GenAI Rewriting API

With ML Kit's GenAI Rewriting API, you can automatically help users rewrite chat messages or short pieces of content with a different style or tone.

Users may find it helpful to be provided with suggestions on how to rewrite a piece of content in the following cases:

Restructuring a message to be more professional when communicating with stakeholders
Shortening a message to be more suitable for posting on social media platforms
Rephrasing a message for non-native speakers looking for alternative ways to communicate the message

Key capabilities

The ML Kit's GenAI Rewriting API can rewrite short pieces of content in one of the following styles:

Elaborate: Expands the input text with more details and descriptive language.
Emojify: Adds relevant emoji to the input text, making it more expressive and fun.
Shorten: Condenses the input text to a shorter version, keeping the core message intact.
Friendly: Rewrites the input text to be more casual and approachable, using a conversational tone.
Professional: Rewrites the input text to be more formal and business-like, using a respectful tone.
Rephrase: Rewrites the input text using different words and sentence structures, while maintaining the original meaning.

Requests will return at least one suggestion. If multiple suggestions are returned, results will be sorted by descending confidence.

Example results

Input	Rewrite Style	Output
Do you want to meet to talk more?	Professional	Would you be interested in meeting again to discuss this further?
I would like to request the pleasure of your company at a casual get-together at my residence this coming Saturday evening	Shorten	Would you like to join me for a casual get-together at my place this Saturday evening?
The event was successful	Elaborate	The event was a resounding success, exceeding all of our expectations and proving to be a resounding triumph.
Let's grab coffee sometime soon	Emojify	Let's grab coffee ☕ sometime soon 👋.
Provide the report by end of day	Friendly	Could you please share the report by the end of the day?
Hey, need that thing ASAP	Professional	Could you please provide the requested document at your earliest convenience?
The project is behind schedule	Rephrase	The project timeline requires adjustment to meet the original deadline

Getting Started

To get started with the GenAI Rewriting API, add this dependency to your project's build file.

  implementation 
 ( 
 "com.google.mlkit:genai-rewriting:1.0.0-beta1" 
 )

Then, instantiate the Rewriter client with the required options, check if the required on-device model features are available (and download them if necessary), prepare your input text as a request, run the rewriting process to get suggestions, and release the resources.

Kotlin

  val 
  
 textToRewrite 
  
 = 
  
 "The event was successful" 
 // Define task with selected input and output format 
 val 
  
 rewriterOptions 
  
 = 
  
 RewriterOptions 
 . 
 builder 
 ( 
 context 
 ) 
  
 // OutputType can be one of the following: ELABORATE, EMOJIFY, SHORTEN, 
  
 // FRIENDLY, PROFESSIONAL, REPHRASE 
  
 . 
 setOutputType 
 ( 
 RewriterOptions 
 . 
 OutputType 
 . 
 ELABORATE 
 ) 
  
 // Refer to RewriterOptions.Language for available languages 
  
 . 
 setLanguage 
 ( 
 RewriterOptions 
 . 
 Language 
 . 
 ENGLISH 
 ) 
  
 . 
 build 
 () 
 val 
  
 rewriter 
  
 = 
  
 Rewriting 
 . 
 getClient 
 ( 
 rewriterOptions 
 ) 
 suspend 
  
 fun 
  
 prepareAndStartRewrite 
 () 
  
 { 
  
 // Check feature availability, status will be one of the following: 
  
 // UNAVAILABLE, DOWNLOADABLE, DOWNLOADING, AVAILABLE 
  
 val 
  
 featureStatus 
  
 = 
  
 rewriter 
 . 
 checkFeatureStatus 
 (). 
 await 
 () 
  
 if 
  
 ( 
 featureStatus 
  
 == 
  
 FeatureStatus 
 . 
 DOWNLOADABLE 
 ) 
  
 { 
  
 // Download feature if necessary. 
  
 // If downloadFeature is not called, the first inference request will 
  
 // also trigger the feature to be downloaded if it's not already 
  
 // downloaded. 
  
 rewriter 
 . 
 downloadFeature 
 ( 
 object 
  
 : 
  
 DownloadCallback 
  
 { 
  
 override 
  
 fun 
  
 onDownloadStarted 
 ( 
 bytesToDownload 
 : 
  
 Long 
 ) 
  
 { 
  
 } 
  
 override 
  
 fun 
  
 onDownloadFailed 
 ( 
 e 
 : 
  
 GenAiException 
 ) 
  
 { 
  
 } 
  
 override 
  
 fun 
  
 onDownloadProgress 
 ( 
 totalBytesDownloaded 
 : 
  
 Long 
 ) 
  
 {} 
  
 override 
  
 fun 
  
 onDownloadCompleted 
 () 
  
 { 
  
 startRewritingRequest 
 ( 
 textToRewrite 
 , 
  
 rewriter 
 ) 
  
 } 
  
 }) 
  
 } 
  
 else 
  
 if 
  
 ( 
 featureStatus 
  
 == 
  
 FeatureStatus 
 . 
 DOWNLOADING 
 ) 
  
 { 
  
 // Inference request will automatically run once feature is 
  
 // downloaded. 
  
