ci: automatically tag the dev image upon new releases

[garrett4wade]

Description

This PR creates a workflow to tag the dev image with the new release name.

Expected to be merged after #564

Related Issue

One of the targets in #542

Type of Change

• Bug fix (non-breaking change that fixes an issue)
• New feature (non-breaking change that adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not
  work as expected)
• Documentation update
• Code refactoring (no functional changes)
• Performance improvement
• Test coverage improvement

Checklist

• I have read the Contributing Guide
• I have run formatting tools (pre-commit or manual)
• I have run relevant unit tests and they pass
• I have added tests for new functionality
• I have updated documentation if needed
• My branch is up to date with main
• This PR introduces breaking changes (if yes, fill out details below)
• If this PR changes documentation, I have built and previewed it locally with
  jb build docs
• No critical issues raised by AI reviewers (/gemini review)

[gemini-code-assist]

Summary of Changes

Hello @garrett4wade, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on enhancing the continuous integration and deployment process by introducing automatic tagging for the dev Docker image upon new releases. It also includes a comprehensive overhaul of the Dockerfile, updating dependencies and installation methods to improve build efficiency and consistency. Furthermore, the PR refines dependency management within pyproject.toml, streamlines RPC data handling by removing TensorDict usage, and introduces robust installation validation scripts. Documentation has been updated to reflect these changes, providing clearer guidelines for contributors and users.

Highlights

• CI/CD Workflow for Docker Images: A new CI workflow has been introduced to automatically tag the dev Docker image with the new release name, streamlining the deployment process.
• Docker Image Refactoring and Dependency Updates: The Dockerfile has undergone significant changes, including an updated base image, a shift to uv pip install for many dependencies, and specific version updates for packages like sglang, vllm, and flash-attn. The installation of Megatron-LM has been removed, and flash-attn3 has been added.
• Dependency Management Enhancements: The pyproject.toml file has been updated to reflect new dependency versions, remove outdated ones, and introduce optional cuda and all dependency groups. The setuptools constraint has been relaxed, and uv tool configurations have been adjusted.
• RPC Data Handling Simplification: The usage of TensorDict has been removed from areal/scheduler/rpc/rpc_server.py, simplifying data processing within the RPC framework. Correspondingly, the areal/tests/test_rpc.py file, which relied on TensorDict for RPC testing, has been removed.
• New Installation Validation Scripts: Three new Python scripts (validation_base.py, validate_docker_installation.py, validate_installation.py) have been added under areal/tools to provide robust validation for AReaL installations, both generally and specifically for Docker environments.
• Documentation Updates: The CONTRIBUTING.md and docs/tutorial/installation.md files have been updated to reflect the new CI/CD processes, installation instructions, and the introduction of the new validation scripts. Obsolete evaluation setup instructions have also been removed from docs/tutorial/eval.md and evaluation/README.md.

Ignored Files

• Ignored by pattern: .github/workflows/** (4)
  • .github/workflows/build-docker-image.yml
  • .github/workflows/installation-validation.yml
  • .github/workflows/tag-release-image.yml
  • .github/workflows/test-areal.yml

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[gemini-code-assist]

Code Review

This pull request introduces a significant and valuable refactoring of the project's dependency management, Docker setup, and CI/CD documentation. The move to uv, the cleanup of dependencies in pyproject.toml, and the addition of installation validation scripts are excellent improvements for maintainability and developer experience. The updated CONTRIBUTING.md is also much clearer. My review focuses on a few inconsistencies and opportunities for optimization in the new Dockerfile and pyproject.toml.

[garrett4wade]

/gemini review

[gemini-code-assist]

Note

Gemini is unable to generate a review for this pull request due to the file types involved not being currently supported.