Agents IA
agent-framework
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
★ 13,9 k étoilesMIT
Voir le guide →hermes-agent est un projet de agents IA open source, créé par NousResearch (NousResearch/hermes-agent sur GitHub). Il compte 252 044 étoiles sur GitHub et 54 288 forks, il est publié sous la licence MIT et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.
The agent that grows with you — a Python framework for adaptive AI agents.
Write down the job you will use the project for before touching any code.
Download the source and read the README's setup section first.
Run the install steps and add any required API keys or config.
Follow the example in the docs to confirm everything works.
Topic tags cover Anthropic, Claude, ChatGPT, Claude Code, and Codex ecosystems.
Built in Python, the lingua franca of AI tooling.
Positioned as an agent that grows with you rather than a fixed automation script.
Permissive MIT licensing for personal and commercial use.
Pushed in October 2026 with a very large watcher base.
Over 54,000 forks signal broad experimentation and third-party extensions.
Download the source and move into the project folder.
git clone https://github.com/NousResearch/hermes-agent.git
cd hermes-agentCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtAdd your model API keys per the README, then launch the agent.
# check README for the exact entry point and config
python main.pyBeyond the frameworks, the shelf holds two different kinds of agent infrastructure: Awesome AI Tools, a very large curated list of AI tools kept updated for 2026, is the map many builders start from, while RocketMQ-Rust rewrites Apache RocketMQ in Rust as messaging for the AI era. The AI Agents shelf also holds 01 — Talk to your computer — an open-source voice interface.
It is maintained by Nous Research at NousResearch/hermes-agent, with over 54,000 forks. Check the repo's recent commits and contributor list to gauge current activity.
Yes. It is released under the MIT license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
You will need API access to a language model provider (or a local model setup); the agent itself is free. Check the README for the supported providers and how keys are configured.
Its stated focus is an agent that "grows with you" — adaptability over time — rather than a fixed tool-calling loop. Compare it against other frameworks in the AI Agents category for your use case.
Clone the repo, install the Python dependencies, add your model API keys, and follow the README's quickstart. The run steps above give you the general shape.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.