AI Codebase Review and Management with GitHub Pull Requests

Question

Pulumi · Accepted Answer

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

```python
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.

### Outputs

- `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.