| |
| import init, { Model } from "./build/m.js"; |
|
|
| async function fetchArrayBuffer(url) { |
| const cacheName = "bert-candle-cache"; |
| const cache = await caches.open(cacheName); |
| const cachedResponse = await cache.match(url); |
| if (cachedResponse) { |
| const data = await cachedResponse.arrayBuffer(); |
| return new Uint8Array(data); |
| } |
| const res = await fetch(url, { cache: "force-cache" }); |
| cache.put(url, res.clone()); |
| return new Uint8Array(await res.arrayBuffer()); |
| } |
| class Bert { |
| static instance = {}; |
|
|
| static async getInstance(weightsURL, tokenizerURL, configURL, modelID) { |
| if (!this.instance[modelID]) { |
| await init(); |
|
|
| self.postMessage({ status: "loading", message: "Loading Model" }); |
| const [weightsArrayU8, tokenizerArrayU8, mel_filtersArrayU8] = |
| await Promise.all([ |
| fetchArrayBuffer(weightsURL), |
| fetchArrayBuffer(tokenizerURL), |
| fetchArrayBuffer(configURL), |
| ]); |
|
|
| this.instance[modelID] = new Model( |
| weightsArrayU8, |
| tokenizerArrayU8, |
| mel_filtersArrayU8 |
| ); |
| } else { |
| self.postMessage({ status: "ready", message: "Model Already Loaded" }); |
| } |
| return this.instance[modelID]; |
| } |
| } |
|
|
| self.addEventListener("message", async (event) => { |
| const { |
| weightsURL, |
| tokenizerURL, |
| configURL, |
| modelID, |
| sentences, |
| normalize = true, |
| } = event.data; |
| try { |
| self.postMessage({ status: "ready", message: "Starting Bert Model" }); |
| const model = await Bert.getInstance( |
| weightsURL, |
| tokenizerURL, |
| configURL, |
| modelID |
| ); |
| self.postMessage({ |
| status: "embedding", |
| message: "Calculating Embeddings", |
| }); |
| const output = model.get_embeddings({ |
| sentences: sentences, |
| normalize_embeddings: normalize, |
| }); |
|
|
| self.postMessage({ |
| status: "complete", |
| message: "complete", |
| output: output.data, |
| }); |
| } catch (e) { |
| self.postMessage({ error: e }); |
| } |
| }); |
|
|