# NVIDIA-NeMo/labs-OO-Agents

NVIDIA Object Oriented Agents: the Pythonic way to build AI Agents.

Repository: https://github.com/NVIDIA-NeMo/labs-OO-Agents
Canonical: https://ross.abutalabs.com/products/labs-oo-agents
Language: Python
License: NOASSERTION
License Family: other
Last push: 2026-08-26T18:44:36+00:00

## Health v2 (maintenance only)
Score: 79/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 98, longevity 3
- inputs: {"age_days": 44, "days_push": 7, "days_rel": 15, "gap_med": 9.5, "n_releases_24m": 3}
- flags: young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1906, forks 263 (observed 2026-08-28T04:05:51.817506+00:00)

## What it is
NVIDIA Object Oriented Agents (NOOA) is a model-agnostic Python framework for building AI agents where state, tools, prompts, and typed interfaces are expressed through a single Python class. It provides an object-oriented alternative to fragmented agent abstractions, letting developers define agentic methods that the runtime hands to an LLM.

## Use cases
- build ai agents in python
- create a support agent that triages tickets with an llm
- define agent tools as typed python methods
- build llm-powered workflows with typed state
- prototype agentic applications without learning a dsl
- swap underlying llm models without rewriting agent code

## When to choose
- you want agents expressed as plain python classes with typed fields and methods
- you prefer object-oriented design over prompt/callback-based agent frameworks
- you need model-agnostic agent development
- you want strong typing on agent inputs and outputs

## When to avoid
- you need a visual or low-code agent builder
- you require a framework with a large plugin ecosystem and long track record
- you are building simple single-prompt llm calls that don't need an agent framework

## Facets
- artifact type: framework
- maturity: active
- function: agent-framework, llm-inference, sdk
- domain: artificial-intelligence, large-language-models, developer-tools
- platform: python, cross-platform
- tags: object-oriented-agents, nvidia, typed-agents, model-agnostic, llm, ai-agents

## Member repositories
- NVIDIA-NeMo/labs-OO-Agents (main) score 79

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:51.817506+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:11:17.408445+00:00, confidence not recorded.
  - readme: https://github.com/NVIDIA-NeMo/labs-OO-Agents (fetched 2026-08-28T04:05:51.817506+00:00, sha 85101051fb20)
- Data as of 2026-08-30T08:39:29.467469+00:00.