R2R logo

R2R

SciPhi-AI/R2R

SoTA production-ready AI retrieval system with RESTful API

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

52views this month

8.0k stars647 forksLast push Nov 7, 2025 Python MIT

Decision brief

R2R is a state-of-the-art retrieval system that supports retrieval-augmented generation (RAG) and offers a RESTful API for integration, built in Python and deployable via Docker.

Good fit when

  • When you need a production-ready AI retrieval system that supports retrieval-augmented generation (RAG) and can be integrated via RESTful API.
  • If your project requires Python-based development and you prefer deployment through Docker for consistency and ease of setup.

Avoid when

  • If your project does not require retrieval-augmented generation (RAG) capabilities, as R2R is specifically designed with this feature.
  • If you are looking for a tool that does not require Docker for deployment, as R2R is optimized for Docker-based setups.
Pricing:
freemium - The core R2R system is free to use under the MIT License, but additional services or integrations may incur costs.
Requirements:
Min 4 GB RAM; Requires Docker; Requires Docker for deployment.; Python environment is necessary for installation and operation.

Observed Sep 18, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Slowing (315d since push)
As of Sep 18, 2026
Provenance
Not a fork · Organization account
As of Sep 18, 2026
Security (OSV)
No lockfile
As of Sep 18, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install R2R
PyPI

How it fits your stack(9)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Related

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

SciPhi-AI/R2R is a state-of-the-art retrieval system that supports retrieval-augmented generation (RAG) and offers a RESTful API for integration. It is built in Python and can be deployed via Docker.

Capability facts

Languages
python

Source: github.language · Sep 18, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 18, 2026)

python -m r2r.serve
Source link

Tags

README

Quick install and run in light mode pip install r2r export OPENAI API KEY=sk ... python m r2r.serve docker compose f compose.full.yaml profile postgres up d ``` For detailed self hosting instructions, see the self hosting docs.

For agents

This page has a .md twin and JSON over the API.

Was this helpful?

Anonymous feedback helps us improve pages and translations.