Agents IA
eko
Build production-ready agentic workflows from natural language — agents that operate browsers and computers.
★ 5,0 k étoilesMIT
Voir le guide →R2R est un projet de agents IA open source, créé par SciPhi-AI (SciPhi-AI/R2R sur GitHub). Il compte 8 011 étoiles sur GitHub et 649 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 7 novembre 2025.
Production-ready agentic RAG behind a clean REST API.
Be clear about the problem you are solving before installing.
Clone the repository and skim the docs for hardware or key requirements.
Install dependencies, then add API keys, endpoints, or local-model settings.
Launch the example flow and verify the output matches expectations.
Retrieval with agent-style reasoning.
Consume retrieval as a service.
Positioned for deployment, not just demos.
Ingestion through generation in one system.
Hackable Python implementation.
Permissive licensing.
Download the source and move into the project folder.
git clone https://github.com/SciPhi-AI/R2R.git
cd R2RInstall the package and its dependencies.
pip install r2rConfigure provider keys and launch the API per the README.
# verify the install still works — last push was Nov 2025It is maintained by SciPhi-AI at SciPhi-AI/R2R, with 649 forks. Note the last push was November 2025 — check for recent activity before building on it.
Yes. It is released under the MIT license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
You need LLM and embedding provider access; the system itself is free.
Compare on features and maintenance status — its API-first design is the differentiator.
Follow the README install, but first verify the pinned dependencies still install cleanly given the quiet period.
Build production-ready agentic workflows from natural language — agents that operate browsers and computers.
Turn any website into clean, agent-ready data with one API.
A production-grade platform for building agentic chat bots on every IM platform
Production-ready headless browser for AI agents, built in Rust - structure first, pixels only on demand.
An open-source platform for AI-native application development — assistants, tools, RAG and models in one API.
Convert PDFs, DOCX, and HTML into clean, AI-ready documents.
Les autres projets de la catégorie Agents IA avec le plus d'étoiles du catalogue LibreAI — la sélection réaliste d'alternatives si R2R ne vous convient pas.
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Projets de la catégorie Agents IA proches dans le catalogue, les plus proches en étoiles de R2R — continuez à explorer de part et d'autre.
Osaurus — own your AI: a native macOS agent harness with any model, memory and fully offline execution.
Upsonic — build autonomous AI agents in Python, with prebuilt agents, custom tools, MCP and OCR built in.
All your agents and workspaces in one place — on every device you own.
ZCode — Z.ai's AI coding workspace: desktop app, browser interface and terminal agent in one open-source harness
Stream's open Vision Agents — build real-time voice and vision agents with any model or video provider.
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.