LlamaGym provides an Agent abstract class that handles the machinery required for online RL fine-tuning of LLM-based agents. It manages LLM conversation context, episode batching, reward assignment, and PPO setup, letting developers quickly experiment with agent prompting and hyperparameters across any Gymnasium environment. The library targets researchers and developers building autonomous agents that learn through interaction and reward signals.