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.. <DESCRIBE THE FULL PROCEDURES FOR THE INSTALLATION OF THE O-RAN COMPONENT INSTALLATION AND DEPLOYMENT>
+For stable l-release user can run following commands
+
.. code:: bash
- git clone [-b <branch-name>] "https://gerrit.o-ran-sc.org/r/aiml-fw/aimlfw-dep" # latest release branch is l-release
+ git clone -b l-release "https://gerrit.o-ran-sc.org/r/aiml-fw/aimlfw-dep" # latest release branch is l-release
cd aimlfw-dep
+Any failure in l-release are tracked here 'https://lf-o-ran-sc.atlassian.net/browse/AIMLFW-286'
Update recipe file :file:`RECIPE_EXAMPLE/example_recipe_latest_stable.yaml` which includes update of VM IP and datalake details.
Ensure image version is correct.
+.. code:: bash
+ bin/install_traininghost.sh RECIPE_EXAMPLE/example_recipe_latest_stable.yaml
+
**Note**: In case the Influx DB datalake is not available, this can be skipped at this stage and can be updated after installing datalake.
-
+In case user prefers to check latest updates they can clone master branch (master branch can be unstable)
.. code:: bash
- bin/install_traininghost.sh <RECIPE_FILE>
+ git clone "https://gerrit.o-ran-sc.org/r/aiml-fw/aimlfw-dep" # master branch
+ cd aimlfw-dep
+
+Update recipe file :file:`RECIPE_EXAMPLE/example_recipe_nexus_images_staging.yaml` which includes update of VM IP and datalake details.
+
+.. code:: bash
+ bin/install_traininghost.sh RECIPE_EXAMPLE/example_recipe_nexus_images_staging.yaml
-**Note**: In case no RECIPE_FILE is passed <RECIPE_EXAMPLE> RECIPE_EXAMPLE/example_recipe_latest_stable.yaml will be considered as default
+**Note**: For l-release use default RECIPE_FILE , that is RECIPE_EXAMPLE/example_recipe_latest_stable.yaml.In case you want to use master branch(not stable) for checking new updates use RECIPE_EXAMPLE/example_recipe_nexus_images_staging.yaml as RECIPE_FILE.
Check running state of all pods and services using below command :
.. code:: bash
./bin/uninstall_kserve.sh
-For Advanced usecases, Please refer to official kserve-documentation `here <https://kserve.github.io/website/docs/getting-started/predictive-first-isvc#1-create-a-namespace>`__
+For Advanced usecases, Please refer to official kserve-documentation `here <https://kserve.github.io/archive/0.11/get_started/first_isvc/#1-create-a-namespace>`__
2. Install both Kserve and Kserve adapter for deploying models (Optional/Not validated in k-release)
kubectl get InferenceService -n ricips
+