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Human-in-the-loop research: the agent proposes a plan, you refine it, then approve it to run the full research. The flow chains turns through previous_interaction_id:
  1. collaborative_planning=True → agent returns a research plan.
  2. collaborative_planning=True → refine the plan (optional).
  3. collaborative_planning=False → agent executes the approved plan.
collaborative_planning is read fresh on every request, so flipping it on the model between turns switches plan-mode to execute-mode within the same conversation.

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Code

cookbook/90_models/google/gemini_interactions/deep_research_collaborative_planning.py
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.google import GeminiInteractions

agent = Agent(
    model=GeminiInteractions(
        agent="deep-research-preview-04-2026",
        collaborative_planning=True,
        thinking_summaries="auto",
        agent_poll_interval=5.0,
    ),
    add_history_to_context=True,
    db=SqliteDb(db_file="tmp/deep_research_collab.db"),
    markdown=True,
)

SESSION_ID = "deep-research-collab-1"

if __name__ == "__main__":
    agent.print_response(
        "Do some research on Google TPUs.",
        session_id=SESSION_ID,
    )

    agent.print_response(
        "Focus more on the differences between Google TPUs and competitor "
        "hardware, and less on the history.",
        session_id=SESSION_ID,
    )

    agent.model.collaborative_planning = False
    agent.print_response(
        "Plan looks good!",
        session_id=SESSION_ID,
    )
Mutating agent.model.collaborative_planning mid-conversation is safe only when the model instance is not shared across concurrent runs. For concurrent use, prefer two separate agents (a planner and an executor) sharing a session.

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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_collaborative_planning.py