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[Setting a Locale](#🌐-setting-a-locale)\n* [UX Customization](#ux-customization)\n   * [Increase your brightness image](#increase-your-brightness-image)\n   * [Font size](#font-size)\n   * [Font family](#font-family)\n   * [Continue button](#continue-button)\n   * [Feedback messages](#feedback-messages)\n* [FAQ](#faq)\n   * [Q: How can I get the results of the liveness session?](#q-how-can-i-get-the-results-of-the-liveness-session)\n   * [Q: My retry fails or the session will not start a second time. What is wrong?](#q-my-retry-fails-or-the-session-will-not-start-a-second-time-what-is-wrong)\n   * [Q: How can I automate deployment of the assets?](#q-how-can-i-automate-deployment-of-the-assets)\n\n## Introduction\n\nThe Azure AI Vision Face UI Web SDK is a client library intended to enable the integration of the face liveness feature into web-applications. It works seamlessly with Azure AI Face APIs to determine the authenticity of a face in a video stream.\n\n* API reference: [AzureAIVisionFaceUI](https://aka.ms/azure-ai-vision-face-liveness-client-sdk-web-api-reference-modules)\n\n## Prerequisites\n\n1. An Azure Face API resource subscription.\n2. Install node from https://nodejs.org/en/download/prebuilt-installer\n\n## Installation\n\n1. Create .npmrc file in root of app folder to pull packages from `https://pkgs.dev.azure.com/msface/SDK/_packaging/AzureAIVision/npm/registry/` registry. \nAn example .npmrc file is available here(https://github.com/Azure-Samples/azure-ai-vision-sdk/blob/main/samples/web/angularjs/.npmrc).\n\n2. Fetch the base64 access token required in the .npmrc file using the API: [Liveness Session Operations - Get Client Assets Access Token](https://learn.microsoft.com/rest/api/face/liveness-session-operations/get-client-assets-access-token?view=rest-face-v1.3-preview)\n\n3. To install the SDK via NPM, run the following command in the root of the app folder:\n\n    ```sh\n    npm install @azure/ai-vision-face-ui@latest\n    ```\n\n## Integrate face liveness detector into your own application\n\nFirst, ensure you have installed the npm package as described in the [Installation](#installation) section.\n\n### Obtaining a session token\n\n  The session-authorization-token is required to start a liveness session. See `fetchTokenOnServer` in `server.js` file method for a demo. \n  For more information on how to orchestrate the liveness flow by utilizing the Azure AI Vision Face service, visit: https://aka.ms/azure-ai-vision-face-liveness-tutorial \n\n### Injecting the web component\n\n  After obtaining a valid session-authorization-token, you can integrate the web component, `<azure-ai-vision-face-ui> `element, using JavaScript.\n\n  ```javascript\n  const azureAIVisionFaceUI = document.createElement(\"azure-ai-vision-face-ui\");\n  document.getElementById(\"your-container-id\").appendChild(azureAIVisionFaceUI);\n  azureAIVisionFaceUI.start(\"***FACE_API_SESSION_TOKEN***\")\n    .then(resultData => { \n      // The resultData which is LivenessDetectionSuccess interface.\n      // The result of analysis is queryable from the service using sessions result API\n      // https://learn.microsoft.com/rest/api/face/liveness-session-operations/get-liveness-session-result?view=rest-face-v1.2-preview.1&tabs=HTTP\n\n    })\n    .catch(errorData => {\n      // In case of failures, the promise is rejected. The errorData which is LivenessDetectionError interface, contains the reason for the failure.\n    });\n  ```\n\n### Retrying a liveness check\n\nA session token represents a single liveness session. You can let the user make more than one attempt within that session without asking your backend for a new token, as long as you stay on the same loaded page.\n\nTo retry, remove the existing `<azure-ai-vision-face-ui>` element, create a new one, and call `start()` again with the **same** token. Do not reload the page to retry.\n\n```javascript\nfunction retryLivenessCheck() {\n  // 1. Remove the previous detector instance.