Using GitHub Copilot CLI with Azure AI Foundry (BYOK Models) – Part 2
This article explains how to use GitHub Copilot CLI with Azure AI Foundry, allowing you to connect Copilot CLI to a cloud-hosted model you control. It covers setting up Azure AI Foundry, deploying a model, and building the final endpoint to use with Copilot CLI.
Why it matters
This article provides a valuable guide for developers who want to leverage the power of large language models with GitHub Copilot CLI while maintaining control over the underlying infrastructure.
Key Points
- 1Connect Copilot CLI to a cloud-hosted model on Azure AI Foundry
- 2Deploy a model (e.g., GPT-4 class) in Azure and get the deployment name
- 3Retrieve the Azure endpoint URL and API key to build the final endpoint
- 4Validate the deployment, API key, and endpoint before using Copilot CLI
Details
The article explains how to use Azure AI Foundry to run larger and more powerful models with GitHub Copilot CLI, compared to the local setup covered in Part 1. By connecting Copilot CLI to a cloud-hosted model on Azure, users gain access to better models and stronger reasoning capabilities, while still maintaining control over the endpoint and deployment. However, this approach comes with the trade-off of cost and network dependency. The article provides step-by-step instructions on setting up Azure AI Foundry, deploying a model, and constructing the final endpoint that Copilot CLI will use. It emphasizes the importance of validating the deployment, API key, and endpoint before using Copilot CLI to avoid debugging issues later.
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