diff --git a/modules/ingesting-content-into-a-llama-model.adoc b/modules/ingesting-content-into-a-llama-model.adoc
index 05c664df..5922ca15 100644
--- a/modules/ingesting-content-into-a-llama-model.adoc
+++ b/modules/ingesting-content-into-a-llama-model.adoc
@@ -10,6 +10,7 @@ You can quickly customize and prototype your retrievable content by ingesting ra
 * You have deployed a Llama 3.2 model with a vLLM model server and you have integrated LlamaStack.
 * You have created a project workbench within a data science project.
 * You have opened a Jupyter notebook and it is running in your workbench environment.
+* You have installed the `llama_stack_client` version 0.2.14 or later in your workbench environment. 
 * You have a created and configured a vector database instance and you know its identifier.
 ifdef::self-managed[]
 * Your environment has network access to the vector database service through {openshift-platform}.
diff --git a/modules/preparing-documents-with-docling-for-llama-stack-retrieval.adoc b/modules/preparing-documents-with-docling-for-llama-stack-retrieval.adoc
index f4c28ef0..7e2e161a 100644
--- a/modules/preparing-documents-with-docling-for-llama-stack-retrieval.adoc
+++ b/modules/preparing-documents-with-docling-for-llama-stack-retrieval.adoc
@@ -27,6 +27,7 @@ ifdef::upstream[]
 * You have installed local object storage buckets and created connections, as described in link:{odhdocshome}/working-on-data-science-projects/#adding-a-connection-to-your-data-science-project_projects[Adding a connection to your data science project].
 endif::[]
 ifndef::upstream[]
+* You have installed the `llama_stack_client` version 0.2.14 or later in your workbench environment. 
 * You have installed local object storage buckets and created connections, as described in link:{rhoaidocshome}{default-format-url}/working_on_data_science_projects/using-connections_projects#adding-a-connection-to-your-data-science-project_projects[Adding a connection to your data science project].
 endif::[]
 * You have compiled to YAML a data science pipeline that includes a Docling transform, either one of the RAG demo samples or your own custom pipeline.
diff --git a/modules/querying-ingested-content-in-a-llama-model.adoc b/modules/querying-ingested-content-in-a-llama-model.adoc
index 06df526e..bc7781b1 100644
--- a/modules/querying-ingested-content-in-a-llama-model.adoc
+++ b/modules/querying-ingested-content-in-a-llama-model.adoc
@@ -20,6 +20,7 @@ endif::[]
 * You have configured a Llama Stack deployment by creating a `LlamaStackDistribution` instance to enable RAG functionality.
 * You have created a project workbench within a data science project.
 * You have opened a Jupyter notebook and it is running in your workbench environment.
+* You have installed the `llama_stack_client` version 0.2.14 or later in your workbench environment. 
 * You have ingested content into your model. 
 
 [NOTE]