Options	HTTP response header: X-Frame-Options	SAMEORIGIN
X-XSS-Protection	HTTP response header: X-XSS-Protection	0