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Run the Deep Research managed agent through the Gemini Interactions API. The agent plans the task, searches the web, and returns a researched report with citations. The model forces background=True and store=True, and the non-streaming path polls until the result is ready.

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Code

cookbook/90_models/google/gemini_interactions/deep_research.py
import asyncio

from agno.agent import Agent
from agno.models.google import GeminiInteractions

agent = Agent(
    model=GeminiInteractions(
        agent="deep-research-preview-04-2026",
        thinking_summaries="auto",
        visualization="auto",
    ),
    markdown=True,
)

if __name__ == "__main__":
    agent.print_response(
        "Research the current state of solid-state battery commercialization "
        "and summarize the leading approaches."
    )

    asyncio.run(
        agent.aprint_response(
            "Compare the major open-source vector databases on indexing and query latency.",
            stream=True,
        )
    )

​
Usage

1

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
2

Set your API key

export GOOGLE_API_KEY=xxx
3

Install dependencies

uv pip install -U "google-genai>=2.0" agno
4

Run Agent

python cookbook/90_models/google/gemini_interactions/deep_research.py