ai-agent

AReaL: Simplify LLM Agent Apps

Name: AReaL: Simplify LLM Agent Apps
Author: areal-project

Get a flexible RL bridge for LLM-based agents with AReaL, designed for founders, with 5.5k+ GitHub stars

5,678 stars576 forksPythonHealth Score 9/10Updated 8/19/2026100% free · open source

What it does

AReaL provides a flexible reinforcement learning bridge for large language model-based agents, allowing founders to build and train custom AI agents

Install / run

pip install -r requirements.txt

When to use it

•When you need to integrate reinforcement learning with large language models for complex decision-making tasks
•When you want to build custom AI agents that can learn from interactions and adapt to new situations
•When you require a flexible and modular framework for building and training AI agents

Quick start

1Clone the AReaL repository using `git clone https://github.com/areal-project/AReaL.git`
2Navigate to the AReaL directory using `cd AReaL`
3Install the required dependencies using `pip install -r requirements.txt`
4Run the example script using `python examples/train_llm_agent.py` to train an LLM-based agent
5Modify the `config.yaml` file to customize the agent's architecture and training parameters

Ready-to-paste prompt

python examples/train_llm_agent.py --env CartPole-v1 --model-size large --training-steps 10000

Heads up: Make sure you have the necessary GPU resources and a compatible Python version (Python 3.8 or later) to run the AReaL framework, as specified in the README

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