fix typo

Author: cloga

articles/machine-learning/prompt-flow/how-to-secure-prompt-flow.md

@@ -87,7 +87,7 @@ Workspace managed virtual network is the recommended way to support network isol
 - If you have strict outbound rule, make sure you have open the [Required public internet access](../how-to-secure-workspace-vnet.md#required-public-internet-access).
 - Add workspace MSI as `Storage File Data Privileged Contributor` to storage account linked with workspace. Please follow step 2 in [Secure prompt flow with workspace managed virtual network](#secure-prompt-flow-with-workspace-managed-virtual-network).
 - Meanwhile, you can follow [private Azure Cognitive Services](../../ai-services/cognitive-services-virtual-networks.md) to make them as private.
-- If you want to deploy prompt flow in workspace which secured by your own virtual network, you can deploy it to AKS cluster which is in the same virtual network. You can follow [Secure Azure Kubernetes Service inferencing environment](../how-to-secure-kubernetes-inferencing-environment.md) to secure your AKS cluster. Learn more about [How to deploy prompt flow to ASK cluster via code](./how-to-deploy-to-code) to secure your RAG workflows.
+- If you want to deploy prompt flow in workspace which secured by your own virtual network, you can deploy it to AKS cluster which is in the same virtual network. You can follow [Secure Azure Kubernetes Service inferencing environment](../how-to-secure-kubernetes-inferencing-environment.md) to secure your AKS cluster. Learn more about [How to deploy prompt flow to ASK cluster via code](./how-to-deploy-to-code.md) to secure your RAG workflows.
 - You can either create private endpoint to the same virtual network or leverage virtual network peering to make them communicate with each other.
 
 ## Known limitations

articles/machine-learning/prompt-flow/tools-reference/vector-index-lookup-tool.md

@@ -89,4 +89,4 @@ The following example is for a JSON format response returned by the tool, which
 
 ## Deploying to an online endpoint
 
-When you deploy a flow containing the vector index loopup tool to an online endpoint, there's an extra step to set up permissions. During deployment through the web pages, there's a choice between System-assigned and User-assigned Identity types. Either way, using the Azure portal (or a similar functionality), add the "AzureML Data Scientist" role of Azure Machine learning studio to the identity assign to the endpoint.
+When you deploy a flow containing the vector index lookup tool to an online endpoint, there's an extra step to set up permissions. During deployment through the web pages, there's a choice between System-assigned and User-assigned Identity types. Either way, using the Azure portal (or a similar functionality), add the "AzureML Data Scientist" role of Azure Machine learning studio to the identity assign to the endpoint.