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 https //docs cloud google com/vertex ai/docs/reference 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 https //docs cloud google com/vertex ai/docs/reference/rest/v1/projects locations reasoningengines/query reasoning engines stream query streams queries using a reasoning engine click here https //docs cloud google com/vertex ai/docs/reference/rest/v1/projects locations reasoningengines/streamquery ask vertex ask vertex is a tool that allows you to ask questions to a model click here https //docs cloud google com/vertex ai/generative ai/docs/reference/rest/v1/projects locations publishers models/generatecontent 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