Prefect

This release includes:

🪲 Fixes
- Refined flow parameter validation to use the correct validation depending on if the parameter is a pydantic v1 or v2 model.

📚 Documentation Improvements
- Added Python `serve` and `deploy` options to the `schedules` concepts documentation

See the [release notes](https://github.com/PrefectHQ/prefect/blob/main/RELEASE-NOTES.md#release-2141) for details!

This release includes:

🌐 **prefect-client**

This slimmed down version of `prefect` has a small surface area of functionality and is intended for interacting with the Prefect server or Prefect Cloud only. It is ideal for use in lightweight, ephemeral execution environments when the goal is to interact with Prefect API resources. It is now installable via `pip`:

bash
pip install prefect-client


🏷 **Flow Labels for Subflow Runs**
We've improved the Prefect UI by adding flow names to subflow runs.

🪲 **Windows Environment Compatibility**
We've fixed issues related to pulling flows and building deployments in Windows environments.

🚮 **UI Cleanup**
We've removed an unnecessary work queue health indicator from push pools.

📚 **Documentation Improvements**
- Added consistent capitalization
- Updated the Docker guide to mention image builds with prefect.yaml and flow.deploy
- Updated Kubernetes guide with Python-based flow deploy creation methods

For a complete overview of all the changes in this release, visit the [compare page](https://github.com/PrefectHQ/prefect/compare/2.13.8...2.14.0).

This release includes:

🚀 **flow.deploy**
We're excited to introduce `flow.deploy` as a simple transition from running your served flows on persistent infrastructure to executing your flows on dynamically provisioned infrastructure via work pools and workers. `flow.deploy` ensures your flows execute consistently across environments by packaging your flow into a Docker image and making that image available to your workers when executing your flow.

See the [release notes](https://github.com/PrefectHQ/prefect/blob/main/RELEASE-NOTES.md#release-2138) for details!

This release includes:

⚙️ 🥳 Pydantic V2 Support

In 10946 we add support for Pydantic V2. In 2.13.5 we released experimental support for Pydantic V2, which made it technically co-installable via forced install. In this release we're enabling proper co-installation.

This release includes:

📦 **Default result storage block**
The new `PREFECT_DEFAULT_RESULT_STORAGE_BLOCK` setting allows users to set a default storage block on a work pool or via job variables for a deployment. It's now easier to swap result storage locations by updating the environment in the UI or your `prefect.yaml` file, eliminating the need to alter your flow source code.

🧪 **Experimental enhanced cancellation**
We're enhancing the reliability of flow run cancellation, which you can try out by enabling the `PREFECT_EXPERIMENTAL_ENABLE_ENHANCED_CANCELLATION` feature. When enabled, you can cancel flow runs where cancellation can fail, such as when your worker is offline.

See the [release notes](https://github.com/PrefectHQ/prefect/blob/main/RELEASE-NOTES.md#release-2136) for details!

This release introduces a few new features:

⚡ You can now load and serve flows from a git repository! With the new `flow.from_source` method, you can specify a git repository and a path to a flow file in that repository. This method will return a flow object that can be run or served with `flow.serve()`.

🧪 Experimental Pydantic 2 compatibility! We're working eagerly toward having prefect installable with either `pydantic<2` or `pydantic>2`. As a first step toward compatibility, we've ensured that Prefect's use of pydantic is isolated from your use of pydantic in as many ways as possible.

See the [release notes](https://github.com/PrefectHQ/prefect/blob/main/RELEASE-NOTES.md#release-2135) for details!