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

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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.

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Scrape + Summarize

This example demonstrates a simple workflow: scrape a website and summarize the content using Gemini. 
import { smartScraper } from 'scrapegraph-js';
import { GoogleGenAI } from '@google/genai';

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

const scrapeResult = await smartScraper(
    apiKey,
    'https://scrapegraphai.com',
    'Extract all content from this page'
);

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

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

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

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Content Analysis

This example shows how to analyze website content using Gemini’s multi-turn conversation capabilities. 
import { smartScraper } from 'scrapegraph-js';
import { GoogleGenAI } from '@google/genai';

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

const scrapeResult = await smartScraper(
    apiKey,
    'https://news.ycombinator.com/',
    'Extract all content from this page'
);

console.log('Scraped content length:', JSON.stringify(scrapeResult.result).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(scrapeResult.result)}`
});
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);

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Structured Extraction

This example demonstrates how to extract structured data using Gemini’s JSON mode from scraped website content. 
import { smartScraper } from 'scrapegraph-js';
import { GoogleGenAI, Type } from '@google/genai';

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

const scrapeResult = await smartScraper(
    apiKey,
    'https://stripe.com',
    'Extract all content from this page'
);

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

const response = await ai.models.generateContent({
    model: 'gemini-2.5-flash',
    contents: `Extract company information: ${JSON.stringify(scrapeResult.result)}`,
    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.