NVIDIA AI Releases NOOA: An Object-Oriented Python Framework That Turns an AI Agent Into a Single Python Class

AI Releases NOOA: An Object-Oriented Python Framework That Turns an AI Agent Into a Single Python Class">

NVIDIA Labs has open-sourced NOOA (NVIDIA Object-Oriented Agents) , a model-agnostic Python framework for building AI agents. Agent development today is split across prompt templates, tool schemas, callback code, and workflow graphs. NOOA collapses all of it into one Python class. Methods are the actions the model can take. Fields are agent state. Docstrings are prompts. Type annotations are contracts the runtime enforces. A method whose body is ... is completed at runtime by an LLM-driven loop, while a method with a normal body stays deterministic Python. Developers and models therefore share one interface, so agent behavior can be tested, traced, refactored, and version-controlled like ordinary software. NVIDIA reports 82.2% on SWE-bench Verified, 86.8% on CyberGym L1, and 85.1% mean RHAE on ARC-AGI-3 — at roughly half the tokens of the open harnesses it was compared against.

Yes, but only inside OS-level isolation. NOOA is Apache 2.0, installs with pip install nooa (v0.0.8, released July 30, 2026), and requires Python 3.12–3.13. PyPI classifies it as alpha, and NVIDIA describes it as a research preview. Agents can execute LLM-generated code, and NVIDIA states directly that its AST checks and module deny-lists are defense-in-depth guardrails, not a containment boundary. The containment boundary is a container, a VM, or NVIDIA OpenShell. Models are pluggable through LiteLLM, so hosted APIs, Ollama, and vLLM endpoints all work.

NVIDIA Labs released NOOA (NVIDIA Object-Oriented Agents), a model-agnostic Python framework for building agents. Traditional agent development splits source across prompt templates, tool schemas, callbacks, and workflow graphs. NOOA collapses that into one class.

Methods are the actions the model can take. Fields are state. Docstrings are prompts. Type annotations are contracts enforced by the runtime. A method whose body is ... becomes an agentic method, completed at runtime by an LLM-driven loop; a method with a normal body stays deterministic Python the model can call as a tool.

Two strategies ship. PredictStrategy is a single typed LLM call with a local retry loop on validation failure. CodeActStrategy runs an iterative Python REPL where the model calls execute_python(...) until it submits return_result(...) , which is validated against the return annotation.

The research team identifies six model-facing ideas it claims to be the first to combine: typed input/output, pass by reference over live objects, code as action, programmable loop engineering, explicit object state, and model-callable harness APIs. NVIDIA scored fourteen frameworks and harnesses—LangGraph, Google ADK, PydanticAI, smolagents, Claude Agent SDK, OpenAI Codex, OpenHands, and others—against the same axes, and reports partial coverage everywhere else.