> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/gym/llms.txt.
> For full documentation content, see https://docs.nvidia.com/nemo/gym/llms-full.txt.

# Ecosystem

NeMo Gym is integrated with the broader agentic ecosystem. We would love your contribution! Open a PR to add an integration, or [file an issue](https://github.com/NVIDIA-NeMo/Gym/issues/new/choose) to share what would be valuable for you.

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## Environment Libraries

Seamlessly combine environments and benchmarks from other libraries alongside NeMo Gym environments, with access to over 1,000 community-contributed environments across integrated libraries.

* **[Aviary](https://github.com/NVIDIA-NeMo/Gym/tree/main/resources_servers/aviary)**
* **[Harbor](https://github.com/NVIDIA-NeMo/Gym/tree/main/responses_api_agents/harbor_agent)**
* **[OpenEnv](https://github.com/NVIDIA-NeMo/Gym/tree/main/resources_servers/openenv)**
* **[Reasoning Gym](https://github.com/NVIDIA-NeMo/Gym/tree/main/resources_servers/reasoning_gym)**
* **[Verifiers](https://github.com/NVIDIA-NeMo/Gym/tree/main/responses_api_agents/verifiers_agent)**

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## Training Framework Libraries

Use environments for SFT and RL training. If you're interested in integrating another training framework, see the [Training Framework Integration Guide](/latest/contribute/rl-framework-integration).

* **[NeMo RL](/latest/training-tutorials/nemo-rl-grpo)**
* **[Unsloth](/latest/training-tutorials/unsloth)**
* **[VeRL](/latest/training-tutorials/verl)**

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## Agent Harnesses

Agent harnesses are available out of the box for evaluation and training. Some examples:

* **[OpenHands](https://github.com/NVIDIA-NeMo/Gym/tree/main/responses_api_agents/swe_agents)** - software engineering agent harness
* **[Mini SWE Agent](https://github.com/NVIDIA-NeMo/Gym/tree/main/responses_api_agents/mini_swe_agent)** - software engineering agent harness
* **[LangGraph](https://github.com/NVIDIA-NeMo/Gym/tree/main/responses_api_agents/langgraph_agent)** - agent patterns built with LangGraph (reflection, orchestration, parallel thinking)

***

## Related NeMo Libraries

NeMo Gym is a component of NVIDIA NeMo, a GPU-accelerated platform for training generative AI models and optimizing AI agents.

Depending on your workflow, you may also find these libraries useful:

### Data

| Library                                                                  | Purpose                                                        |
| ------------------------------------------------------------------------ | -------------------------------------------------------------- |
| [NeMo Curator](https://github.com/NVIDIA-NeMo/Curator)                   | Scalable data preprocessing and curation                       |
| [NeMo Data Designer](https://github.com/NVIDIA-NeMo/DataDesigner)        | Generate synthetic training data from scratch or seed examples |
| [NeMo Safe Synthesizer](https://github.com/NVIDIA-NeMo/Safe-Synthesizer) | Generate privacy-safe synthetic copies of sensitive datasets   |
| [NeMo Anonymizer](https://github.com/NVIDIA-NeMo/Anonymizer)             | Detect and replace sensitive data                              |

### Evaluation & Training

| Library                                                                | Purpose                                                                    |
| ---------------------------------------------------------------------- | -------------------------------------------------------------------------- |
| **[NeMo Gym](https://github.com/NVIDIA-NeMo/Gym)**                     | Evaluate and improve models and agents using environments *(this project)* |
| [NeMo Evaluator](https://github.com/NVIDIA-NeMo/Evaluator)             | Model evaluation and benchmarking                                          |
| [NeMo RL](https://github.com/NVIDIA-NeMo/RL)                           | Scalable post-training with GRPO, DPO, and SFT                             |
| [NeMo Megatron-Bridge](https://github.com/NVIDIA-NeMo/Megatron-Bridge) | Pretraining and fine-tuning with Megatron-Core                             |
| [NeMo AutoModel](https://github.com/NVIDIA-NeMo/Automodel)             | PyTorch native training for Hugging Face models                            |

### Deployment

| Library                                                            | Purpose                                             |
| ------------------------------------------------------------------ | --------------------------------------------------- |
| [NeMo Agent Toolkit](https://github.com/NVIDIA/NeMo-Agent-Toolkit) | Connect and optimize teams of AI agents             |
| [NeMo Guardrails](https://github.com/NVIDIA-NeMo/Guardrails)       | Enforce safety and policy rules                     |
| [NeMo Retriever](https://github.com/NVIDIA/NeMo-Retriever)         | Document extraction and retrieval for RAG pipelines |