src/embed/hf.ts

import { pipeline } from "@xenova/transformers";
 import { Embeddings, EmbeddingsParams } from "langchain/embeddings/base";

 export interface XenovaTransformersEmbeddingsParams extends EmbeddingsParams {
   model?: string;
 }

 export default class XenovaTransformersEmbeddings
   extends Embeddings
   implements XenovaTransformersEmbeddingsParams
 {
   model: string;

   client: any;

   constructor(fields?: XenovaTransformersEmbeddingsParams) {
     super(fields ?? {});
     this.model = fields?.model ?? "Xenova/all-MiniLM-L6-v2";
   }

   async _embed(texts: string[]): Promise<number[][]> {
     if (!this.client) {
       this.client = await pipeline("embeddings", this.model);
     }
     console.log(this.client, texts);

     return this.caller.call(async () => {
       return await Promise.all(
         texts.map(async (t) => (await this.client(t, { pooling: 'mean', normalize: true })).data)
       );
     });
   }

   embedQuery(document: string): Promise<number[]> {
     return this._embed([document]).then((embeddings) => embeddings[0]);
   }

   embedDocuments(documents: string[]): Promise<number[][]> {
     return this._embed(documents);
   }
 }