Flight Booking - Pydantic Ai

Example of a multi-agent flow where one agent delegates work to another, then hands off control to a third agent.

Demonstrates:

In this scenario, a group of agents work together to find the best flight for a user.

The control flow for this example can be summarised as follows:

mermaid

graph TD
  START --> search_agent("search agent")
  search_agent --> extraction_agent("extraction agent")
  extraction_agent --> search_agent
  search_agent --> human_confirm("human confirm")
  human_confirm --> search_agent
  search_agent --> FAILED
  human_confirm --> find_seat_function("find seat function")
  find_seat_function --> human_seat_choice("human seat choice")
  human_seat_choice --> find_seat_agent("find seat agent")
  find_seat_agent --> find_seat_function
  find_seat_function --> buy_flights("buy flights")
  buy_flights --> SUCCESS

Running the Example

With dependencies installed and environment variables set, run:

bash

python/uv-run -m pydantic_ai_examples.flight_booking

Example Code

snippet {path="/examples/pydantic_ai_examples/flight_booking.py"}