import { QdrantVectorStore } from "langchain/vectorstores/qdrant";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";
import { TextLoader } from "langchain/document_loaders/fs/text";

// Create docs with a loader
const loader = new TextLoader("src/document_loaders/example_data/example.txt");
const docs = await loader.load();

const vectorStore = await QdrantVectorStore.fromDocuments(
  docs,
  new OpenAIEmbeddings(),
  {
    url: process.env.QDRANT_URL,
    collectionName: "a_test_collection",
  }
);

// Search for the most similar document
const response = await vectorStore.similaritySearch("hello", 1);

console.log(response);
/*
[
  Document {
    pageContent: 'Foo\nBar\nBaz\n\n',
    metadata: { source: 'src/document_loaders/example_data/example.txt' }
  }
]
*/