assistant-robot/dist/LanguageModel.mjs

An assistant widget, have a 3D robot which can interact with user, have a simple LLM which can chat with user.

var n = Object.defineProperty;
var d = (o, t, s) => t in o ? n(o, t, { enumerable: !0, configurable: !0, writable: !0, value: s }) : o[t] = s;
var a = (o, t, s) => (d(o, typeof t != "symbol" ? t + "" : t, s), s);
import * as l from "@tensorflow-models/qna";
import "@tensorflow/tfjs-core";
import "@tensorflow/tfjs-backend-cpu";
import "@tensorflow/tfjs-backend-webgl";
import { o as i, q as h } from "./utils-FAxjgnse.mjs";
class m {
  constructor() {
    a(this, "status", i.loading);
    a(this, "onLoadList", []);
  }
  loaded() {
    this.status = i.ready, this.onLoadList.forEach((t) => t());
  }
  onLoad(t) {
    this.onLoadList.push(t);
  }
  removeLoadCb(t) {
    this.onLoadList = this.onLoadList.filter((s) => s != t);
  }
}
class f extends m {
  constructor({ passage: s, modelUrl: e }) {
    super();
    // The content to extract answers from.
    a(this, "passage");
    // specifies custom url of the model. This is useful for area/countries that don't have access to the model hosted on GCP.
    a(this, "modelUrl");
    // the real language model
    a(this, "model");
    this.passage = s, this.modelUrl = e, this.init();
  }
  // to load real language model
  async init() {
    this.status = i.loading;
    try {
      const s = this.modelUrl ? { modelUrl: this.modelUrl } : void 0;
      this.model = await l.load(s), this.loaded();
    } catch (s) {
      console.warn(s), this.status = i.error;
    }
  }
  /**
   * ask model question
   * @param question question to ask
   * @returns answer of the question
   */
  async findAnswers(s) {
    if (this.model) {
      const e = await this.model.findAnswers(s, this.passage), r = h(e);
      return r ? r.text : "";
    }
    return "";
  }
}
export {
  m as LanguageModel,
  f as MobileBertModel
};