API de GenAI Rewriting

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()

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();