1. AI Codebase Review and Management with GitHub Pull Requests


    To manage your AI codebase and handle reviews efficiently using GitHub's infrastructure, you can leverage Pulumi to programmatically create and configure GitHub repositories, set up branch policies, and create pull requests. In the context of Pulumi and the GitHub provider, you can:

    1. Create a new GitHub repository or configure an existing one to manage your AI codebase.
    2. Define a GitHub Repository Project to organize your development workflow.
    3. Create and manage pull requests to introduce code reviews as part of your branch policies.
    4. Utilize GitHub Project Cards to organize tasks and pull requests.

    The program below demonstrates how to perform these tasks using Pulumi with the pulumi_github provider. Each resource is briefly explained within the code comments.

    GitHub Repository and Project Setup

    First, we'll create a new GitHub repository to store your AI code. We'll also set up a project within this repository to better organize issues and pull requests. In addition, we demonstrate how to create a pull request, which will be used to review and merge code changes.

    Pulumi Python Program for AI Codebase Review and Management

    import pulumi import pulumi_github as github # Configure the GitHub provider # Make sure you have the GitHub token set in the environment variables or the Pulumi configuration # as this is needed to authenticate against your GitHub account. # You can set it up by running `pulumi config set github:token YOUR_GITHUB_TOKEN --secret` # Create a new GitHub repository to store your AI codebase repo = github.Repository("ai-codebase", # The name of the repository; change this to your preferred repository name name="ai-codebase", # The description of the repository description="Repository for AI codebase management", # Set repository visibility, can be 'private' or 'public' visibility="private", # Initialize the repository with an initial README auto_init=True, ) # Create a new GitHub Repository Project to organize development workflow repo_project = github.RepositoryProject("ai-codebase-project", # The name of the project; change this to your preferred project name name="AI Codebase Management", # The body/description of the project body="Project to manage AI codebase development and reviews", # Link the project to the created repository repository=repo.name, ) # Example of creating a pull request # To reflect real usage, replace baseRef and headRef with actual branch names relevant to your workflow. pull_request = github.RepositoryPullRequest("ai-codebase-pr", # The title of the pull request title="Feature: Add ML model training module", # The body/content of the pull request (description) body="This PR introduces the ML model training module for review.", # The base branch on which you want the changes to be pulled base_repository=repo.name, base_ref="main", # The head branch from which the changes are sourced head_ref="feature/add-ml-training", # The owner of the repository, replace this with your GitHub username or organization owner="your-github-username", # Whether maintainers can modify the pull request maintainer_can_modify=True, ) # Export the repository URL as an output pulumi.export("repository_url", repo.clone_url) # Export the repository project URL as an output pulumi.export("project_url", pulumi.Output.concat("https://github.com/", repo.name, "/projects/", repo_project.number)) # Export the pull request URL as an output pulumi.export("pull_request_url", pull_request.html_url)

    This code sets up the core GitHub infrastructure needed for managing an AI codebase.

    What is happening in the program?

    1. A github.Repository resource is being created, named ai-codebase, which serves as the location for your code.
    2. A github.RepositoryProject named ai-codebase-project is also created within the repository. This is used to organize and manage the workflow related to your codebase.
    3. A github.RepositoryPullRequest resource creates a new pull request against the main branch with the title "Feature: Add ML model training module". This would typically be used to merge a feature branch into the main branch.


    • repository_url: The Git URL to clone the repository.
    • project_url: The URL to access the repository's project for organizing the development workflow.
    • pull_request_url: The URL to access and review the created pull request.

    In order to run this code, you need to ensure you have Pulumi installed and configured with your GitHub token to interact with your GitHub account. Make sure to replace placeholders like your-github-username with your actual GitHub username or organization and update branch names according to your workflow.

    Once you run the Pulumi program, it will set up the resources as defined and output the URLs to access the repo, project, and pull request. This way, you're prepared with a structured approach to manage AI codebase reviews using GitHub and Pulumi.