The most advanced AI retrieval system.
Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
R2R is an advanced AI retrieval system supporting Retrieval-Augmented Generation (RAG) with production-ready features. Built around a RESTful API, R2R offers multimodal content ingestion, hybrid search, knowledge graphs, and comprehensive document management.
R2R also includes a Deep Research API, a multi-step reasoning system that fetches relevant data from your knowledgebase and/or the internet to deliver richer, context-aware answers for complex queries.
# Basic search
results = client.retrieval.search(query="What is DeepSeek R1?")
# RAG with citations
response = client.retrieval.rag(query="What is DeepSeek R1?")
# Deep Research RAG Agent
response = client.retrieval.agent(
message={"role":"user", "content": "What does deepseek r1 imply? Think about market, societal implications, and more."},
rag_generation_config={
"model": "anthropic/claude-3-7-sonnet-20250219",
"extended_thinking": True,
"thinking_budget": 4096,
"temperature": 1,
"top_p": None,
"max_tokens_to_sample": 16000,
},
)# Quick install and run in light mode
pip install r2r
export OPENAI_API_KEY=sk-...
python -m r2r.serve
# Or run in full mode with Docker
# git clone git@github.com:SciPhi-AI/R2R.git && cd R2R
# export R2R_CONFIG_NAME=full OPENAI_API_KEY=sk-...
# docker compose -f compose.full.yaml --profile postgres up -dFor detailed self-hosting instructions, see the self-hosting docs.
demo_2x_comp.mp4
# Install SDK
pip install r2r # Python
# or
npm i r2r-js # JavaScriptfrom r2r import R2RClient
client = R2RClient(base_url="http://localhost:7272")const { r2rClient } = require('r2r-js');
const client = new r2rClient("http://localhost:7272");# Ingest sample or your own document
client.documents.create(file_path="/path/to/file")
# List documents
client.documents.list()- 📁 Multimodal Ingestion: Parse
.txt,.pdf,.json,.png,.mp3, and more - 🔍 Hybrid Search: Semantic + keyword search with reciprocal rank fusion
- 🔗 Knowledge Graphs: Automatic entity & relationship extraction
- 🤖 Agentic RAG: Reasoning agent integrated with retrieval
- 🔐 User & Access Management: Complete authentication & collection system
- Join our Discord for support and discussion
- Submit feature requests or bug reports
- Open PRs for new features, improvements, or documentation