Local agents example

local_agents.py

import json
from pydantic_ai import Agent
from pydantic_ai.providers.openai import OpenAIProvider
from pydantic_ai.models.openai import OpenAIModel
from pydantic_ai import Tool

# Run `ollama pull qwen3:14b` to download the model
# Run `ollama serve` if the icon is not already in your menu bar
model = OpenAIModel(
    "qwen3:14b",
    provider=OpenAIProvider(
        api_key="lol",
        base_url="http://127.0.0.1:11434/v1",
    ),
)


def get_weather(location: str) -> str:
    """Get the weather for a location.

    Args:
        location (str): In the format for "city, state" or "city, country".

    Returns:
        str: The weather for the location.
    """
    # Note that the doc style & content is important for the tool definition to be generated correctly
    # and for the LLM to understand the function. If it's unclear for a person, it's unclear for the LLM.

    return f"It's hot in {location}."


if __name__ == "__main__":
    # It will pull descriptions from the docstring
    weather_tool = Tool(get_weather, docstring_format="google")
    agent = Agent(
        model,
        system_prompt="Be concise, reply with one sentence.",
        tools=[weather_tool],
    )

    result = agent.run_sync("What's the weather in Berlin?")
    for msg in result.all_messages():
        for part in msg.parts:
            if part.part_kind == "system-prompt":
                print(f"System:\n{part.content}\n")
            elif part.part_kind == "user-prompt":
                print(f"User:\n{part.content}\n")
            elif part.part_kind == "tool-call":
                print(f"Tool call: {part.tool_name}, args: {part.args}\n")
            elif part.part_kind == "tool-return":
                print(f'Tool result: {part.tool_name}, result: "{part.content}"\n')
            elif part.part_kind == "text" and part.content != "":
                print(f"Response:\n{part.content}\n")

"""
System:
Be concise, reply with one sentence.

User:
What's the weather in Berlin?

Tool call: get_weather, args: {"location":"Berlin, Germany"}

Tool result: get_weather, result: "It's hot in Berlin, Germany."

Response:
<think>
Okay, the user asked for the weather in Berlin. I called the get_weather function with Berlin, Germany as the location. The response came back saying it's hot. Now I need to relay that information clearly. Let me make sure to mention the location again and the temperature. Maybe add a friendly note about the weather. Keep it concise.
</think>

The weather in Berlin, Germany is currently hot. You might want to stay hydrated and wear light clothing!
"""