basic.py
"""
Basic Advisor
=============
The simplest usage of AdvisorTools: give your agent a single advisor model
it can ask for feedback, a second opinion, or additional context.
How it works:
1. The primary agent (OpenAI) drafts a response
2. It calls `ask_advisor` with a specific question and relevant context
3. The advisor (Gemini) answers without seeing the rest of the conversation
4. The primary agent decides what to incorporate into its final answer
Unlike a critique loop, the agent stays in control: advisor responses are
advice, not instructions.
"""
from agno.agent import Agent
from agno.models.google import Gemini
from agno.models.openai import OpenAIResponses
from agno.tools.advisor import AdvisorTools
# ---------------------------------------------------------------------------
# Create Agent with a single Gemini advisor
# ---------------------------------------------------------------------------
agent = Agent(
model=OpenAIResponses(id="gpt-5.5"),
tools=[
AdvisorTools(
advisors=[Gemini(id="gemini-3.5-flash")],
)
],
instructions=[
"After drafting a response, ask your advisor for a second opinion.",
"Incorporate the suggestions you agree with into your final answer.",
],
markdown=True,
)
# ---------------------------------------------------------------------------
# Run
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent.print_response(
"Explain how DNS resolution works when you type a URL in your browser",
stream=True,
)
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno google-genai openai
3
Export your API keys
export GOOGLE_API_KEY="your_google_api_key_here"
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:GOOGLE_API_KEY="your_google_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
basic.py, then run:python basic.py