add gcp to permissions link

Author: commit111

docs/concepts/managed-llms/managed-language-models.md

@@ -13,7 +13,7 @@ Each cloud provider offers their own managed Large Language Model services. AWS
 In order to leverage cloud-native managed language models from your Defang services, all you need to do is add the `x-defang-llm` extension to the service config and Defang will configure the approprate roles and permissions for you.
 
 :::tip
-Ensure you have the necessary permissions to access the model you intend to use. For example, if you are using AWS Bedrock, verify that your account has [model access](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html).
+Ensure you have the necessary permissions to access the model you intend to use. To do this, you can check your [AWS Bedrock model access](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html) or [GCP Vertex AI model permissions](https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-partner-models?hl=en#grant-permissions).
 :::
 
 ## Example

docs/tutorials/deploying-openai-apps-aws-bedrock-gcp-vertex.mdx

@@ -106,8 +106,8 @@ You should configure your application to specify the model you want to use.
 
 Choose the correct `MODEL` depending on which cloud provider you are using.
 
-Ensure you have the necessary permissions to access the model you intend to use.
-For example, if you are using AWS Bedrock, verify that your account has [model access](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html).
+Ensure you have the necessary permissions to access the model you intend to use. 
+To do this, you can check your [AWS Bedrock model access](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html) or [GCP Vertex AI model permissions](https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-partner-models?hl=en#grant-permissions).
 
 :::info
 **Choosing the Right Model**