add links + comma

Author: commit111

docs/concepts/managed-llms/openai-access-gateway.md

@@ -37,7 +37,7 @@ The `x-defang-llm` extension is used to configure the appropriate roles and perm
 
 ## Model Mapping
 
-Defang supports model mapping through the [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway) on AWS and GCP. This takes a model with a Docker naming convention (e.g. `ai/llama3.3`) and maps it to the closest matching model name on the target platform. If no such match can be found it can fallback onto a known existing model (e.g. `ai/mistral`).
+Defang supports model mapping through the [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway) on AWS and GCP. This takes a model with a Docker naming convention (e.g. `ai/llama3.3`) and maps it to the closest matching model name on the target platform. If no such match can be found, it can fallback onto a known existing model (e.g. `ai/mistral`).
 
 This can be configured through the following environment variables:
 * `USE_MODEL_MAPPING` (default to true) - configures whether or not model mapping should be enabled.

docs/tutorials/deploy-openai-apps/aws-bedrock.mdx

@@ -114,7 +114,7 @@ Choose the correct `MODEL` depending on which cloud provider you are using.
 - For **AWS Bedrock**, use a Bedrock model ID (e.g., `anthropic.claude-3-sonnet-20240229-v1:0`). [See available Bedrock models](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html).
 :::
 
-Alternatively, Defang supports model mapping through the [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway). This takes a model with a Docker naming convention (e.g. `ai/llama3.3`) and maps it to
+Alternatively, Defang supports [model mapping](/docs/concepts/managed-llms/openai-access-gateway/#model-mapping) through the [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway). This takes a model with a Docker naming convention (e.g. `ai/llama3.3`) and maps it to
 the closest equivalent on the target platform. If no such match can be found, a fallback can be defined to use a known existing model (e.g. `ai/mistral`). These environment
 variables are `USE_MODEL_MAPPING` (default to true) and `FALLBACK_MODEL` (no default), respectively.
 

docs/tutorials/deploy-openai-apps/gcp-vertex.mdx

@@ -119,7 +119,7 @@ To do this, you can check your [AWS Bedrock model access](https://docs.aws.amazo
 - For **GCP Vertex AI**, use a full model path (e.g., `google/gemini-2.5-pro-preview-03-25`). [See available Vertex AI models](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/call-vertex-using-openai-library#client-setup).
 :::
 
-Alternatively, Defang supports model mapping through the [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway). This takes a model with a Docker naming convention (e.g. `ai/llama3.3`) and maps it to
+Alternatively, Defang supports [model mapping](/docs/concepts/managed-llms/openai-access-gateway/#model-mapping) through the [openai-access-gateway](https://github.com/DefangLabs/openai-access-gateway). This takes a model with a Docker naming convention (e.g. `ai/llama3.3`) and maps it to
 the closest matching one on the target platform. If no such match can be found, it can fallback onto a known existing model (e.g. `ai/mistral`). These environment
 variables are `USE_MODEL_MAPPING` (default to true) and `FALLBACK_MODEL` (no default), respectively.