\n  document.querySelector(\"azure-ai-vision-face-ui\")?.remove();\n\n  // 2. Create a fresh instance on the same page and reuse the same token.\n  const azureAIVisionFaceUI = document.createElement(\"azure-ai-vision-face-ui\");\n  document.getElementById(\"your-container-id\").appendChild(azureAIVisionFaceUI);\n  azureAIVisionFaceUI.start(\"***FACE_API_SESSION_TOKEN***\")    // same token as the first attempt\n    .then(resultData => { /* ... */ })\n    .catch(errorData => { /* ... */ });\n}\n```\n\nWhen to ask your backend for a **new** token instead of reusing the current one:\n\n* You are starting a genuinely new liveness session (a new user, or a new check).\n* The page was fully reloaded (see [Using the SDK inside an iframe](#using-the-sdk-inside-an-iframe) for why a reload matters).\n* `start()` rejected with `LivenessError.InvalidToken`. This means the current token has reached the end of its allowed use, and the next attempt needs a fresh token from a new session.\n\nA token cannot be reused after the page that is running the SDK has been reloaded. A reload starts the flow over, so it needs a token from a new session.\n\n### Using the SDK inside an iframe\n\nThe SDK works the same inside an iframe as it does at the top level of a page. Being in an iframe is not, by itself, a special case, and it does not change how tokens or retries work.\n\nThe one thing that matters for retries is whether the page running the SDK is **fully reloaded** between attempts:\n\n* If your retry keeps the page alive and only re-creates the `<azure-ai-vision-face-ui>` element (as shown in [Retrying a liveness check](#retrying-a-liveness-check)), the same token keeps working. This is true whether the SDK is at the top level or inside an iframe.\n* If your retry **reloads the page** (for example by setting the iframe's `src` again, navigating it, or calling `location.reload()` inside it), that is a fresh start and needs a token from a new session. Reusing the previous token after a reload will not work.\n\nThis is intentional: a session token is tied to a single session, so it cannot be carried into a freshly loaded page and reused there.\n\nIf a parent page hosts the SDK in an iframe and owns the \"Try again\" control, prefer telling the iframe to retry in place rather than reloading it. A simple way is to send the iframe a message and have the iframe re-run the retry steps:\n\n```javascript\n// In the parent page, on \"Try again\":\niframe.contentWindow.postMessage({ type: \"retry-liveness\" }, iframeOrigin);\n\n// Inside the iframe page:\nwindow.addEventListener(\"message\", (event) => {\n  if (event.origin !== expectedParentOrigin) return;      // always validate the sender's origin\n  if (event.data?.type !== \"retry-liveness\") return;\n  retryLivenessCheck();                                   // re-creates the element, reuses the same token, no reload\n});\n```\n\nA working parent + iframe example is included in the JavaScript sample.\n\n### Deployment\n\n  It's important to note that essential assets like WebAssembly (wasm) files and localization files are packaged within the NPM distribution. During deployment to a production environment, it's essential to include these assets. As an example, you can deploy the 'facelivenessdetector-assets' from the node_modules\\azure-ai-vision-face-ui folder to the root assets directory like `public` folder after the npm installation to ensure proper asset deployment.\n\n\n## 🌍 Localization\n\nThe Azure AI Vision Face UI SDK embraces global diversity by supporting multiple languages. The complete list of supported locales and language dictionary is available [here](https://github.com/Azure-Samples/azure-ai-vision-sdk/tree/main/samples/Localization.md)\n\n### 🌐 Setting a Locale\n\n  To use a specific locale, assign the locale attribute to the azure-ai-vision-face-ui component. If translations are available for that locale, they will be used; otherwise, the SDK will default to English.