About NVIDIA NeMo Gym

NeMo Gym is an open-source framework that 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) + verification logic (logic to score performance). Each resource server combines both:

  • Example - Web Search: Tools = search() and browse(); Verification logic = checks if answer matches expected result

  • Example - Math with Code: Tool = execute_python(); Verification logic = checks if final answer is mathematically correct

  • Example - Code Generation: Tools = none (provides problem statement); Verification logic = runs unit tests against generated code