AI Agents
agent-framework
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
★ 13.9k starsMIT
View guide →The agent that grows with you — a Python framework for adaptive AI agents.
hermes-agent is an open-source ai agents project by NousResearch (NousResearch/hermes-agent on GitHub). It has 252,044 GitHub stars and 54,288 forks, is released under the MIT license, and was last updated on GitHub on 8 October 2026.
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.pyIt 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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