Code
reasoning_effort.py
Usage
1
Set up your virtual environment
2
Set your API key
3
Install dependencies
4
Run Agent
Save the code above as
reasoning_effort.py, then run:Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Control how much reasoning o3-mini does with the reasoning_effort parameter.
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.websearch import WebSearchTools
agent = Agent(
model=OpenAIChat(id="o3-mini", reasoning_effort="high"),
tools=[WebSearchTools(enable_news=False)],
instructions="Use tables to display data.",
markdown=True,
)
agent.print_response("Write a report comparing NVDA to TSLA", stream=True)
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
Set your API key
export OPENAI_API_KEY=xxx
Install dependencies
uv pip install -U openai ddgs agno
Run Agent
reasoning_effort.py, then run:python reasoning_effort.py
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