Azure AI Foundry Workshop

🤖Overview | 🚀Quick Start | 📦Prerequisites | ⚙️Local Setup | 📔Workshop Content | 🧩Project Structure | ❓Support | 🤝Contributing

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🤖 Overview

A hands-on workshop that guides you through building intelligent AI agents using Azure AI Foundry's SDK, with examples ranging from customer service to health and dietary advice. You will:

• Learn Azure AI Foundry fundamentals
• Set up authentication and project configuration
• Deploy and test AI models
• Build AI agents (customer service and health advisor examples)
• Implement health calculations and dietary planning
• Evaluate agent performance with safety checks

Duration: 2-4 hours
Focus: Hands-on exercises, interactive notebooks, practical examples

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🚀 Quick Start

1. Clone the repo:

   git clone https://github.com/Azure/azure-ai-foundry-workshop.git
   cd azure-ai-foundry-workshop

2. Create & activate a virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # Windows: .venv\Scripts\activate

3. Configure environment:

   cp .env.local .env

   Update .env with your Azure AI Foundry values:

   • PROJECT_CONNECTION_STRING: Your project connection string from Azure ML workspace
   • MODEL_DEPLOYMENT_NAME: Your model deployment name
   • EMBEDDING_MODEL_DEPLOYMENT_NAME: Your embedding model deployment name
   • TENANT_ID: Your tenant ID from Azure portal
   • BING_CONNECTION_NAME: Your Bing search connection name
   • SERVERLESS_MODEL_NAME: Your serverless model name

   Note: The model specified in MODEL_DEPLOYMENT_NAME must be supported by Azure AI Agents Service or Assistants API. See supported models for details.

4. Install dependencies:

   # Install core Azure AI SDKs
   pip install azure-identity azure-ai-projects azure-ai-inference azure-ai-evaluation azure-ai-contentsafety azure-monitor-opentelemetry
   
   # Install additional requirements
   pip install -r requirements.txt

5. Start Jupyter:

   jupyter notebook

6. Follow the Learning Path:

   1. Introduction (docs/1-introduction/)

      • 1-authentication.ipynb: Set up your Azure credentials
      • 2-environment_setup.ipynb: Configure your environment
      • 3-quick_start.ipynb: Learn basic operations

   2. Main Workshop (docs/2-notebooks/)

      • Chat Completion & RAG (1-chat_completion/)
      • Agent Development (2-agent_service/)
      • Quality Attributes (3-quality_attributes/)

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📦 Prerequisites

• Python 3.10+
• Azure subscription with access to Azure AI Foundry
• Deployment of a model and AI Search connection configured in Azure AI Foundry
• Basic Python knowledge
• Azure CLI
• Git

Setting Up Azure CLI

# Install Azure CLI (Ubuntu)
curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash

# Login and set subscription
az login
az account set --subscription <YOUR_SUBSCRIPTION_ID>

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⚙️ Local Setup

1. Verify Python Version:

   python --version  # Should be 3.10 or higher

2. Create & activate virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # Windows: .venv\Scripts\activate

3. Install dependencies:

   pip install -r requirements.txt

4. Configure environment:

   • Copy .env.example to .env
   • Update with your Azure credentials

5. Start Jupyter:

   jupyter notebook

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📔 Workshop Content

1. Introduction (docs/1-introduction/)

• Azure authentication and setup
• Environment configuration
• Quick start with AI Foundry
• Core concepts and SDKs

2. Chat Completion & RAG (docs/2-notebooks/1-chat_completion/)

• Basic chat completion
• Embeddings and vector search
• RAG for health knowledge
• Advanced models (Phi-4)

3. Agent Development (docs/2-notebooks/2-agent_service/)

• Health Advisor Agent basics
• Code interpreter for health metrics
• File search capabilities
• Bing grounding for medical info
• AI Search integration
• Azure Functions deployment

4. Quality Attributes (docs/2-notebooks/3-quality_attributes/)

• Observability setup
• Performance monitoring
• Agent evaluation
• Health advice safety checks

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🧩 Project Structure

azure-ai-foundry-workshop/
├── docs/
│   ├── 1-introduction/
│   │   ├── 1-authentication.ipynb
│   │   ├── 2-environment_setup.ipynb
│   │   └── 3-quick_start.ipynb
│   ├── 2-notebooks/
│   │   ├── 1-chat_completion/
│   │   │   ├── 1-basic-chat-completion.ipynb
│   │   │   ├── 2-embeddings.ipynb
│   │   │   ├── 3-basic-rag.ipynb
│   │   │   └── 4-phi-4.ipynb
│   │   ├── 2-agent_service/
│   │   │   ├── 1-basics.ipynb
│   │   │   ├── 2-code_interpreter.ipynb
│   │   │   ├── 3-file-search.ipynb
│   │   │   ├── 4-bing_grounding.ipynb
│   │   │   ├── 5-agents-aisearch.ipynb
│   │   │   └── 6-agents-az-functions.ipynb
│   │   └── 3-quality_attributes/
│   │       ├── 1-Observability.ipynb
│   │       └── 2-evaluation.ipynb
│   ├── agents/
│   ├── evaluation/
│   ├── models/
│   └── sdk/
├── .env
├── .env.local
└── requirements.txt

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❓ Support

If you encounter issues:

1. Check Prerequisites:

   • Verify Python version
   • Confirm Azure CLI installation
   • Check environment variables

2. Common Solutions:

   • Restart Jupyter kernel
   • Reactivate virtual environment
   • Clear notebook output and restart

3. Get Help:

   • Check Azure AI Foundry docs
   • Search open issues
   • Submit a new issue

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🤝 Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Submit a Pull Request

Development Guidelines

• Follow PEP 8 style guide
• Add tests for new features
• Update documentation
• Keep examples simple and clear

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Code of Conduct

This project follows the Microsoft Open Source Code of Conduct.

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License

MIT License
Copyright (c) Microsoft

See LICENSE.txt for details.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos must follow Microsoft's Trademark & Brand Guidelines.