Grounding with Parallel Web Search on Vertex AI

Ground Gemini 3.7 Flash responses with Parallel web search on Vertex AI.

Ground Gemini 3.7 Flash responses with Parallel web search on Vertex AI after configuring a Marketplace subscription or Parallel API key.

The source already selects gemini-3.7-flash. Parallel grounding requires Vertex AI, a supported model/location, and either a Marketplace subscription or PARALLEL_API_KEY.

parallel_grounding.py
"""Grounding with Parallel Web Search on Vertex AI.

Parallel Web Systems offers a search API optimized for LLM grounding,
providing access to live web data from billions of pages. This is available
exclusively on Vertex AI through a native first-party integration.

Note: This uses the dedicated `parallelAiSearch` tool type in Vertex AI,
which is different from the generic `ExternalApi` approach. Parallel has
a native integration with Google Cloud that handles authentication and
API communication automatically.

Requirements:
- Set up Google Cloud credentials: `gcloud auth application-default login`
- Set environment variables:
  - GOOGLE_CLOUD_PROJECT: Your GCP project ID
  - GOOGLE_CLOUD_LOCATION: Your GCP region (e.g., us-central1)
- Optionally set PARALLEL_API_KEY if not using GCP Marketplace subscription

Run `pip install google-genai` to install dependencies.

For more information, see:
- https://docs.cloud.google.com/vertex-ai/generative-ai/docs/grounding/grounding-with-parallel
- https://docs.parallel.ai/integrations/google-vertex
"""

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

# Create an agent with Parallel web search grounding
agent = Agent(
    model=Gemini(
        id="gemini-3.7-flash",
        vertexai=True,  # Required for Parallel grounding
        parallel_search=True,
        # Optional: provide API key directly instead of env var.
        # If omitted, uses PARALLEL_API_KEY env var or GCP Marketplace subscription.
        # parallel_api_key="your-api-key",
        # Optional: custom configuration for domain filtering, excerpt limits, etc.
        # Passed as custom_configs to ToolParallelAiSearch.
        # parallel_config={"source_policy": {"exclude_domains": ["example.com"]}},
    ),
    add_datetime_to_context=True,
    markdown=True,
)

# Ask questions that benefit from real-time web information
agent.print_response(
    "What are the latest developments in quantum computing this week?",
    stream=True,
)

# The response will include citations from Parallel's web search results
# agent.print_response(
#     "What are the top trending topics in AI research today?",
#     stream=True,
# )

Run the Example

Set up your virtual environment

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

Install dependencies

uv pip install -U agno google-genai

Export environment variables

export GOOGLE_CLOUD_LOCATION="your_google_cloud_location_here"
export GOOGLE_CLOUD_PROJECT="your_google_cloud_project_here"

Authenticate with Google Cloud

Sign in with Application Default Credentials:

gcloud auth application-default login

Configure Parallel access

Subscribe to Parallel through Google Cloud Marketplace, or create a Parallel API key and export it as PARALLEL_API_KEY in the shell that runs the example.

Run the example

Save the code above as parallel_grounding.py, then run:

python parallel_grounding.py

Full source: cookbook/90_models/google/gemini/parallel_grounding.py