[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2024-12-21(UTC)"],[[["\u003cp\u003eThis guide outlines the steps to create a generic recommendations application using Vertex AI Agent Builder, starting with setting up a Google Cloud project.\u003c/p\u003e\n"],["\u003cp\u003eYou must prepare structured data, such as in a BigQuery table or JSON files, before importing it into a data store within Vertex AI Search.\u003c/p\u003e\n"],["\u003cp\u003eAfter creating the app and connecting it to the data store, you can configure filterable fields to refine the recommendations provided.\u003c/p\u003e\n"],["\u003cp\u003eThe platform allows for previewing recommendations through both the Vertex AI Agent Builder console and API, and once satisfied, the app can be deployed by integrating API calls into your website or application.\u003c/p\u003e\n"],["\u003cp\u003eOngoing maintenance is supported, which includes refreshing your data to keep the recommendations app up to date with your data store.\u003c/p\u003e\n"]]],[],null,["# Custom recommendations checklist\n\nThis page provides a checklist of the steps required to create a generic recommendations app.\n\n\u003cbr /\u003e\n\nIf you're new to AI Applications, consider following the [Get started\nwith custom recommendations](/generative-ai-app-builder/docs/try-generic-recommendations) tutorial to create a\nsample app.\n\n\n### [Set up a Google Cloud\nproject](#set-up-project)\n\nSet up a Google Cloud project, turn on AI Applications, and set up access\ncontrol for your project. You can use an existing Google Cloud project if you\nhave one already.\n\n### Actions\n\n1. Review [Before you begin](/generative-ai-app-builder/docs/before-you-begin) and confirm that you have completed the steps. \n\n### [Prepare your data](#prepare-data)\n\nPrepare your data for importing to Vertex AI Search.\n\nFor custom recommendations, you must supply **structured data**.\nThis is data provided with a specific schema. For example, you\ncan provide data in a BigQuery table or as JSON files in\nCloud Storage.\n\n### Actions\n\n1. Review the information about supported data and the relationship between apps\n and data stores in [About apps and data\n stores](/generative-ai-app-builder/docs/create-datastore-ingest).\n\n2. Prepare your data according to the requirements in [Prepare data for\n ingestion](/generative-ai-app-builder/docs/prepare-data#structured).\n\n### [Import your data](#import-data)\n\nCreate a data store and then import your data into it.\n\nHow you import your data depends on where you're importing it from. For\nexample, if your data is in Cloud Storage, you can import it using the\nconsole or the API by providing the bucket location of your data.\n\n### Actions\n\n1. Follow the instructions for your data source in [Create a custom recommendations\ndata store](/generative-ai-app-builder/docs/create-data-store-recommendations). \n\n### [Create your app](#create-app)\n\nCreate your custom recommendations app and connect it to your new data store.\n\n### Actions\n\n1. [Create a custom recommendations app](/generative-ai-app-builder/docs/create-generic-recommendations-app). \n\n### [Configure your\nrecommendations](#configure-settings)\n\nYou can update field settings to make them filterable and filter your\nrecommendations results using those fields.\n\n### Actions\n\n1. Set specific fields as filterable to allow Vertex AI Search to use\n those fields for filtering recommendations. See [Configure field\n settings](/generative-ai-app-builder/docs/configure-field-settings).\n\n2. [Filter recommendations](/generative-ai-app-builder/docs/filter-recommendations).\n\n### [Preview\nrecommendations](#preview-results)\n\nYou can preview your recommendations to check if your recommendations are\nappearing as expected.\n\n### Actions\n\n1. To preview your recommendations, use the AI Applications console or the API.\n\n - **Console.** Use the console **Preview** page to preview your\n recommendations. See the **Console** instructions for the kind of data that\n your app uses in [Get\n recommendations](/generative-ai-app-builder/docs/preview-recommendations).\n\n - **API** . If you're integrating API calls into your application, make API\n calls to preview your recommendations. See the **REST**\n instructions for the kind of data that your app uses in [Get\n recommendations](/generative-ai-app-builder/docs/preview-recommendations).\n\n### [Deploy your\nrecommendations app](#preview-results)\n\nWhen you are happy with the previews from your recommendations app, share\nit with your users by deploying it to your website.\n\n### Actions\n\n1. To deploy your recommendations app, integrate API calls into your server or\n applications. For more information about making API calls, see the **REST**\n instructions for the kind of data that your app uses in [Get\n recommendations](/generative-ai-app-builder/docs/preview-recommendations).\n\n For client library resources, see [AI Applications client\nlibraries](/generative-ai-app-builder/docs/libraries). \n\n### [Record and import user events](#user-events)\n\nTo get personalized recommendation results, you can update the user events\nin your recommendation app. For more information see\n[About user events](/generative-ai-app-builder/docs/user-events).\n\n### Actions\n\n1. [Import historical user events](/generative-ai-app-builder/docs/import-user-events).\n2. [Record real-time user events](/generative-ai-app-builder/docs/record-user-events). \n\n### [Maintain your app](#maintain-data)\n\nYou can maintain your app to ensure that latest and necessary data is available\nin your data store.\n\n### Actions\n\n1. [Refresh your data](/generative-ai-app-builder/docs/refresh-data)."]]
