# Copyright (c) Microsoft. All rights reserved.

import asyncio

from agent_framework import Agent
from agent_framework.ollama import OllamaChatClient
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

"""
Ollama Agent Reasoning Example

This sample demonstrates implementing a Ollama agent with reasoning.

Ensure to install Ollama and have a model running locally before running the sample
Not all Models support reasoning, to test reasoning try qwen3:8b
Set the model to use via the OLLAMA_MODEL environment variable or modify the code below.
https://ollama.com/

"""


async def main() -> None:
    print("=== Response Reasoning Example ===")

    agent = Agent(
        client=OllamaChatClient(),
        name="TimeAgent",
        instructions="You are a helpful agent answer in one sentence.",
        default_options={"think": True},  # Enable Reasoning on agent level
    )
    query = "Hey what is 3+4? Can you explain how you got to that answer?"
    print(f"User: {query}")
    # Enable Reasoning on per request level
    result = await agent.run(query)
    reasoning = "".join((c.text or "") for c in result.messages[-1].contents if c.type == "text_reasoning")
    print(f"Reasoning: {reasoning}")
    print(f"Answer: {result}\n")


if __name__ == "__main__":
    asyncio.run(main())