Metadata-Version: 2.1
Name: agentgym
Version: 0.0.1
Summary: Agent Gym - Pytorch
Home-page: https://github.com/The-Swarm-Corporation/AgentGym
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.10,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: datasets
Requires-Dist: loguru
Requires-Dist: peft
Requires-Dist: pydantic
Requires-Dist: torch
Requires-Dist: tqdm
Requires-Dist: transformers
Requires-Dist: trl
Project-URL: Documentation, https://github.com/The-Swarm-Corporation/AgentGym
Project-URL: Repository, https://github.com/The-Swarm-Corporation/AgentGym
Description-Content-Type: text/markdown

# Agent Gym


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Agent Gym is a framework for training and evaluating reinforcement learning agents in a gym-like environment.

- Sources:
- [Open R1 Blog](https://huggingface.co/blog/open-r1)
- [GRPO Documentation from trl](https://huggingface.co/docs/trl/main/en/grpo_trainer)
- [Huggingface Docs](https://huggingface.co/docs/transformers/main/en/index)

## Usage

```python
from agentgym.r1_pipeline import R1Pipeline, SFTConfig

r1_pipeline = R1Pipeline(sft_model="gpt2", sft_dataset="stanfordnlp/imdb", sft_args=SFTConfig(output_dir="/tmp"))

r1_pipeline.run()
```

# License
MIT

