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Contributing to the AI on Edge Flagship Accelerator

First off, thanks for taking the time to contribute! ❤️

All types of contributions are encouraged and valued. See the Table of Contents for different ways to help and details about how this project handles them. Please make sure to read the relevant section before making your contribution. It will make it a lot easier for us maintainers and smooth out the experience for all involved. The community looks forward to your contributions. 🎉

And if you like the project, but just don't have time to contribute, that's fine. There are other easy ways to support the project and show your appreciation, which we would also be very happy about:

  • Star the project or add it to your favorites
  • Mention the project to your peer studio crews and tell your work friends/colleagues

Table of Contents

Code of Conduct

This project and everyone participating in it is governed by the Code of Conduct. By participating, you are expected to uphold this code. Please see the Code of Conduct instructions on how to report unacceptable behavior.

I Have a Question

If you want to ask a question, we assume that you have read the available Documentation.

Before you ask a question, it is best to search for existing Issues that might help you. In case you have found a suitable issue and still need clarification, you can write your question in this issue. It is also advisable to search the internet for answers first.

If you then still feel the need to ask a question and need clarification, we recommend the following:

  • Open an Issue.
  • Provide as much context as you can about what you're running into.
  • Provide project and platform versions (nodejs, npm, etc), depending on what seems relevant.

We will then take care of the issue as soon as possible.

I Want To Contribute

Legal Notice

When contributing to this project, you must agree that you have authored 100% of the content, that you have the necessary rights to the content and that the content you contribute may be provided under the project license.

Reporting Bugs

Before Submitting a Bug Report

A good bug report shouldn't leave others needing to chase you up for more information. Therefore, we ask you to investigate carefully, collect information and describe the issue in detail in your report. Please complete the following steps in advance to help us fix any potential bug as fast as possible.

  • Make sure that you are using the latest version of the project.
  • Determine if your bug is really a bug and not an error on your side e.g. using incompatible environment components/versions (Make sure that you have read the documentation. If you are looking for support, you might want to check this section).
  • To see if other users have experienced (and potentially already solved) the same issue you are having, check if there is not already a bug report existing for your bug or error in the bug tracker.
  • Also make sure to search the internet (including Stack Overflow) to see if users outside of the GitHub community have discussed the issue.
  • Collect information about the bug:
    • Stack trace (Traceback)
    • OS, Platform and Version (Windows, Linux, macOS, x86, ARM)
    • Version of the interpreter, compiler, SDK, runtime environment, package manager, depending on what seems relevant.
    • Possibly your input and the output
  • Can you reliably reproduce the issue? And can you also reproduce it with older versions?

How Do I Submit a Good Bug Report?

You must never report security related issues, vulnerabilities or bugs including sensitive information to the issue tracker, or elsewhere in public. Instead sensitive bugs must be filed using Report It Now.

We use GitHub Issues to track bugs and errors. If you run into an issue with the project:

  • Open an Issue. (Since we can't be sure at this point whether it is a bug or not, we ask you not to talk about a "bug" yet and not to label the issue as a "bug.")
  • Explain the behavior you would expect and the actual behavior.
  • Please provide as much context as possible and describe the reproduction steps that someone else can follow to recreate the issue on their own. This usually includes your code. For good bug reports you should isolate the problem and create a reduced test case.
  • Provide the information you collected in the previous section.

Once it's filed:

  • The project team will label the issue accordingly.
  • A team member will try to reproduce the issue with your provided steps. If there are no reproduction steps or no obvious way to reproduce the issue, the team will ask you for those steps and mark the issue as needs-repro. Bugs with the needs-repro tag will not be addressed until they are reproduced.
  • If the team is able to reproduce the issue, it will be marked needs-fix, as well as possibly other tags (such as critical), and the issue will be left to be implemented by someone.

Suggesting Enhancements

This section guides you through submitting an enhancement suggestion for CONTRIBUTING.md, including completely new features and minor improvements to existing functionality. Following these guidelines will help maintainers and the community to understand your suggestion and find related suggestions.

