Hosting Pre-trained AI Model Repositories on GitHub

Question

Pulumi · Accepted Answer

To host pre-trained AI model repositories on GitHub using Pulumi, you would typically need to set up a GitHub repository, configure it with any specific settings like topics, issue tracking, and branch policies, and possibly add collaborators or teams.

Firstly, the github.Repository resource is used to create a new repository. You can configure various aspects of the repository such as its name, description, visibility (public or private), and whether it has features like a wiki, issues, or downloads.

Here's how you would use Pulumi to create a GitHub repository for hosting your AI models:

Repository Creation: You start by creating a new GitHub repository with the desired features.
File Upload: Though Pulumi doesn't directly interact with the files within a GitHub repository, you can automate the process of pushing files to it using Git commands after your Pulumi program has created the repository.
Collaboration: If needed, you can add collaborators or teams to the repository using resources like github.RepositoryCollaborator and github.Team.

Below, you will find a Pulumi program in Python that demonstrates how to create a GitHub repository ready to host pre-trained AI models. This program assumes you have GitHub credentials configured for Pulumi.

import pulumi
import pulumi_github as github

# Create a new GitHub Repository.
ai_model_repo = github.Repository("ai-model-repo",
    name="pre-trained-ai-models",
    description="Repository containing pre-trained AI models.",
    visibility="public",  # or "private" for a private repository
    has_issues=True,
    has_projects=False,
    has_wiki=False,
    topics=["ai", "machine-learning", "pre-trained-models"],
    license_template="mit",  # Choose an appropriate license.
)

# Export the URL of the repository so that it can be easily accessed.
pulumi.export("repository_url", ai_model_repo.html_url)

# After running `pulumi up`, you will need to manually push your AI model files to the repository.
# Use Git to clone the repository, add your files, and push them to GitHub.
# Example Git commands:
# git clone <repository_url>
# cd <repository_name>
# git add .
# git commit -m "Add pre-trained AI models"
# git push origin main

# To add a collaborator to the repository with push access.
collaborator = github.RepositoryCollaborator("collaborator",
    repository=ai_model_repo.name,
    username="<collaborator_github_username>",  # Replace with the collaborator's GitHub username.
    permission="push"
)

# To create a GitHub team and add it to the repository.
team = github.Team("ai-models-team",
    name="AI Models Team",
    description="Team responsible for maintaining the AI models repository."
)

# Add the repository to the team with push access.
team_access = github.TeamRepository("team_repo_access",
    repository=ai_model_repo.name,
    team_id=team.id,
    permission="push"
)

This program creates a public GitHub repository with the provided name and description. Additionally, it sets the repository's visibility to public, enables issue tracking, disables projects and wiki features, adds topics for discoverability, and specifies an MIT license.

You can then push your AI model files to the created repository using Git commands as shown in the commented section. This step is done outside of Pulumi's purview.

Furthermore, the program showcases how to add a collaborator and create a team that is associated with the repository, granting them push access. Replace <collaborator_github_username> with the actual GitHub username of the person you wish to add as a collaborator.

After the execution of this program using pulumi up, you will see the repository_url exported in the output, which you can use to access your newly created GitHub repository.

Remember to handle sensitive information, such as GitHub tokens or passwords, securely. You may store such credentials in a configuration file or use environment variables to avoid hardcoding them into your Pulumi program.