This project demonstrates a basic conversational AI agent using the PydanticAI framework.
The project features a conversational AI agent that acts as a waiter in a restaurant, handling dietary requirements and taking orders. It showcases the following capabilities:
- Dynamic model choice
- Human-in-the-loop input
- Tool calling with dependencies
- Conversation history/memory
- Dynamic system prompt
- Structured output
AI Waiter: Ah, bonjour madame et monsieur! Welcome to Le Bistro, where the food is as delightful as the company! Before we embark on a culinary adventure, might you have any dietary restrictions or preferences? We wouldn't want any rogue ingredients crashing the party!
You: I only eat yellow coloured food
AI Waiter: Magnifique! A connoisseur of the golden hue, I see! Let's explore the menu with your sunshine-filled preference in mind. For appetizers, we have the Quinoa Stuffed Bell Peppers, which are a vibrant yellow. For the main course, the Chickpea and Sweet Potato Curry is a golden delight! And for dessert, the Fresh Fruit Sorbet might have some yellow options depending on the day! What do you think?
You: I'll take the Bell Peppers and fruit sorbet
AI Waiter: Excellent choices! One order of the Quinoa Stuffed Bell Peppers and the Fresh Fruit Sorbet for the discerning palate at table number 1! Your order has been placed, and I shall return with your delectable delights shortly. Au revoir!
Order placed: [Order(menu_items=['Quinoa Stuffed Bell Peppers', 'Fresh Fruit Sorbet'], table_number=1)]
The agent is built using PydanticAI's Agent class, implementing the AgentRunner common interface.
- PydanticAI implementation: pydanticai/agent.py
- Python 3.11+
- API key for LLM provider (e.g., OpenAI, Anthropic, Gemini)
Install the project in editable mode:
make installThe agent can be run via the command line.
uv run python -m pydantic-ai-demo --model=<provider:model_name> --api_key=<api_key>Note
Run uv run python -m pydantic-ai-demo -h for details about the available options.
The project includes a Makefile for common development tasks:
make install: Installs the project dependencies.make run: Runs the PydanticAI agent with default settings.make test: Runs tests.make lint: Runs linting checks.make format: Formats the code.make clean: Cleans up build artifacts and caches.