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mcp-run-python

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by pydantic
flight-booking.md1.32 kB
Example of a multi-agent flow where one agent delegates work to another, then hands off control to a third agent. Demonstrates: * [agent delegation](../multi-agent-applications.md#agent-delegation) * [programmatic agent hand-off](../multi-agent-applications.md#programmatic-agent-hand-off) * [usage limits](../agents.md#usage-limits) 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](./setup.md#usage), run: ```bash python/uv-run -m pydantic_ai_examples.flight_booking ``` ## Example Code ```snippet {path="/examples/pydantic_ai_examples/flight_booking.py"}```

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