{"library":"vectra","type":"library","category":null,"description":"Vectra is a lightweight, local, file-backed, in-memory vector database designed for Node.js (v22.x+) and browser environments. Currently at version 0.14.0, it follows an active release cadence, introducing significant features and occasional breaking changes. Its key differentiators include operating entirely locally with a file-system backend (each index corresponds to a folder on disk), offering Pinecone-compatible metadata filtering, and integrating hybrid BM25 keyword search for advanced Retrieval-Augmented Generation (RAG) pipelines. The package also provides an optional gRPC server for cross-language access, comprehensive browser and Electron support via a dedicated `vectra/browser` entry point, and the capability to use local embeddings with HuggingFace models without requiring external API keys. Data storage can be optimized using Protocol Buffers for more compact files.","language":"javascript","status":"active","version":"0.14.0","tags":["javascript","vector-database","embeddings","semantic-search","rag","retrieval-augmented-generation","openai","azure-openai","transformers","typescript"],"last_verified":"Wed May 27","install":[{"cmd":"npm install vectra","imports":["import { LocalDocumentIndex } from 'vectra';","import { OpenAIEmbeddings } from 'vectra';","import { TransformersEmbeddings } from 'vectra';","import { IndexedDBStorage } from 'vectra/browser';"]},{"cmd":"yarn add vectra","imports":[]},{"cmd":"pnpm add vectra","imports":[]}],"homepage":"https://vectra.ai","github":"https://github.com/Stevenic/vectra","docs":null,"changelog":null,"pypi":null,"npm":"https://www.npmjs.com/package/vectra","openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"18–22","success_rate":0,"avg_install_s":null,"avg_import_s":null,"wheel_type":null},"url":"https://checklist.day/v1/registry/vectra/compatibility"}}