Com a tarefa Vertex AI - Prever, é possível realizar uma previsão on-line. As previsões on-line são solicitações síncronas feitas em um endpoint de modelo. Use as previsões on-line ao fazer solicitações em resposta a entradas de aplicativos ou quando precisar de inferências em tempo hábil.
A Vertex AI é um serviço do Google Cloud que permite treinar e implantar modelos de ML e aplicativos de IA, além de personalizar modelos de linguagem grandes (LLMs) para uso em aplicativos com tecnologia de IA.
Antes de começar
Execute as seguintes tarefas no projeto do Google Cloud antes de configurar a tarefa Vertex AI - Prever:
Ativar a API Vertex AI (aiplatform.googleapis.com).
Criar um perfil de autenticação. Application Integration usa um perfil de autenticação para se conectar a um endpoint de autenticação para a tarefa Vertex AI - Prever.
Verifique se o VPC Service ControlsNÃO está configurado para Application Integration no projeto do Google Cloud.
Configurar a tarefa Previsão na Vertex AI
No console Google Cloud , acesse a página Application Integration.
A página Integrações aparece listando todas as integrações disponíveis no projeto do Google Cloud.
Selecione uma integração ou clique em Criar integração para criar uma.
Caso você esteja criando uma nova integração, siga estas etapas:
Digite um nome e uma descrição no painel Criar integração.
Selecione uma região para a integração.
Selecione uma conta de serviço para a integração. É possível mudar ou atualizar os detalhes da conta de serviço de uma integração a qualquer momento no painel Resumo da integraçãoinfo na barra de ferramentas de integração.
Clique em Criar. A integração recém-criada é aberta no editor de integração.
Na barra de navegação do editor de integração, clique em Tarefas para conferir a lista de tarefas e conectores disponíveis.
Clique e coloque o elemento Vertex AI - Previsão no editor de integração.
Clique no elemento Vertex AI - Previsão no designer para ver o painel de configuração da tarefa Vertex AI - Prever.
Acesse Autenticação e selecione o perfil de autenticação que você quer usar.
Opcional. Se você não tiver criado um perfil de autenticação antes de configurar a tarefa, clique em + Novo perfil de autenticação e siga as etapas em Criar um novo perfil de autenticação.
A tarefa Vertex AI - Prever retorna uma resposta com a previsão.
Estratégia de solução de erros
A estratégia de solução de erros para uma tarefa especifica a ação a ser realizada se a tarefa falhar
devido a um erro temporário. Para mais informações sobre como usar uma estratégia de tratamento de erros e conhecer os diferentes tipos de estratégias de tratamento de erros, consulte Estratégias de tratamento de erros.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-25 UTC."],[[["\u003cp\u003eThe Vertex AI - Predict task enables synchronous online predictions by sending requests to a model endpoint within the Vertex AI service.\u003c/p\u003e\n"],["\u003cp\u003eBefore using the Vertex AI - Predict task, you must enable the Vertex AI API, deploy a model to an endpoint, and create an authentication profile with the required IAM permissions.\u003c/p\u003e\n"],["\u003cp\u003eVPC Service Controls should not be set up for Application Integration when using the Vertex AI - Predict task, as it will cause the task to stop functioning.\u003c/p\u003e\n"],["\u003cp\u003eThe task configuration involves selecting an authentication profile and defining input parameters such as the region, project ID, endpoint, and request JSON.\u003c/p\u003e\n"],["\u003cp\u003eThe output of the Vertex AI - Predict task is a prediction response, and you can configure error handling and refer to the documentation for quotas and limits.\u003c/p\u003e\n"]]],[],null,["# Vertex AI - Predict task\n\nSee the [supported connectors](/integration-connectors/docs/connector-reference-overview) for Application Integration.\n\nVertex AI - Predict task\n========================\n\n|\n| **Preview**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nThe **Vertex AI - Predict** task lets you perform an online prediction. Online predictions are synchronous requests made to a model [endpoint](/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints). You can use online predictions when making requests in response to application inputs or when you require timely inferences.\n\n\n[Vertex AI](/vertex-ai/docs) is a Google Cloud service that allows you to train and deploy ML models and AI applications, and customize large language models (LLMs) for use in your AI-powered applications.\n\nBefore you begin\n----------------\n\nEnsure that you perform the following tasks in your Google Cloud project before configuring the **Vertex AI - Predict** task:\n\n1. Enable the Vertex AI API (`aiplatform.googleapis.com`).\n\n\n [Enable the Vertex AI API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n2. Deploy the [model](/vertex-ai/docs/reference/rest/v1/projects.locations.models) resource to the [endpoint](/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints).