build your first agent with azure ai agent service workshop

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Basic Information

This repository contains the content and sample code for a 75-minute workshop titled "Build your code-first agent with Azure AI Foundry." It is designed to let participants try the workshop hands-on and provides links to the full workshop guide and a lab-ready version for delivery such as Microsoft AI Tour. The workshop uses a sales-analytics scenario (Contoso) where a conversational agent answers questions about sales data. The repo includes sample application code that can be used as-is or replaced, documentation for modifying the workshop materials, and prerequisite guidance such as Azure subscription, GitHub account and Codespaces, and estimated resource consumption. The README also includes security notices about preview features and guidance to consult Microsoft documentation for securing intelligent applications. Contributors are asked to follow the repository's contribution process and CLA requirements.

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Features
Provides a complete workshop package with step-by-step content and sample code for building a code-first agent using Azure AI Foundry Agent Service. Includes a 75-minute workshop guide and links to detailed workshop documentation and a lab version for event delivery. Presents a realistic sales-analytics scenario (Contoso) to exercise conversational queries against sales data. Lists prerequisites and minimal cost guidance for running the lab, and points to a docs/README for customizing materials. Contains sample application code that can be reused or replaced, and highlights security and preview-feature warnings. Offers contribution guidance, CLA handling via a bot, and references Microsoft open source code of conduct and trademark guidance.
Use Cases
This repository helps developers and instructors learn to build and demonstrate a code-first conversational agent with Azure AI Foundry by providing ready-made workshop materials and runnable sample code. It gives a practical scenario and exercises to explore agent tools, shaping model behavior via instructions, and answering data-driven questions. The materials reduce setup time by listing needed Azure and GitHub resources, recommending GitHub Codespaces for an easy environment, and estimating low consumption costs for a typical run-through. It also surfaces important security cautions and points to Microsoft guidance for hardening intelligent applications. Instructors can adapt the docs for labs or tours and contributors can propose improvements via issues and pull requests.

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