# How to Update Marin to the Latest Version: A Step-by-Step Guide for the Monorepo > Update Marin to the latest version with this step-by-step guide. Learn how to pull new commits and refresh workspace dependencies using uv sync for your monorepo. - Repository: [The Marin Project/marin](https://github.com/marin-community/marin) - Tags: how-to-guide - Published: 2026-08-29 --- **To update Marin to the latest version, pull the newest commits from the repository root and run `uv sync` to refresh all inter-dependent workspace dependencies.** Marin is an open-source monorepo maintained by marin-community that houses multiple interconnected workspaces including marin-iris, marin-levanter, and marin-zephyr. When you need to update Marin to the latest version, you must synchronize both the source code and the Python environment defined in [`pyproject.toml`](https://github.com/marin-community/marin/blob/main/pyproject.toml) to maintain compatibility across all sub-packages. ## Prerequisites for Updating Marin Before executing the update, ensure your environment meets these requirements: - Git access to the `marin-community/marin` repository - The `uv` package manager installed (the preferred installer for this monorepo) - Current working directory set to the repository root ## The Standard Update Workflow Updating Marin follows a two-phase process: synchronizing the source code and refreshing the workspace environment. ### Pull the Latest Commits First, retrieve the newest code including experiment scripts, library updates, and bug fixes: ```bash git pull origin main ``` This command updates your local branch with changes from the remote main branch. ### Synchronize Dependencies with uv Run `uv sync` from the repository root to reinstall all packages declared in [`pyproject.toml`](https://github.com/marin-community/marin/blob/main/pyproject.toml) and the workspace members: ```bash uv sync ``` This ensures you receive the newest versions of *marin-iris*, *marin-levanter*, *marin-zephyr*, and other inter-dependent components simultaneously. ### Verify the Update Confirm the runtime reflects the latest code by inspecting the version attributes: ```bash python -c "import marin, levanter; print(marin.__version__, levanter.__version__)" ``` If the output shows recent version numbers, the synchronization succeeded. ## Alternative Update Methods Depending on your specific workflow, you might need these alternative approaches. ### Using pip for Editable Install If you prefer pip over uv, reinstall the repository in editable mode to guarantee imports resolve to freshly-checked-out sources: ```bash pip install -e . ``` This prevents Python from loading stale wheel installations cached in your environment. ### Updating a Single Workspace To update only one component rather than the entire monorepo (for example, just the *levanter* library): ```bash uv sync -p lib/levanter ``` This command rebuilds only the specified workspace while maintaining compatibility with the core system. ## Post-Update Validation After updating Marin to the latest version, validate the installation to catch regressions before starting new experiments. ### Run the Test Suite Execute the centralized test runner implemented in [`infra/ci/run_tests.py`](https://github.com/marin-community/marin/blob/main/infra/ci/run_tests.py): ```bash uv run --no-project infra/ci/run_tests.py ``` This validates the integrity of the entire workspace. If any tests fail, you can roll back with `git checkout ` or file an issue against the repository. ## Updating Containerized Deployments For users running Marin via Docker or Kubernetes, the update process differs slightly. Simply rebuild or re-pull the container image after pulling the latest code. The Dockerfile in marin-community/marin already installs the workspace in editable mode, so the standard image build process incorporates all updated source files automatically. ## Summary - Execute `git pull origin main` followed by `uv sync` to update Marin to the latest version efficiently - The [`pyproject.toml`](https://github.com/marin-community/marin/blob/main/pyproject.toml) file defines workspace members that `uv sync` manages automatically - Verify successful updates by checking package versions and running the test suite via [`infra/ci/run_tests.py`](https://github.com/marin-community/marin/blob/main/infra/ci/run_tests.py) - For targeted updates, use `uv sync -p ` to rebuild individual components - Containerized environments require image rebuilds rather than direct `uv sync` execution ## Frequently Asked Questions ### What is the fastest way to update Marin to the latest version? The fastest method is running `git pull origin main` immediately followed by `uv sync` from the repository root. According to the marin-community/marin source code, this combination updates both the source code and all inter-dependent workspace packages in seconds without manual dependency resolution. ### How do I update only one Marin workspace instead of the entire monorepo? Use the workspace-specific flag: `uv sync -p lib/levanter` (replace `levanter` with your target workspace). This rebuilds only that specific component while maintaining compatibility with the core marin system, saving time when you only need updates from a single library. ### Why does Marin use uv instead of pip for updates? The marin-community/marin repository uses uv because it handles the complex monorepo structure more efficiently than pip. As defined in [`pyproject.toml`](https://github.com/marin-community/marin/blob/main/pyproject.toml), uv synchronizes all workspace members automatically, ensuring that marin-iris, marin-levanter, and marin-zephyr remain version-compatible without manual intervention. ### How can I verify that Marin updated correctly? Run `python -c "import marin, levanter; print(marin.__version__)"` to check runtime versions, then execute `uv run --no-project infra/ci/run_tests.py` to validate functionality against the test suite. If both commands succeed without errors, your update to the latest version is complete and stable.