Prepare release 0.55.2 (#2401)

* Prepare release 0.55.2

* Auto-update of Starter template

---------

Co-authored-by: GitHub Actions <[email protected]>

Author: bcdurak

README.md

@@ -91,7 +91,7 @@
     <a href="https://www.zenml.io/company#team">Meet the Team</a>
     <br />
     <br />
-    🎉 Version 0.55.1 is out. Check out the release notes
+    🎉 Version 0.55.2 is out. Check out the release notes
     <a href="https://github.com/zenml-io/zenml/releases">here</a>.
     <br />
     <br />

RELEASE_NOTES.md

@@ -1,5 +1,42 @@
 <!-- markdown-link-check-disable -->
 
+# 0.55.2
+
+This patch comes with a variety of new features, bug-fixes, and documentation updates.
+
+Some of the most important changes include: 
+
+- The ability to add tags to outputs through the step context
+- Allowing the secret stores to utilize the implicit authentication method of AWS/GCP/Azure Service Connectors
+- [Lazy loading client methods](https://docs.zenml.io/v/docs/user-guide/advanced-guide/data-management/late-materialization) in a pipeline context
+- Updates on the Vertex orchestrator to switch to the native VertexAI scheduler
+- The new [HyperAI](https://hyperai.ai) integration featuring a new orchestrator and service connector
+- Bumping the mlflow version to 2.10.0
+
+We'd like to give a special thanks to @christianversloot and @francoisserra for their contributions. 
+
+## What's Changed
+* `0.55.1` in migration testing by @avishniakov in https://github.com/zenml-io/zenml/pull/2368
+* Credential-less AWS/GCP/Azure Secrets Store support by @stefannica in https://github.com/zenml-io/zenml/pull/2365
+* Small docs updates by @strickvl in https://github.com/zenml-io/zenml/pull/2359
+* generic `Client()` getters lazy loading by @avishniakov in https://github.com/zenml-io/zenml/pull/2323
+* Added slack settings OSSK-382 by @htahir1 in https://github.com/zenml-io/zenml/pull/2378
+* Label triggered slow ci by @avishniakov in https://github.com/zenml-io/zenml/pull/2379
+* Remove unused `is-slow-ci` input from fast and slow integration testing by @strickvl in https://github.com/zenml-io/zenml/pull/2382
+* Add deprecation warning for `ExternalArtifact` non-value features by @avishniakov in https://github.com/zenml-io/zenml/pull/2375
+* Add telemetry pipeline run ends by @htahir1 in https://github.com/zenml-io/zenml/pull/2377
+* Updating the `update_model` decorator  by @bcdurak in https://github.com/zenml-io/zenml/pull/2136
+* Mocked API docs building by @avishniakov in https://github.com/zenml-io/zenml/pull/2360
+* Add outputs tags function by @avishniakov in https://github.com/zenml-io/zenml/pull/2383
+* Bump mlflow to v2.10.0 by @christianversloot in https://github.com/zenml-io/zenml/pull/2374
+* Fix sharing of model versions by @schustmi in https://github.com/zenml-io/zenml/pull/2380
+* Fix GCP service connector login to overwrite existing valid credentials by @stefannica in https://github.com/zenml-io/zenml/pull/2392
+* Update `has_custom_name` for legacy artifacts by @avishniakov in https://github.com/zenml-io/zenml/pull/2384
+* Use native VertexAI scheduler capability instead of old GCP official workaround by @francoisserra in https://github.com/zenml-io/zenml/pull/2310
+* HyperAI integration: orchestrator and service connector by @christianversloot in https://github.com/zenml-io/zenml/pull/2372
+
+**Full Changelog**: https://github.com/zenml-io/zenml/compare/0.55.1...0.55.2
+
 # 0.55.1
 
