Agentic Azure App Service app with LangGraph and Azure AI Foundry Agent Service

This repository demonstrates how to build a modern FatAPI web application that integrates with both Azure AI Foundry Agents and LangGraph Agents. It provides a simple CRUD task list and two interactive chat agents.

Getting Started

See Tutorial: Build an agentic web app in Azure App Service with LangGraph or Azure AI Foundry Agent Service (Python).

Features

• Task List: Simple CRUD web app application.
• LangGraph Agent: Chat with an agent powered by LangGraph.
• Azure AI Foundry Agent: Chat with an agent powered by Azure AI Foundry Agent Service.
• OpenAPI Schema: Enables integration with Azure AI Foundry agents.

Project Structure

.devcontainer/
└── devcontainer.json            # Dev container configuration for VS Code
infra/
├── main.bicep                   # Bicep IaC template
├── main.parameters.json         # Parameters for Bicep deployment
public/
└── index.html                   # React frontend
src/
├── __init__.py
├── app.py                       # Main FastAPI application
├── azure.yaml                   # Azure Developer CLI config
├── agents/                      # AI agent implementations
│   ├── __init__.py
│   ├── foundry_task_agent.py    # Azure AI Foundry agent
│   └── langgraph_task_agent.py  # LangGraph agent
├── models/                      # Pydantic models for data validation
│   └── __init__.py
├── routes/                      # API route definitions
│   ├── __init__.py
│   └── api.py                   # Task and chat endpoints
└── services/                    # Business logic services
    ├── __init__.py
    └── task_service.py          # Task CRUD operations with SQLite
tasks.db                         # SQLite database file
requirements.txt                 # Python dependencies
README.md                        # Project documentation