bergamot-translator/wasm

Using Bergamot Translator in JavaScript

The example file bergamot.html in the folder test_page demonstrates how to use the bergamot translator in JavaScript via a <script> tag.

Pre-requisite: Download files required for translation

Please note that Using JS APIs and Demo section below assumes that the bergamot project specific model files are already downloaded and present in the test_page folder. If this is not done then use following instructions to do so:

cd test_page
mkdir models
git clone --depth 1 --branch main --single-branch https://github.com/mozilla-applied-ml/bergamot-models
cp -rf bergamot-models/prod/* models
gunzip models/*/*

Using JS APIs

// The model configuration as YAML formatted string. For available configuration options, please check: https://marian-nmt.github.io/docs/cmd/marian-decoder/
// This example captures some of the most relevant options
const modelConfig = `vocabs:
  - /esen/vocab.esen.spm
  - /esen/vocab.esen.spm
beam-size: 1
normalize: 1.0
word-penalty: 0
max-length-break: 128
mini-batch-words: 1024
workspace: 128
max-length-factor: 2.0
skip-cost: true
cpu-threads: 0
quiet: true
quiet-translation: true
gemm-precision: int8shift
`;

// Download model and shortlist files and read them into buffers
const modelFile = `models/esen/model.esen.intgemm.alphas.bin`;
const shortlistFile = `models/esen/lex.50.50.esen.s2t.bin`;
const downloadedBuffers = await Promise.all([downloadAsArrayBuffer(modelFile), downloadAsArrayBuffer(shortlistFile)]); // Please refer to bergamot.html in test_page folder for this function
const modelBuffer = downloadedBuffers[0];
const shortListBuffer = downloadedBuffers[1];

// Construct AlignedMemory instances from the buffers
var alignedModelMemory = constructAlignedMemoryFromBuffer(modelBuffer, 256); // Please refer to bergamot.html in test_page folder for this function
var alignedShortlistMemory = constructAlignedMemoryFromBuffer(shortListBuffer, 64); // Please refer to bergamot.html in test_page folder for this function

// Instantiate the TranslationModel
const model = new Module.TranslationModel(modelConfig, alignedModelMemory, alignedShortlistMemory);

// Instantiate the arguments of translate() API i.e. TranslationRequest and input (vector<string>)
const request = new Module.TranslationRequest();
const input = new Module.VectorString;

// Initialize the input
input.push_back("Hola"); input.push_back("Mundo");

// translate the input; the result is a vector<TranslationResult>
const result = model.translate(input, request);

// Print original and translated text from each entry of vector<TranslationResult>
for (let i = 0; i < result.size(); i++) {
    console.log(' original=' + result.get(i).getOriginalText() + ', translation=' + result.get(i).getTranslatedText());
}

// Don't forget to clean up the instances
model.delete();
request.delete();
input.delete();

Demo (see everything in action)

• Make sure that you followed Pre-requisite instructions before moving forward.

• Start the test webserver (ensure you have the latest nodejs installed)

  cd test_page
  bash start_server.sh ../../build-wasm
  

  Provide the folder containing the wasm artifacts as the first argument of start_server.sh script (../../build-wasm in this case).

• Open any of the browsers below

  • Firefox Nightly +87: make sure the following prefs are on (about:config)

    dom.postMessage.sharedArrayBuffer.bypassCOOP_COEP.insecure.enabled = true
    javascript.options.wasm_simd = true
    javascript.options.wasm_simd_wormhole = true
    

  • Chrome Canary +90: start with the following argument

    --js-flags="--experimental-wasm-simd"
    

• Browse to the following page:

  http://localhost:8000/bergamot.html
  

• Run some translations:

  • Choose a model and press Load Model
  • Type a sentence to be translated in the From textbox and press Translate
  • See the results in the To and Log textboxes