Search Grounding with Gemini

Search grounding is a powerful feature in the Gemini API that allows you to enhance your model's responses by providing relevant search results as context.

See Live Demo built using these code snippets

Typescript

import {
  DynamicRetrievalMode,
  GoogleGenerativeAI,
} from "@google/generative-ai";

const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
const model = genAI.getGenerativeModel(
{
    model: "models/gemini-2.0-flash",
}
);

const result = await model.generateContent({
contents: [
    {
    role: "user",
    parts: [{ text: searchQuery }],
    },
],
tools: [
    {
    google_search: {},
    },
],
});

console.log(result.response.candidates[0].groundingMetadata);

Python

from google import genai
from google.genai.types import Tool, GenerateContentConfig, GoogleSearch

client = genai.Client()
model_id = "gemini-2.0-flash"

google_search_tool = Tool(
    google_search = GoogleSearch()
)

response = client.models.generate_content(
    model=model_id,
    contents="When is the next total solar eclipse in the United States?",
    config=GenerateContentConfig(
        tools=[google_search_tool],
        response_modalities=["TEXT"],
    )
)

for each in response.candidates[0].content.parts:
    print(each.text)
# Example response:
# The next total solar eclipse visible in the contiguous United States will be on ...

# To get grounding metadata as web content.
print(response.candidates[0].grounding_metadata.search_entry_point.rendered_content)