Pydantic AI

pip install pytest-llmtest[pydantic-ai]

from pydantic_ai import Agent
from llmtest.integrations.pydantic_ai import PydanticAIAdapter
from llmtest import expect
 
agent = Agent('openai:gpt-5-mini', system_prompt='Be concise.')
adapter = PydanticAIAdapter(agent)
 
def test_my_agent():
    output = adapter.run_sync("What is the capital of France?")
 
    assert expect.contains("Paris").check(output).passed
    assert expect.latency_under(5000).check(output).passed
    assert expect.cost_under(0.01).check(output).passed

from pydantic import BaseModel
 
class CityInfo(BaseModel):
    name: str
    country: str
 
agent = Agent('openai:gpt-5-mini', output_type=CityInfo)
adapter = PydanticAIAdapter(agent)
 
def test_structured():
    output = adapter.run_sync("Tell me about Paris")
    assert expect.structured_output(CityInfo).check(output).passed

agent = Agent('openai:gpt-5-mini')
 
@agent.tool_plain
def add(a: int, b: int) -> int:
    return a + b
 
adapter = PydanticAIAdapter(agent)
 
def test_tools():
    output = adapter.run_sync("What is 42 + 58?")
    assert output.tool_calls
    assert output.tool_calls[0]["name"] == "add"

from dataclasses import dataclass
 
@dataclass
class MyDeps:
    api_key: str
 
agent = Agent('openai:gpt-5-mini', deps_type=MyDeps)
adapter = PydanticAIAdapter(agent)
 
def test_with_deps():
    output = adapter.run_sync("Fetch data", deps=MyDeps(api_key="test"))
    assert output.content

def test_retry():
    output = adapter.run_sync(
        "Name a European capital",
        retries=3,
        retry_if=lambda out: "Paris" not in out.content,
    )
    assert "Paris" in output.content

import pytest
 
@pytest.mark.asyncio
async def test_async():
    output = await adapter.run("What is the capital of France?")
    assert expect.contains("Paris").check(output).passed