\n\n* Example - Enabling Portuguese\n  ```javascript\n  const azureAIVisionFaceUI = document.createElement(\"azure-ai-vision-face-ui\");\n  azureAIVisionFaceUI.locale = \"pt-PT\";  // Setting Portuguese locale\n  document.getElementById(\"your-container-id\").appendChild(azureAIVisionFaceUI);\n  ```\n\n## UX Customization\nYou can customize the layout of the page using following options:\n\n### Increase your brightness image\n  Customize the default \"Increase your screen brightness\" image by providing your own image. Ensure the image is correctly deployed for production.\n  azureAIVisionFaceUI.brightnessImagePath = newImagePath;\n  \n### Font size\n  Customize the default font size for all the text. The default is 1.5rem\n  azureAIVisionFaceUI.fontSize = newSize;\n    \n### Font family\n  Customize the default font family for all the text. The default value is `font-family: system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, 'Open Sans', 'Helvetica Neue', sans-serif;`\n  \n  azureAIVisionFaceUI.fontFamily = newFontFamily;\n    \n### Continue button\n  Customize the look and feel of the \"Continue\" button by providing your own CSS styles. To change the text, use `languageDictionary` attribute and override the \"Continue\" key.\n  \n  azureAIVisionFaceUI.continueButtonStyles = newCSS;\n    \n### Feedback messages\n  Customize the look and feel of the feedback messages by providing your own CSS styles.\n  \n  azureAIVisionFaceUI.feedbackMessageStyles = newCSS;\n    \n## FAQ\n    \n### Q: How can I get the results of the liveness session?\n\nOnce the session is completed and the promise fulfilled, for security reasons the client does not receive the outcome whether face is live or spoof. \n\nYou can query the result from your backend service by calling the sessions results API to get the outcome\nhttps://aka.ms/face/liveness-session/get-liveness-session-result\n\n### Q: My retry fails or the session will not start a second time. What is wrong?\n\nThis almost always comes down to how the retry is wired and which token it uses:\n\n* **Reusing a token after a full page reload.** A session token is tied to one session and cannot be reused once the page running the SDK has been reloaded. If your \"Try again\" reloads the page (or reloads the iframe by re-setting its `src`, navigating it, or calling `location.reload()`), request a token from a new session for that attempt. See [Using the SDK inside an iframe](#using-the-sdk-inside-an-iframe).\n* **Retrying without reloading is supported and is the recommended pattern.** Keep the page loaded, remove the `<azure-ai-vision-face-ui>` element, create a new one, and call `start()` again with the same token. See [Retrying a liveness check](#retrying-a-liveness-check).\n* **`start()` rejected with `LivenessError.InvalidToken`.** The current token has reached the end of its allowed use. Obtain a fresh token from a new session before the next attempt.\n\nNote that running inside an iframe does not change any of this. The deciding factor is whether the page was reloaded, not whether the SDK is in an iframe.\n\n### Q: How can I automate deployment of the assets?\n\n* React\n\n  For deployment\n  You can add postbuild script to your package.json to copy facelivenessdetector-assets to public\n  ```\n  \"scripts\": {\n      \"postbuild\": \"cpy node_modules/azure-ai-vision-face-ui/facelivenessdetector-assets/**/* public/facelivenessdetector-assets --parents\"\n    }\n  ```\n\n* Angular\n\n  Please see the [AngularJS integration example](https://github.com/Azure-Samples/azure-ai-vision-sdk/tree/main/samples/web/angularjs/src/face/face.component.ts) at `samples/angularjs/src/face/face.component.ts`\n\n  For deployment you can add section to deploy facelivenessdetector-assets in your projects' build section of the configuration file\n  ```\n  \n  \"build\": {\n    \"options\": {\n      \"assets\": [\n        { \"glob\": \"**/*\", \"input\": \"./node_modules/azure-ai-vision-face-ui/facelivenessdetector-assets\", \"output\": \"/facelivenessdetector-assets\" }\n      ],\n    }\n  }\n  ```\n","readmeFilename":"README.md"}