gemini.mdx

title	Gemini
description	Use ScrapeGraphAI with Google Gemini AI for web scraping + AI workflows

Integrate ScrapeGraphAI with Google's Gemini for AI applications powered by web data.

Setup

npm install scrapegraph-js @google/genai

Create .env file:

SGAI_APIKEY=your_scrapegraph_key
GEMINI_API_KEY=your_gemini_key

If using Node < 20, install `dotenv` and add `import 'dotenv/config'` to your code.

Scrape + Summarize

This example demonstrates a simple workflow: scrape a website and summarize the content using Gemini.

import { scrapegraphai } from 'scrapegraph-js';
import { GoogleGenAI } from '@google/genai';

const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });

const { data } = await sgai.extract('https://scrapegraphai.com', {
    prompt: 'Extract all content from this page',
});

console.log('Scraped content length:', JSON.stringify(data).length);

const response = await ai.models.generateContent({
    model: 'gemini-2.5-flash',
    contents: `Summarize: ${JSON.stringify(data)}`,
});

console.log('Summary:', response.text);

Content Analysis

This example shows how to analyze website content using Gemini's multi-turn conversation capabilities.

import { scrapegraphai } from 'scrapegraph-js';
import { GoogleGenAI } from '@google/genai';

const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });

const { data } = await sgai.extract('https://news.ycombinator.com/', {
    prompt: 'Extract all content from this page',
});

console.log('Scraped content length:', JSON.stringify(data).length);

const chat = ai.chats.create({
    model: 'gemini-2.5-flash'
});

// Ask for the top 3 stories on Hacker News
const result1 = await chat.sendMessage({
    message: `Based on this website content from Hacker News, what are the top 3 stories right now?\n\n${JSON.stringify(data)}`
});
console.log('Top 3 Stories:', result1.text);

// Ask for the 4th and 5th stories on Hacker News
const result2 = await chat.sendMessage({
    message: `Now, what are the 4th and 5th top stories on Hacker News from the same content?`
});
console.log('4th and 5th Stories:', result2.text);

Structured Extraction

This example demonstrates how to extract structured data using Gemini's JSON mode from scraped website content.

import { scrapegraphai } from 'scrapegraph-js';
import { GoogleGenAI, Type } from '@google/genai';

const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });

const { data } = await sgai.extract('https://stripe.com', {
    prompt: 'Extract all content from this page',
});

console.log('Scraped content length:', JSON.stringify(data).length);

const response = await ai.models.generateContent({
    model: 'gemini-2.5-flash',
    contents: `Extract company information: ${JSON.stringify(data)}`,
    config: {
        responseMimeType: 'application/json',
        responseSchema: {
            type: Type.OBJECT,
            properties: {
                name: { type: Type.STRING },
                industry: { type: Type.STRING },
                description: { type: Type.STRING },
                products: {
                    type: Type.ARRAY,
                    items: { type: Type.STRING }
                }
            },
            propertyOrdering: ['name', 'industry', 'description', 'products']
        }
    }
});

console.log('Extracted company info:', response?.text);

For more examples, check the Gemini documentation.