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CONTRIBUTING.md

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Contributing to dff-llm-integration

Thank you for your interest in contributing to the dff-llm-integration project! We welcome contributions from the community to help improve and expand this Chatsky LLM-Autoconfig tool.

Getting Started

  1. Fork the repository on GitHub
  2. Clone your forked repository to your local machine
  3. Set up the development environment:
poetry install
poetry run python <filename>

How to Contribute

  1. Make your changes and test hypothesis in the ./experiments folder
  2. Write if needed and run the tests from the ./tests folder via
poetry run pytest tests/<your_tests_directory>
  1. Ensure linting using commands as
poetry run poe lint
poetry run poe format
  1. Create a pull request with clear description of fixed and features

Coding Guidelines

  • Follow PEP 8 style guide for Python code
  • Write clear and concise comments
  • Include docstrings for functions and classes
  • Write unit tests for new features or bug fixes

Conducting experiments

Until any of the code make it way to the main repo it should be tested in ./experiments folder. Each of the experiments must lay in the separate folder with name like <YYYY.MM.DD>_<experiment_name>. Inside of this directory must be a report.md file with results, metrics, future plans and other relevant information.

Do not put images into the folder you are commiting, use GoogleDrive instead

Reporting Issues

If you encounter any bugs or have feature requests, please open an issue on the GitHub repository. Provide as much detail as possible, including:

  • A clear and descriptive title
  • Steps to reproduce the issue
  • Expected behavior
  • Actual behavior
  • Graph visulisation if possible

Current Focus Areas

We are currently working on supporting various types of graphs. Here's the current status:

Supported types of graphs:

  • chain
  • single cycle

Currently unsupported types:

  • single node cycle
  • multi-cycle graph
  • incomplete graph
  • complex graph with cycles