Vertex AI Search with Gemini.

Vertex AI Search allows Gemini to search through your data stores, providing grounded responses based on your private knowledge base.

"""Vertex AI Search with Gemini.

Vertex AI Search allows Gemini to search through your data stores,
providing grounded responses based on your private knowledge base.

Prerequisites:
1. Set up Vertex AI Search datastore in Google Cloud Console
2. Export environment variables:
   export GOOGLE_GENAI_USE_VERTEXAI="true"
   export GOOGLE_CLOUD_PROJECT="your-project-id"
   export GOOGLE_CLOUD_LOCATION="your-location"

Run `uv pip install google-generativeai` to install dependencies.
"""

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

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

# Replace with your actual Vertex AI Search datastore ID
# Format: "projects/{project_id}/locations/{location}/collections/default_collection/dataStores/{datastore_id}"
datastore_id = "projects/your-project-id/locations/global/collections/default_collection/dataStores/your-datastore-id"

agent = Agent(
    model=Gemini(
        id="gemini-2.5-flash",
        vertexai_search=True,
        vertexai_search_datastore=datastore_id,
        vertexai=True,  # Use Vertex AI endpoint
    ),
    markdown=True,
)

# Ask questions that can be answered from your knowledge base
agent.print_response("What are our company's policies regarding remote work?")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/90_models/google/gemini

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python vertex_ai_search.py