HNSWLib is an high performance in-memory vectorstore.
It is great for testing since you do not need access to the file system or a cloud service.
Install HNSWLib addon
npm install @llm-tools/embedjs-hnswlib
Usage
import { RAGApplicationBuilder } from '@llm-tools/embedjs';
import { OpenAiEmbeddings } from '@llm-tools/embedjs-openai';
import { HNSWDb } from '@llm-tools/embedjs-hnswlib';
import { WebLoader } from '@llm-tools/embedjs-loader-web';
// set OPENAI_API_KEY in your env
process.env.OPENAI_API_KEY = "sk-xxx";
const app = await new RAGApplicationBuilder()
.setEmbeddingModel(new OpenAiEmbeddings())
.setModel(SIMPLE_MODELS.OPENAI_GPT4_O)
.setVectorDatabase(new HNSWDb())
.build();
//add data source and start query it
await app.addLoader(new WebLoader({ urlOrContent: 'https://www.forbes.com/profile/elon-musk' }));
await app.query('Tell me about Elon Musk');
If you can't find specific feature or run into issues, please feel free to reach out through the following channels.