 **If you are actively using the Model Control Plane features, we suggest that you directly upgrade to 0.55.1, bypassing 0.55.0.**

examples/quickstart/quickstart.ipynb

@@ -628,8 +628,8 @@
     "        dataset_trn, dataset_tst = feature_engineering()\n",
     "    else:\n",
     "        # Load the datasets from an older pipeline\n",
-    "        dataset_trn = client.get_artifact_version(id=train_dataset_id)\n",
-    "        dataset_tst = client.get_artifact_version(id=test_dataset_id) \n",
+    "        dataset_trn = client.get_artifact_version(name_id_or_prefix=train_dataset_id)\n",
+    "        dataset_tst = client.get_artifact_version(name_id_or_prefix=test_dataset_id) \n",
     "\n",
     "    trained_model = model_trainer(\n",
     "        dataset_trn=dataset_trn,\n",
@@ -970,8 +970,8 @@
     "@pipeline\n",
     "def inference(preprocess_pipeline_id: UUID):\n",
     "    \"\"\"Model batch inference pipeline\"\"\"\n",
-    "    # random_state = client.get_artifact_version(id=preprocess_pipeline_id).metadata[\"random_state\"].value\n",
-    "    # target = client.get_artifact_version(id=preprocess_pipeline_id).run_metadata['target'].value\n",
+    "    # random_state = client.get_artifact_version(name_id_or_prefix=preprocess_pipeline_id).metadata[\"random_state\"].value\n",
+    "    # target = client.get_artifact_version(name_id_or_prefix=preprocess_pipeline_id).run_metadata['target'].value\n",
     "    random_state = 42\n",
     "    target = \"target\"\n",
     "\n",
@@ -981,7 +981,7 @@
     "    df_inference = inference_preprocessor(\n",
     "        dataset_inf=df_inference,\n",
     "        # We use the preprocess pipeline from the feature engineering pipeline\n",
-    "        preprocess_pipeline=client.get_artifact_version(id=preprocess_pipeline_id),\n",
+    "        preprocess_pipeline=client.get_artifact_version(name_id_or_prefix=preprocess_pipeline_id),\n",
     "        target=target,\n",
     "    )\n",
     "    inference_predict(\n",

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "zenml"
-version = "0.55.1"
+version = "0.55.2"
 packages = [{ include = "zenml", from = "src" }]
 description = "ZenML: Write production-ready ML code."
 authors = ["ZenML GmbH <[email protected]>"]

src/zenml/VERSION

@@ -1 +1 @@
-0.55.1
+0.55.2

src/zenml/zen_server/deploy/helm/Chart.yaml

@@ -1,6 +1,6 @@
 apiVersion: v2
 name: zenml
-version: "0.55.1"
+version: "0.55.2"
 description: Open source MLOps framework for portable production ready ML pipelines
 keywords:
 - mlops

src/zenml/zen_server/deploy/helm/README.md

@@ -20,8 +20,8 @@ ZenML is an open-source MLOps framework designed to help you create robust, main
 To install the ZenML chart directly from Amazon ECR, use the following command:
 
 ```bash
-# example command for version 0.55.1
-helm install my-zenml oci://public.ecr.aws/zenml/zenml --version 0.55.1
+# example command for version 0.55.2
+helm install my-zenml oci://public.ecr.aws/zenml/zenml --version 0.55.2
 ```
 
 Note: Ensure you have OCI support enabled in your Helm client and that you are authenticated with Amazon ECR.

src/zenml/zen_stores/migrations/versions/0.55.2_release.py

@@ -0,0 +1,24 @@
+"""Release [0.55.2].
+
+Revision ID: 0.55.2
+Revises: 0.55.1
+Create Date: 2024-02-06 11:32:02.715174
+
+"""
+
+
+# revision identifiers, used by Alembic.
+revision = "0.55.2"
+down_revision = "0.55.1"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    """Upgrade database schema and/or data, creating a new revision."""
+    pass
+
+
+def downgrade() -> None:
+    """Downgrade database schema and/or data back to the previous revision."""
+    pass