https://github.com/thegovind/ai-foundry-workshop
https://github.com/thegovind/ai-foundry-workshop
agent-service agents ai-foundry azure azure-ai azure-ai-foundry azure-openai openai
Last synced: 5 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/thegovind/ai-foundry-workshop
- Owner: Azure
- License: mit
- Created: 2025-01-08T01:47:59.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-04-30T05:10:20.000Z (5 months ago)
- Last Synced: 2025-05-08T03:13:53.942Z (5 months ago)
- Topics: agent-service, agents, ai-foundry, azure, azure-ai, azure-ai-foundry, azure-openai, openai
- Language: Jupyter Notebook
- Homepage: https://aifoundry.app
- Size: 6.98 MB
- Stars: 49
- Watchers: 13
- Forks: 63
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
Awesome Lists containing this project
README
# Azure AI Foundry Workshop
[📦Prerequisites](#-prerequisites) | [🚀Quick Start](#-quick-start) | [🤖Overview](#-overview) | [📔Workshop Content](#-workshop-content) | [🧩Project Structure](#-project-structure) | [❓Support](#-support) | [🤝Contributing](#-contributing)
## 🤖 Overview
A hands-on workshop that guides you through building intelligent apps and AI agents on top of Azure AI Foundry, with fun examples related 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 (health advisor examples)
- Implement health calculations and dietary planning
- Evaluate agent performance and monitor quality attributes
- Deploy an end-to-end AI native sample app that incorporates all these capabilities and design patterns
> **Duration**: 4-5 hours
> **Focus**: Hands-on exercises, interactive notebooks, practical examples, end-to-end project
## 🎥 Workshop Overview Video
Watch our overview video to get a comprehensive understanding of the workshop:
[](https://youtu.be/0bGLgmZJ6DE)
## 📸 Visuals
### Sections Overview
*Figure 1: Overview of different sections in this workshop.*
### End-to-End Sample UI
*Figure 2: User interface of the end-to-end AI native sample project.*
---
## 📦 Prerequisites
Before starting the workshop, ensure you have:
- [Python 3.10](https://www.python.org/downloads/) or higher installed
- An active Azure subscription with access to [Azure AI Foundry](https://ai.azure.com)
- [Azure CLI](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli) installed
- [Git](https://git-scm.com/downloads) installed
- [VS Code](https://code.visualstudio.com/), [GitHub Codespaces](https://github.com/features/codespaces), or [Jupyter Notebook](https://jupyter.org/install) environment
- Basic Python programming knowledge
- Model deployment and [AI Search](https://learn.microsoft.com/en-us/azure/search/search-what-is-azure-search) connection configured in Azure AI Foundry
---
## 🚀 Quick Start
1. **Clone the repo**:
```bash
git clone https://github.com/Azure/ai-foundry-workshop.git
cd ai-foundry-workshop
```
2. **Install uv**:
```bash
# Unix/Linux/macOS
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
```
3. **Create & activate a virtual environment**:
```bash
uv venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
```
4. **Set up Azure AI Foundry**:
a. **Create Project and Deploy Resources**:
1. Go to [Azure AI Foundry](https://ai.azure.com)
2. Create a new AI Hub and Project using the AI Foundry Wizard
3. Deploy required models:
- GPT models(gpt-4o, gpt-4o-mini) for chat/completion (**set TPM to max** to avoid issues with Agents notebooks)
- Embedding model for vector search
- Ensure the model is deployed in `Global-Standard` or `DataZone-Standard`
4. Set up connections:
- Configure [Grounding with Bing](https://learn.microsoft.com/en-us/azure/ai-services/agents/how-to/tools/bing-grounding?view=azure-python-preview&tabs=python&pivots=overview) connection
- Configure Azure AI Search connection
5. Add your user account to the `Azure AI Developer` role from Azure AI Foundry Management Portal
b. **Configure Environment Variables**:
```bash
cp .env.example .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](https://learn.microsoft.com/en-us/azure/ai-services/agents/concepts/model-region-support?tabs=python#azure-openai-models) for details. For Grounding with Bing Search, you need to use `gpt-4o-mini` model.
5. **Install dependencies**:
```bash
# Install core Azure AI SDKs and Jupyter requirements
uv pip install azure-identity azure-ai-projects azure-ai-inference[opentelemetry] azure-search-documents azure-ai-evaluation azure-monitor-opentelemetry
# Install Jupyter requirements
uv pip install ipykernel jupyterlab notebook
# Register the kernel with Jupyter
python -m ipykernel install --user --name=.venv --display-name="Python (.venv)"
# Install additional requirements (optional - for deploying repo or running mkdocs)
uv pip install -r requirements.txt
```
> **Note**: If you encounter kernel errors in VS Code, try:
> 1. Select kernel: Click "Select Kernel" > "Python Environments" > "Python (.venv)"
> 2. If kernel is not listed, run `python -m ipykernel install --user --name=.venv` again, or use the "Create New Kernel" wizard in VS Code to create a new Python environment
> 3. Reload VS Code if needed
6. **Choose your notebook environment**:
**Option A: VS Code**
- Install [VS Code Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
- Install either:
- [Jupyter extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter) for .ipynb files
- [Polyglot Notebooks extension](https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.dotnet-interactive-vscode) for .dib files
- Open any notebook and select your Python kernel (.venv)
**Option B: GitHub Codespaces**
- Click "Code" > "Create codespace" on the repository
- Wait for environment setup
- Notebooks will be ready to run
**Option C: Jupyter Lab/Notebook**
```bash
# Install Jupyter if you haven't already
uv pip install jupyterlab notebook
# Start Jupyter Lab (recommended)
jupyter lab
# Or start Jupyter Notebook
jupyter notebook
```
7. **Follow the Learning Path**:
1. **Introduction** (`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** (`2-notebooks/`)
- Chat Completion & RAG (`1-chat_completion/`)
- Agent Development (`2-agent_service/`)
- Quality Attributes (`3-quality_attributes/`)
---
## đź“” Workshop Learning Path
Follow these notebooks in sequence to complete the workshop:
### 1. Introduction (`1-introduction/`)
| Notebook | Description |
|----------|-------------|
| [1. Authentication](1-introduction/1-authentication.ipynb) | Set up Azure credentials and access |
| [2. Environment Setup](1-introduction/2-environment_setup.ipynb) | Configure your development environment |
| [3. Quick Start](1-introduction/3-quick_start.ipynb) | Learn basic Azure AI Foundry operations |
### 2. Main Workshop (`2-notebooks/`)
| Topic | Notebooks |
|-------|-----------|
| **Chat Completion & RAG** | • [Chat Completion & RaG](2-notebooks/1-chat_completion/) |
| **Agent Development** | • [Agent Development](2-notebooks/2-agent_service/) |
| **Quality Attributes** | • [Observability & Evaluations](2-notebooks/3-quality_attributes/) |
---
## 🤝 Contributing
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details on how to:
- Submit bug reports and feature requests
- Submit pull requests
- Follow our coding standards
- Participate in code reviews
---
## âť“ Support
If you need help or have questions:
---