Connecting Modal with Git Repositories
Last updated August 26, 2024
Seamlessly integrate your machine learning projects with popular Git repositories like GitHub and GitLab to streamline your code management, collaboration, and deployment workflows. Modal's integration with Git provides a powerful and efficient way to manage your machine learning code.
Benefits of Git Integration
- Version Control: Track changes to your code, experiment with different approaches, and easily revert to previous versions as needed.
- Collaboration: Share code with teammates, collaborate on projects, and leverage the power of Git's branching and merging features.
- Deployment Automation: Integrate your Git repository with Modal's deployment pipelines to automatically build, test, and deploy your models after code changes.
- Reproducibility: Ensure that you can reproduce your experiments and deployments by capturing the exact code used for each run.
Connecting Your Git Repository
1. **Create a Modal Project:** Create a new Modal project to house your machine learning code.
2. **Connect to a Git Repository:** Within your Modal project, select the option to connect to a Git repository.
3. **Choose Your Repository Provider:** Select your preferred Git provider (e.g., GitHub, GitLab).
4. **Authorize Modal:** Provide the necessary authorization for Modal to access your repository.
5. **Select a Branch:** Specify the branch within your repository that Modal should use for code management.
Managing Your Code with Git
- Code Editing: Access a built-in code editor within Modal to modify your project's code directly.
- Commit Changes: Commit your code changes directly from Modal, ensuring that you keep track of modifications and maintain a complete history.
- Push Changes: Push your commits back to your Git repository to share them with others or integrate them into your deployment pipeline.
- Pull Changes: Pull the latest changes from your Git repository to ensure your Modal project is up to date.
Automating Deployment with Git
- Deployment Triggers: Configure deployment triggers in your Modal project to automatically build and deploy your model whenever new code is pushed to your Git repository.
- CI/CD Pipelines: Define continuous integration and continuous delivery (CI/CD) pipelines using Modal's tools to automate the deployment process.
- Automated Testing: Include automated tests within your Git repository to ensure code quality and prevent errors during deployment.
By integrating your Git repository with Modal, you streamline your machine learning workflows, simplify collaboration, and automate deployment processes, allowing you to focus on building and refining your models.