gpt-embeddings-langchain.ts

import { Document } from 'langchain/document';
import { OpenAIChat } from 'langchain/llms/openai';
import { OpenAIEmbeddings } from 'langchain/embeddings/openai';
import { RecursiveCharacterTextSplitter } from 'langchain/text_splitter';
import { MemoryVectorStore } from 'langchain/vectorstores/memory';
import { VectorDBQAChain } from 'langchain/chains';

export async function main(apiKey: string) {
  const text = `some text`;
  const splitter = new RecursiveCharacterTextSplitter({
    chunkSize: 900,
    chunkOverlap: 200,
  });

  const docs = await splitter.splitDocuments([
    new Document({ pageContent: text }),
  ]);

  const vectorStore = await MemoryVectorStore.fromDocuments(
    docs,
    new OpenAIEmbeddings({
      openAIApiKey: apiKey,
    }),
  );

  const model = new OpenAIChat({
    openAIApiKey: apiKey,
    temperature: 0,
  });

  const chain = VectorDBQAChain.fromLLM(model, vectorStore, {
    k: 1,
    returnSourceDocuments: true,
  });

  const res = await chain.call({
    query: 'some prompt',
  });

  return res;
}