\n3. Create an [authentication profile](/application-integration/docs/configuring-auth-profile#createAuthProfile). Application Integration uses an authentication profile to connect to an authentication endpoint for the **Vertex AI - Predict** task. **Note:** If you're creating an authentication profile of [Service account](/application-integration/docs/configure-authentication-profiles#service-account) type, then ensure that the service account is assigned with the IAM role that contains the following IAM permission(s):\n | - `aiplatform.endpoints.predict`\n |\n | To know about IAM permissions and the predefined IAM roles that grant them, see [IAM permissions reference](/iam/docs/permissions-reference#search).\n |\n | For information about granting additional roles or permissions to a service account, see [Granting, changing, and revoking access](/iam/docs/granting-changing-revoking-access).\n4. Ensure that [VPC Service Controls](/application-integration/docs/vpc-service-controls) is **NOT** setup for Application Integration in your Google Cloud project. **Warning:** **Vertex AI - Predict task** will not function or will stop functioning if [VPC Service Controls](/application-integration/docs/vpc-service-controls) is setup for Application Integration in your Google Cloud project.\n\nConfigure the Vertex AI - Predict task\n--------------------------------------\n\n1. In the Google Cloud console, go to the **Application Integration** page.\n\n [Go to Application Integration](https://console.cloud.google.com/integrations)\n2. In the navigation menu, click **Integrations** .\n\n\n The **Integrations** page appears listing all the integrations available in the Google Cloud project.\n3. Select an existing integration or click **Create integration** to create a new one.\n\n\n If you are creating a new integration:\n 1. Enter a name and description in the **Create Integration** pane.\n 2. Select a region for the integration. **Note:** The **Regions** dropdown only lists the regions provisioned in your Google Cloud project. To provision a new region, click **Enable Region** . See [Enable new region](/application-integration/docs/enable-new-region) for more information.\n 3. Select a service account for the integration. You can change or update the service account details of an integration any time from the info **Integration summary** pane in the integration toolbar. **Note:** The option to select a service account is displayed only if you have enabled integration governance for the selected region.\n 4. Click **Create** . The newly created integration opens in the *integration editor*.\n\n\n4. In the *integration editor* navigation bar, click **Tasks** to view the list of available tasks and connectors.\n5. Click and place the **Vertex AI - Predict** element in the integration editor.\n6. Click the **Vertex AI - Predict** element on the designer to view the **Vertex AI - Predict** task configuration pane.\n7. Go to **Authentication** , and select an existing authentication profile that you want to use.\n\n Optional. If you have not created an authentication profile prior to configuring the task, Click **+ New authentication profile** and follow the steps as mentioned in [Create a new authentication profile](/application-integration/docs/configuring-auth-profile#createAuthProfile).\n8. Go to **Task Input** , and configure the displayed inputs fields using the following [Task input parameters](#params) table.\n\n Changes to the inputs fields are saved automatically.\n\nTask input parameters\n---------------------\n\n\nThe following table describes the input parameters of the **Vertex AI - Predict** task:\n\nTask output\n-----------\n\nThe **Vertex AI - Predict** task returns a response containing the [prediction](/vertex-ai/docs/reference/rest/v1/PredictResponse).\n\nError handling strategy\n-----------------------\n\n\nAn error handling strategy for a task specifies the action to take if the task fails due to a [temporary error](/application-integration/docs/error-handling). For information about how to use an error handling strategy, and to know about the different types of error handling strategies, see [Error handling strategies](/application-integration/docs/error-handling-strategy).\n\nQuotas and limits\n-----------------\n\nFor information about quotas and limits, see [Quotas and limits](/application-integration/docs/quotas).\n\nWhat's next\n-----------\n\n- For information about how to use the Vertex AI task with a pre-existing model, see [AI powered applications with Application Integration and Vertex AI](https://www.googlecloudcommunity.com/gc/Integration-Services/AI-powered-applications-with-Application-Integration-and-Vertex/td-p/696540).\n- To learn how to use Vertex AI in Application Integration, see [Enhancing your business integration flows with Vertex AI](https://www.googlecloudcommunity.com/gc/Integration-Services/Enhancing-your-business-integration-flows-with-GenAI-Vertex-AI/td-p/696527).\n- [Test and publish](/application-integration/docs/test-publish-integrations) your integration.\n- Add a [Data Mapping task](/application-integration/docs/data-mapping-task).\n- Learn about [all supported tasks and triggers](/application-integration/docs/how-to-guides#configure-tasks-for-google-cloud-services)."]]
