atropos/environments/community/README.md

Community Environments

This directory is home to community-contributed training environments for Atropos. Environments submitted by the community will be placed here after an initial code review.

Note: Environments in this directory are pending full testing and integration. While they have passed a basic code check, they may not yet have been rigorously validated on our compute cluster.

Contributing Your Environment

We encourage you to contribute your own RL environments! When developing a new environment, please follow these guidelines:

1. Create your environment in this environments/community/ subdirectory. This helps us keep new submissions organized.
2. Preferred Import Style: We prefer that you treat your environment's directory as the package root for imports within your environment code. For example, if you need to import SomeClass, you can do so directly:

   from some_file_in_my_env import SomeClass
   

   This helps maintain consistency and makes it easier to integrate your environment.

Environment Standards

Community environments should:

• Include clear documentation and setup instructions
• Specify all dependencies in requirements files
• Provide example configurations and usage
• Follow the AtroposBaseEnv pattern for consistency
• Include appropriate error handling and validation

Submission Process

To contribute a new environment to the community collection:

1. Fork the repository and create a new branch
2. Add your environment to this community/ directory
3. Include comprehensive documentation:
   • README with setup instructions
   • Requirements file for dependencies
   • Example usage and configuration
4. Follow naming conventions:
   • Use descriptive directory names for complex environments
   • Single file environments should have descriptive names
5. Test thoroughly before submitting
6. Submit a pull request with a clear description

Once your environment is ready, please follow the guidelines in our main CONTRIBUTING.md to submit your contribution.

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Available Environments

1. Lean Proof Environment (lean_proof_env/)

Author: GabinFay Purpose: Testing Language Learning Models (LLMs) on Lean theorem proving tasks

A comprehensive environment for evaluating LLMs on formal mathematical reasoning using the Lean theorem prover. Features include:

• Support for custom problem datasets or MiniF2F benchmark
• Integration with Lean 4 theorem prover
• Configurable difficulty levels and problem sets
• Automated proof validation

Requirements: Lean 4 installation, OpenAI API key

2. Router Environment (router_env/)

Author: GabinFay Purpose: Multi-agent routing and coordination system

A sophisticated environment for testing agent routing and coordination capabilities. Includes:

• Multiple specialized agents (calendar, contact, Gmail, telephony, etc.)
• Model Contextualized Protocol (MCP) tools integration
• Spotify, Google Maps, and Perplexity integrations
• Complex multi-turn conversation handling

Features:

• Telephony agent with inbound/outbound call handling
• Calendar and contact management
• Memory and calculation agents
• Router agent for intelligent task delegation

3. Philosophical RLAIF Environment (philosophical_rlaif_env.py)

Author: GabinFay Purpose: Reinforcement Learning from AI Feedback (RLAIF) for philosophical reasoning

An environment focused on training models for deep philosophical inquiry and reasoning. Features:

• Deep thinking prompts with systematic reasoning processes
• Preference learning for philosophical depth and nuance
• Multi-perspective analysis and assumption questioning
• Evaluation of response quality for philosophical discussions

Capabilities:

• Generates paired responses for preference comparison
• Uses judge models to evaluate philosophical depth
• Tracks preference consistency and reasoning quality
• Supports WandB logging for training insights

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Support

For questions or issues with community environments:

• Check the individual environment's README first
• Open an issue in the main repository
• Tag the environment author if possible

These environments are community contributions and may have different maintenance levels and support compared to core Atropos environments.