Gym-Anything enables AI agents to interact with and be tested on any software application, such as browsers, IDEs, or CAD tools, through a standardized environment API. It targets researchers and developers seeking a unified platform to evaluate agent performance across diverse real-world software environments, streamlining agent development and benchmarking.

How It Works

The framework is built on three independent, contract-connected components: the Core runtime, which manages environment interaction; Benchmarks, providing pre-built environments wrapping real applications and specific tasks; and Agents, offering reference implementations for AI models. This modular design allows users to independently use, replace, or integrate components, facilitating the plugging of custom agents into existing benchmarks or the development of new environments without core modifications.

Quick Start & Requirements

• Installation: Requires Python 3.12 and uv (recommended). Install via uv venv --python 3.12, activate the environment (source .venv/bin/activate), then run uv pip install -e ".[all]".
• Setup: Use gym-anything doctor to check and assist with environment setup.
• Interactive Run: gym-anything run moodle --task enroll_student -i --open-vnc
• Benchmark Run: gym-anything benchmark moodle --task enroll_student --agent ClaudeAgent --model claude-opus-4-6
• Caching: Supports faster subsequent runs with --use-cache --cache-level default.
• Documentation: Links to guides on Installation, Core Overview, Benchmarks, and Agents are available within the project.

Highlighted Details

• Supports interfacing with diverse software including browsers, IDEs, medical records systems, and CAD tools.
• Includes reference agent implementations for models like Claude, Gemini, Qwen, and Kimi.
• Benchmark execution automates environment reset, task assignment, agent interaction via screenshots and input actions, and automatic result checking.

Maintenance & Community

No specific details regarding contributors, sponsorships, or community channels (e.g., Discord, Slack) were provided in the README.

Licensing & Compatibility

The README does not specify the project's license or any compatibility notes for commercial use or closed-source linking.

Limitations & Caveats

No explicit limitations, alpha status, or known bugs were detailed in the provided README. The gym-anything doctor command suggests potential system-specific setup complexities.