feat: implement Azure OpenAI deployment routing to map logical model

[Danni2901]

Azure OpenAI Deployment-Based Router

In Azure OpenAI Service, each model is deployed as a separate "Deployment" with its own unique name (e.g., my-gpt-4o-deployment). This structure differs from standard OpenAI, where model names are universal.

The Deployment-Based Router allows you to map logical, unified model names to specific Azure deployment names dynamically. This is essential for large-scale projects where you want to switch models without changing code or hardcoded deployment names.

[taylorotwell]

Can you link me to how other AI SDKs implement this?

[Danni2901]

Can you link me to how other AI SDKs implement this?

Hi @taylorotwell, here is how major AI SDKs handle the mapping between standard model names and Azure's custom deployment names:

1. Microsoft Semantic Kernel (.NET/Python)
   Explicitly separates the logical modelId (e.g., "gpt-4") and deploymentName during configuration.
   👉 Semantic Kernel Azure Docs

2. LangChain
   Provides a dedicated azure_deployment parameter in the AzureChatOpenAI class to map the deployment.
   👉 LangChain Azure Docs

This PR follows a similar approach, ensuring Laravel AI can cleanly separate logical model names from Azure deployment identifiers.