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HNSWLib

兼容性

仅适用于Node.js。

HNSWLib是一个内存向量存储器，可以保存到文件中。它使用HNSWLib。

设置​

:::注意

在Windows上，你可能需要先安装Visual Studio才能正确构建hnswlib-node包。

:::

您可以通过以下方式进行安装

npm install hnswlib-node

用法​

从文本创建新索引​

import { HNSWLib } from "langchain/vectorstores/hnswlib";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";

const vectorStore = await HNSWLib.fromTexts(
  ["Hello world", "Bye bye", "hello nice world"],
  [{ id: 2 }, { id: 1 }, { id: 3 }],
  new OpenAIEmbeddings()
);

const resultOne = await vectorStore.similaritySearch("hello world", 1);
console.log(resultOne);

从加载器创建新索引​

import { HNSWLib } from "langchain/vectorstores/hnswlib";
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();

// Load the docs into the vector store
const vectorStore = await HNSWLib.fromDocuments(docs, new OpenAIEmbeddings());

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

将索引保存到文件并重新加载​

import { HNSWLib } from "langchain/vectorstores/hnswlib";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";

// Create a vector store through any method, here from texts as an example
const vectorStore = await HNSWLib.fromTexts(
  ["Hello world", "Bye bye", "hello nice world"],
  [{ id: 2 }, { id: 1 }, { id: 3 }],
  new OpenAIEmbeddings()
);

// Save the vector store to a directory
const directory = "your/directory/here";
await vectorStore.save(directory);

// Load the vector store from the same directory
const loadedVectorStore = await HNSWLib.load(directory, new OpenAIEmbeddings());

// vectorStore and loadedVectorStore are identical

const result = await loadedVectorStore.similaritySearch("hello world", 1);
console.log(result);

过滤文档​

import { HNSWLib } from "langchain/vectorstores/hnswlib";
import { OpenAIEmbeddings } from "langchain/embeddings/openai";

const vectorStore = await HNSWLib.fromTexts(
  ["Hello world", "Bye bye", "hello nice world"],
  [{ id: 2 }, { id: 1 }, { id: 3 }],
  new OpenAIEmbeddings()
);

const result = await vectorStore.similaritySearch(
  "hello world",
  10,
  (document) => document.metadata.id === 3
);

// only "hello nice world" will be returned
console.log(result);