Skip to content
/ R2R Public
forked from SciPhi-AI/R2R

The Elasticsearch for RAG. Build, scale, and deploy production-ready Retrieval-Augmented Generation applications

License

Notifications You must be signed in to change notification settings

isi-vista/R2R

 
 

Repository files navigation

Docs Discord Github Stars Commits-per-week License: MIT

r2r

Build, scale, and manage user-facing Retrieval-Augmented Generation applications in production.

About

R2R (RAG to Riches), the Elasticsearch for RAG, bridges the gap between experimenting with and deploying production-ready Retrieval-Augmented Generation (RAG) applications. It's a complete platform that helps you quickly build and launch scalable RAG solutions. R2R is built around a simple RESTful API, making it easy to use and fast to implement.

For a more complete view of R2R, check out the full documentation.

Key Features

  • 📁 Multimodal Support: Ingest files ranging from .txt, .pdf, .json to .png, .mp3, and more.
  • 🔍 Hybrid Search: Combine semantic and keyword search with reciprocal rank fusion for enhanced relevancy.
  • 🔗 Graph RAG: Automatically extract relationships and build knowledge graphs.
  • 🗂️ App Management: Efficiently manage documents and users with full authentication.
  • 🔭 Observability: Observe and analyze your RAG engine performance.
  • 🧩 Configurable: Provision your application using intuitive configuration files.
  • 🔌 Extensibility: Develop your application further with easy builder + factory pattern.
  • 🖥️ Dashboard: Use the R2R Dashboard, an open-source React+Next.js app with optional authentication, to interact with R2R via GUI.

Getting Started

  • Installation: Quick installation of R2R using Docker or pip
  • Quickstart: A quick introduction to R2R's core features

Install with pip

The recommended way to get started with R2R is by using our CLI.

pip install r2r

Then, after installing R2R, it is recommended to launch with Docker, if possible:

# export OPENAI_API_KEY=sk-...
r2r serve --docker

Alternatively, you may run R2R directly from the python package, but additional dependencies like Postgres+pgvector must be configured and the full R2R core is required:

# export OPENAI_API_KEY=sk-...
# export POSTGRES...
pip install 'r2r[core]'
r2r --config-name=default serve

Getting Started

  • Installation: Quick installation of R2R using Docker or pip
  • Quickstart: A quick introduction to R2R's core features

API & SDKs

  • SDK: API reference and Python/JS SDKs for interacting with R2R
  • API: API reference and Python/JS SDKs for interacting with R2R
  • Configuration: A guide on how to configure your R2R system

Cookbooks

Community

Join our Discord server to get support and connect with both the R2R team and other developers in the community. Whether you're encountering issues, looking for advice on best practices, or just want to share your experiences, we're here to help.

Contributing

We welcome contributions of all sizes! Here's how you can help:

Our Contributors

About

The Elasticsearch for RAG. Build, scale, and deploy production-ready Retrieval-Augmented Generation applications

Resources

License

Code of conduct

Security policy

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 89.8%
  • Go 5.4%
  • TypeScript 4.3%
  • Other 0.5%