Skip to main content
Glama

mcp-run-python

Official
by pydantic
roulette_wheel.py1.65 kB
"""Example demonstrating how to use Pydantic AI to create a simple roulette game. Run with: uv run -m pydantic_ai_examples.roulette_wheel """ from __future__ import annotations as _annotations import asyncio from dataclasses import dataclass from typing import Literal from pydantic_ai import Agent, RunContext # Define the dependencies class @dataclass class Deps: winning_number: int # Create the agent with proper typing roulette_agent = Agent( 'groq:llama-3.3-70b-versatile', deps_type=Deps, retries=3, output_type=bool, system_prompt=( 'Use the `roulette_wheel` function to determine if the customer has won based on the number they bet on.' ), ) @roulette_agent.tool async def roulette_wheel( ctx: RunContext[Deps], square: int ) -> Literal['winner', 'loser']: """Check if the bet square is a winner. Args: ctx: The context containing the winning number. square: The number the player bet on. """ return 'winner' if square == ctx.deps.winning_number else 'loser' async def main(): # Set up dependencies winning_number = 18 deps = Deps(winning_number=winning_number) # Run some example bets using streaming async with roulette_agent.run_stream( 'Put my money on square eighteen', deps=deps ) as response: result = await response.get_output() print('Bet on 18:', result) async with roulette_agent.run_stream( 'I bet five is the winner', deps=deps ) as response: result = await response.get_output() print('Bet on 5:', result) if __name__ == '__main__': asyncio.run(main())

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pydantic/pydantic-ai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server