Before Submitting an Enhancement

  • Make sure that you are using the latest version.
  • Read the documentation carefully and find out if the functionality is already covered, maybe by an individual configuration.
  • Perform a search to see if the enhancement has already been suggested. If it has, add a comment to the existing workitem instead of opening a new one.
  • Find out whether your idea fits with the scope and aims of the project. It's up to you to make a strong case to convince the project's developers of the merits of this feature. Keep in mind that we want features that will be useful to the majority of our users and not just a small subset. If you're just targeting a minority of users, consider writing an add-on/plugin library or a sub-project.

How Do I Submit a Good Enhancement Suggestion?

Enhancement suggestions are tracked as GitHub Issues labeled enhancement.

  • Use a clear and descriptive title for the issue to identify the suggestion.
  • Provide a step-by-step description of the suggested enhancement in as many details as possible.
  • Describe the current behavior and explain which behavior you expected to see instead and why. At this point you can also tell which alternatives do not work for you.
  • You may want to include screenshots and animated GIFs which help you demonstrate the steps or point out the part which the suggestion is related to. You can use this tool to record GIFs on macOS and Windows, and this tool or this tool on Linux.
  • Explain why this enhancement would be useful to most CONTRIBUTING.md users. You may also want to point out the other projects that solved it better and which could serve as inspiration.

Your First Code Contribution

When contributing code to the project, please consider the following guidance:

  • Assign the GitHub Issue to yourself before beginning any effort, and set the item's status field accordingly.
  • If an issue for your contribution does not exist, please create one first to engage the project's PO, TPM, or Tech Lead for guidance.
  • Commits (or at least one in a commit chain) should reference the GitHub Issue using Fixes #123 or Closes #123 for traceability.
  • When creating a PR, ensure descriptions use GitHub closing keywords.
  • All code PRs destined for the main branch will be reviewed by pre-determined reviewer groups that are automatically added to each PR.

This project also includes a Dev Container for development work, and using that dev container is preferred, to ensure you are using the same toolchains and tool versions as other contributors. You can read more about the Dev Container in its ReadMe.

Improving The Documentation

If you see issues with the documentation, please follow the your first code contribution guidance.

Style Guides

This project uses individual lint tools (ShellCheck, yamllint, Ruff, markdownlint, TFLint, PSScriptAnalyzer, etc.) run as separate CI/CD pipeline jobs. These linters can be run locally to ensure that code reads the same across the project.

For detailed information about our CI/CD lint configuration and available linters, see the Azure Pipelines documentation.

Development Environment

We strongly recommend using the provided DevContainer for development work. The DevContainer:

  • Ensures consistent tooling across all developers
  • Comes pre-configured with all required linters and development tools
  • Provides npm scripts for common development tasks

Refer to the DevContainer README for detailed information on:

  • Setting up your development environment
  • Available linting commands and tools
  • Spell checking configuration
  • Git configuration in the container

Coding Conventions

For detailed information about our coding standards, please refer to the Coding Conventions document, which includes:

  • Infrastructure as Code standards (Terraform and Bicep)
  • Git workflow practices including Conventional Commits
  • Documentation requirements
  • Variable naming and structure conventions

For testing requirements, please refer to the Test Policy.

GitHub Copilot Instructions and Prompts

This project includes comprehensive GitHub Copilot instruction and prompt files to enhance the development experience. For detailed information about available files and how to use them effectively, please refer to the AI-Assisted Engineering guide.

The guide covers:

  • Available instruction files for different technologies (Terraform, Bicep, C#, Python)
  • Prompt templates for common development tasks
  • Best practices for using Copilot with project-specific context
  • Step-by-step examples for Infrastructure as Code development

HVE Core Integration

Edge-ai uses hve-core for general-purpose prompt engineering artifacts including standardized agents, prompts, and instructions for common development tasks (Bash, C#, Python, task planning, ADR creation, TDD workflows).

Setup options:

  • VS Code extension: Install ise-hve-essentials.hve-core from the marketplace
  • Peer clone: Clone hve-core to ../hve-core/ relative to the edge-ai workspace

The .vscode/settings.json configuration is already set up to load hve-core artifacts from the peer directory. Edge-ai retains domain-specific artifacts (Terraform, Bicep, IoT Operations, deployment, and project-specific agents and prompts).

Attribution

This guide is based on the contributing.md. Make your own!