Merge pull request #2206 from recommenders-team/staging

Staging to main: Fix issue with Cornac version

Author: miguelgfierro

SETUP.md

@@ -247,7 +247,7 @@ First make sure that the tag that you want to add, e.g. `0.6.0`, is added in [`r
 1. Make sure that the code in main passes all the tests (unit and nightly tests).
 1. Create a tag with the version number: e.g. `git tag -a 0.6.0 -m "Recommenders 0.6.0"`.
 1. Push the tag to the remote server: `git push origin 0.6.0`.
-1. When the new tag is pushed, a release pipeline is executed. This pipeline runs all the tests again (PR gate and nightly builds), generates a wheel and a tar.gz which are uploaded to a [GitHub draft release](https://github.com/microsoft/recommenders/releases).
+1. When the new tag is pushed, a release pipeline is executed. This pipeline runs all the tests again (PR gate and nightly builds), generates a wheel and a tar.gz which are uploaded to a [GitHub draft release](https://github.com/microsoft/recommenders/releases). *NOTE: Make sure you add the release tag to the [federeted credendials](tests/README.md).*
 1. Fill up the draft release with all the recent changes in the code.
 1. Download the wheel and tar.gz locally, these files shouldn't have any bug, since they passed all the tests.
 1. Install twine: `pip install twine`

setup.py

@@ -28,7 +28,8 @@
 
 install_requires = [
     "category-encoders>=2.6.0,<3",  # requires packaging
-    "cornac>=1.15.2,<3",  # requires packaging, tqdm
+    "cornac>=1.15.2,<=2.2.2;python_version<='3.8'",
+    "cornac>=2.3.0,<3;python_version>='3.9'",  # requires packaging, tqdm
     "hyperopt>=0.2.7,<1",
     "lightgbm>=4.0.0,<5",
     "locust>=2.12.2,<3",  # requires jinja2

tests/README.md

@@ -250,8 +250,7 @@ Then, follow the steps below to create the AzureML infrastructure:
       * AzureML Compute Operator
       * AzureML Data Scientist
       * Reader
-   1. [Create a federated identiy credential on the
-      UMI](https://learn.microsoft.com/en-us/entra/workload-id/workload-identity-federation-create-trust-user-assigned-managed-identity?pivots=identity-wif-mi-methods-azp#github-actions-deploying-azure-resources)
+   1. [Create a federated identity credential on the UMI](https://learn.microsoft.com/en-us/entra/workload-id/workload-identity-federation-create-trust-user-assigned-managed-identity?pivots=identity-wif-mi-methods-azp#github-actions-deploying-azure-resources)
       with the following settings:
       * Name: A unique name for the federated identity credential
         within your application.
@@ -262,6 +261,7 @@ Then, follow the steps below to create the AzureML infrastructure:
         + `repo:recommenders-team/recommenders:pull_request`
         + `repo:recommenders-team/recommenders:ref:refs/heads/staging`
         + `repo:recommenders-team/recommenders:ref:refs/heads/main`
+        + `repo:recommenders-team/recommenders:ref:refs/tags/1.2.1`
       * Description: (Optional) A description of the credential.
       * Audiences: Specifies who can use this credential; for GitHub
         Actions, use `api://AzureADTokenExchange`.