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What is AI-Gateway?

AI-Gateway is a project that explores the integration of Azure API Management with AI capabilities, including Azure OpenAI and AI Foundry, through a series of experimental labs.

How to use AI-Gateway?

To use AI-Gateway, clone the repository, set up the required prerequisites, and navigate through the available labs to experiment with various AI functionalities.

Key features of AI-Gateway?

• Experiments with Model Context Protocol (MCP) for client authorization.
• Integration with Azure OpenAI models and APIs.
• Tools for managing AI budgets and costs through the FinOps Framework.
• Various labs for testing AI functionalities like content filtering, prompt shielding, and model routing.

Use cases of AI-Gateway?

1. Experimenting with AI models and APIs in a controlled environment.
2. Managing AI service costs effectively.
3. Implementing advanced AI functionalities in applications.

FAQ from AI-Gateway?

• What prerequisites are needed to use AI-Gateway?

You need Python 3.12 or later, VS Code with Jupyter extension, an Azure subscription, and Azure CLI installed.

• Is AI-Gateway suitable for production use?

AI-Gateway is primarily for experimentation and learning; production use should follow best practices from the Azure Well-Architected Framework.