 // If Gemini Nano is already downloaded on the device, the 
  
 // feature-specific LoRA adapter model will be downloaded 
  
 // quickly. However, if Gemini Nano is not already downloaded, 
  
 // the download process may take longer. 
  
 startRewritingRequest 
 ( 
 textToRewrite 
 , 
  
 rewriter 
 ) 
  
 } 
  
 else 
  
 if 
  
 ( 
 featureStatus 
  
 == 
  
 FeatureStatus 
 . 
 AVAILABLE 
 ) 
  
 { 
  
 startRewritingRequest 
 ( 
 textToRewrite 
 , 
  
 rewriter 
 ) 
  
 } 
 } 
 suspend 
  
 fun 
  
 startRewritingRequest 
 ( 
 text 
 : 
  
 String 
 , 
  
 rewriter 
 : 
  
 Rewriter 
 ) 
  
 { 
  
 // Create task request 
  
 val 
  
 rewritingRequest 
  
 = 
  
 RewritingRequest 
 . 
 builder 
 ( 
 text 
 ). 
 build 
 () 
  
 // Start rewriting request with non-streaming response 
  
 // More than 1 result may be returned. If multiple suggestions are 
  
 // returned, results will be sorted by descending confidence. 
  
 val 
  
 rewriteResults 
  
 = 
  
 rewriter 
 . 
 runInference 
 ( 
 rewritingRequest 
 ). 
 await 
 (). 
 results 
  
 // You can also start a streaming request 
  
 // rewriter.runInference(rewritingRequest) { newText - 
>  
 //    // Show new text in UI 
  
 // } 
 } 
 // Be sure to release the resource when no longer needed 
 // For example, on viewModel.onCleared() or activity.onDestroy() 
 rewriter 
 . 
 close 
 ()

Java

  String 
  
 textToRewrite 
  
 = 
  
 "The event was successful" 
 ; 
 // Define task with required input and output format 
 RewriterOptions 
  
 rewriterOptions 
  
 = 
  
 RewriterOptions 
 . 
 builder 
 ( 
 context 
 ) 
  
 // OutputType can be one of the following: ELABORATE, 
  
 // EMOJIFY, SHORTEN, FRIENDLY, PROFESSIONAL, REPHRASE 
  
 . 
 setOutputType 
 ( 
 RewriterOptions 
 . 
 OutputType 
 . 
 ELABORATE 
 ) 
  
 // Refer to RewriterOptions.Language for available 
  
 // languages 
  
 . 
 setLanguage 
 ( 
 RewriterOptions 
 . 
 Language 
 . 
 ENGLISH 
 ) 
  
 . 
 build 
 (); 
 Rewriter 
  
 rewriter 
  
 = 
  
 Rewriting 
 . 
 getClient 
 ( 
 rewriterOptions 
 ); 
 void 
  
 prepareAndStartRewrite 
 () 
  
 throws 
  
 ExecutionException 
 , 
  
 InterruptedException 
  
 { 
  
 // Check feature availability, status will be one of the 
  
 // following: UNAVAILABLE, DOWNLOADABLE, DOWNLOADING, AVAILABLE 
  
 try 
  
 { 
  
 int 
  
 featureStatus 
  
 = 
  
 rewriter 
 . 
 checkFeatureStatus 
 (). 
 get 
 (); 
  
 if 
  
 ( 
 featureStatus 
  
 == 
  
 FeatureStatus 
 . 
 DOWNLOADABLE 
 ) 
  
 { 
  
 // Download feature if necessary. 
  
 // If downloadFeature is not called, the first inference 
  
 // request will also trigger the feature to be downloaded 
  
 // if it's not already downloaded. 
  
 rewriter 
 . 
 downloadFeature 
 ( 
  
 new 
  
 DownloadCallback 
 () 
  
 { 
  
 @Override 
  
 public 
  
 void 
  
 onDownloadCompleted 
 () 
  
 { 
  
 startRewritingRequest 
 ( 
 textToRewrite 
 , 
  
 rewriter 
 ); 
  
 } 
  
 @Override 
  
 public 
  
 void 
  
 onDownloadFailed 
 ( 
 GenAIException 
  
 e 
 ) 
  
 {} 
  
 @Override 
  
 public 
  
 void 
  
 onDownloadProgress 
 ( 
  
 long 
  
 totalBytesDownloaded 
 ) 
  
 {} 
  
 @Override 
  
 public 
  
 void 
  
 onDownloadStarted 
 ( 
 long 
  
 bytesDownloaded 
 ) 
  
 {} 
  
 }); 
  
 } 
  
 else 
  
 if 
  
 ( 
 featureStatus 
  
 == 
  
 FeatureStatus 
 . 
 DOWNLOADING 
 ) 
  
 { 
  
 // Inference request will automatically run once feature is 
  
 // downloaded. 
  
