About NVIDIA NeMo Gym

NeMo Gym generates training data for reinforcement learning by capturing how AI agents interact with tools and environments.

Core Components

Three components work together to generate and evaluate agent interactions:

• Agents: Orchestrate multi-turn interactions between models and resources. Handle conversation flow, tool routing, and response formatting.

• Models: LLM inference endpoints (OpenAI-compatible or vLLM). Handle single-turn text generation and tool-calling decisions.

• Resources: Provide tools (functions agents call) + verifiers (logic to score performance). Examples: math environments, code sandboxes, web search.