 // If Gemini Nano is already downloaded on the device, the 
  
 // feature-specific LoRA adapter model will be downloaded 
  
 // quickly. However, if Gemini Nano is not already downloaded, 
  
 // the download process may take longer. 
  
 startRewritingRequest 
 ( 
 textToRewrite 
 , 
  
 rewriter 
 ); 
  
 } 
  
 else 
  
 if 
  
 ( 
 featureStatus 
  
 == 
  
 FeatureStatus 
 . 
 AVAILABLE 
 ) 
  
 { 
  
 startRewritingRequest 
 ( 
 textToRewrite 
 , 
  
 rewriter 
 ); 
  
 } 
  
 } 
  
 catch 
  
 ( 
 ExecutionException 
  
 | 
  
 InterruptedException 
  
 e 
 ) 
  
 { 
  
 e 
 . 
 printStackTrace 
 (); 
  
 } 
 } 
 void 
  
 startRewritingRequest 
 ( 
 String 
  
 text 
 , 
  
 Rewriter 
  
 rewriter 
 ) 
  
 { 
  
 // Create task request 
  
 RewritingRequest 
  
 rewritingRequest 
  
 = 
  
 RewritingRequest 
 . 
 builder 
 ( 
 text 
 ). 
 build 
 (); 
  
 try 
  
 { 
  
 // Start rewriting request with non-streaming response 
  
 // More than 1 result may be returned. If multiple 
  
 // suggestions are returned, results will be sorted by 
  
 // descending confidence. 
  
 rewriter 
 . 
 runInference 
 ( 
 rewritingRequest 
 ). 
 get 
 (). 
 getResults 
 (); 
  
 // You can also start a streaming request 
  
 // rewriter.runInference(rewritingRequest, newText -> { 
  
 //     // Show new text in UI 
  
 // }); 
  
 } 
  
 catch 
  
 ( 
 ExecutionException 
  
 | 
  
 InterruptedException 
  
 e 
 ) 
  
 { 
  
 e 
 . 
 printStackTrace 
 (); 
  
 } 
 } 
 // Be sure to release the resource when no longer needed 
 // For example, on viewModel.onCleared() or activity.onDestroy() 
 rewriter 
 . 
 close 
 ();

Supported features and limitations

The GenAI Rewriting API supports the following languages: English, Japanese, French, German, Italian, Spanish, and Korean, and they are defined in RewriterOptions.Language . Input should be less than 256 tokens.

Availability of the specific feature configuration (specified by RewriterOptions ) may vary depending on the particular device's configuration and the models that have been downloaded to the device.

The most reliable way for developers to ensure that the intended API feature is supported on a device with the requested RewriterOptions is to call the checkFeatureStatus() method. This method provides the definitive status of feature availability on the device at runtime.

Common setup issues

ML Kit GenAI APIs rely on the Android AICore app to access Gemini Nano. When a device is just setup (including reset), or the AICore app is just reset (e.g. clear data, uninstalled then reinstalled), the AICore app may not have enough time to finish initialization (including downloading latest configurations from server). As a result, the ML Kit GenAI APIs may not function as expected. Here are the common setup error messages you may see and how to handle them:

Example error message	How to handle
AICore failed with error type 4-CONNECTION_ERROR and error code 601-BINDING_FAILURE: AICore service failed to bind.	This could happen when you install the app using ML Kit GenAI APIs immediately after device setup or when AICore is uninstalled after your app is installed. Updating AICore app then reinstalling your app should fix it.
AICore failed with error type 3-PREPARATION_ERROR and error code 606-FEATURE_NOT_FOUND: Feature ... is not available.	This could happen when AICore hasn't finished downloading the latest configurations. When the device is connected to the internet, it usually takes a few minutes to a few hours to update. Restarting the device can speed up the update. Note that if the device's bootloader is unlocked, you'll also see this error—this API does not support devices with unlocked bootloaders.
AICore failed with error type 1-DOWNLOAD_ERROR and error code 0-UNKNOWN: Feature ... failed with failure status 0 and error esz: UNAVAILABLE: Unable to resolve host ...	Keep network connection, wait for a few minutes and retry.