docs: update JS SDK docs to match scrapegraph-js PR #13

Rewrite all JavaScript code examples to match the new v2 SDK API from
ScrapeGraphAI/scrapegraph-js#13. Key changes:
- Replace factory pattern (scrapegraphai({ apiKey })) with direct imports
- All functions use (apiKey, params) signature
- scrape() uses formats array instead of single format string
- Return type is ApiResult<T> with status check, not throw-on-error
- crawl.status() renamed to crawl.get(), crawl.delete() added
- monitor.create() uses formats array, not prompt
- Restore generateSchema and checkHealth in docs
- Schema params use JSON objects, not Zod instances
- history is now history.list() and history.get()

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: VinciGit00

api-reference/errors.mdx

@@ -139,17 +139,17 @@ except APIError as e:
 ```
 
 ```javascript JavaScript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } from 'scrapegraph-js';
 
-const sgai = scrapegraphai({ apiKey: 'your-api-key' });
+const result = await extract('your-api-key', {
+  url: 'https://example.com',
+  prompt: 'Extract data',
+});
 
-try {
-  const { data } = await sgai.extract('https://example.com', {
-    prompt: 'Extract data',
-  });
-  console.log('Data:', data);
-} catch (error) {
-  console.error('Error:', error.message);
+if (result.status === 'success') {
+  console.log('Data:', result.data);
+} else {
+  console.error('Error:', result.error);
 }
 ```
 </CodeGroup>

cookbook/examples/pagination.mdx

@@ -349,20 +349,17 @@ if __name__ == "__main__":
 ## JavaScript SDK Example
 
 ```javascript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } from 'scrapegraph-js';
 import 'dotenv/config';
 
-const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
+const result = await extract(process.env.SGAI_APIKEY, {
+  url: 'https://www.amazon.in/s?k=tv&crid=1TEF1ZFVLU8R8&sprefix=t%2Caps%2C390&ref=nb_sb_noss_2',
+  prompt: 'Extract all product info including name, price, rating, and image_url',
+});
 
-const { data } = await sgai.extract(
-  'https://www.amazon.in/s?k=tv&crid=1TEF1ZFVLU8R8&sprefix=t%2Caps%2C390&ref=nb_sb_noss_2',
-  {
-    prompt: 'Extract all product info including name, price, rating, and image_url',
-    totalPages: 3,
-  }
-);
-
-console.log('Response:', JSON.stringify(data, null, 2));
+if (result.status === 'success') {
+  console.log('Response:', JSON.stringify(result.data?.json, null, 2));
+}
 ```
 
 ## Example Output

developer-guides/llm-sdks-and-frameworks/anthropic.mdx

@@ -27,16 +27,17 @@ If using Node < 20, install `dotenv` and add `import 'dotenv/config'` to your co
 This example demonstrates a simple workflow: scrape a website and summarize the content using Claude.
 
 ```typescript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } from 'scrapegraph-js';
 import Anthropic from '@anthropic-ai/sdk';
 
-const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
 const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
 
-const { data } = await sgai.extract('https://scrapegraphai.com', {
+const result = await extract(process.env.SGAI_APIKEY!, {
+    url: 'https://scrapegraphai.com',
     prompt: 'Extract all content from this page',
 });
 
+const data = result.data?.json;
 console.log('Scraped content length:', JSON.stringify(data).length);
 
 const message = await anthropic.messages.create({
@@ -55,12 +56,11 @@ console.log('Response:', message);
 This example shows how to use Claude's tool use feature to let the model decide when to scrape websites based on user requests.
 
 ```typescript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } from 'scrapegraph-js';
 import { Anthropic } from '@anthropic-ai/sdk';
 import { z } from 'zod';
 import { zodToJsonSchema } from 'zod-to-json-schema';
 
-const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
 const anthropic = new Anthropic({
     apiKey: process.env.ANTHROPIC_API_KEY
 });
@@ -90,10 +90,12 @@ if (toolUse && toolUse.type === 'tool_use') {
     const input = toolUse.input as { url: string };
     console.log(`Calling tool: ${toolUse.name} | URL: ${input.url}`);
 
-    const { data } = await sgai.extract(input.url, {
+    const result = await extract(process.env.SGAI_APIKEY!, {
+        url: input.url,
         prompt: 'Extract all content from this page',
     });
 
+    const data = result.data?.json;
     console.log(`Scraped content preview: ${JSON.stringify(data)?.substring(0, 300)}...`);
     // Continue with the conversation or process the scraped content as needed
 }
@@ -104,11 +106,10 @@ if (toolUse && toolUse.type === 'tool_use') {
 This example demonstrates how to use Claude to extract structured data from scraped website content.
 
 ```typescript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } from 'scrapegraph-js';
 import Anthropic from '@anthropic-ai/sdk';
 import { z } from 'zod';
 
-const sgai = scrapegraphai({ apiKey: process.env.SGAI_APIKEY });
 const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
 
 const CompanyInfoSchema = z.object({
@@ -117,9 +118,11 @@ const CompanyInfoSchema = z.object({
     description: z.string().optional()
 });
 
-const { data } = await sgai.extract('https://stripe.com', {
+const result = await extract(process.env.SGAI_APIKEY!, {
+    url: 'https://stripe.com',
     prompt: 'Extract all content from this page',
 });
+const data = result.data?.json;
 
 const prompt = `Extract company information from this website content.
 

developer-guides/llm-sdks-and-frameworks/gemini.mdx

@@ -27,15 +27,16 @@ If using Node < 20, install `dotenv` and add `import 'dotenv/config'` to your co
 This example demonstrates a simple workflow: scrape a website and summarize the content using Gemini.
 
 ```typescript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } 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', {
+const result = await extract(process.env.SGAI_APIKEY!, {
+    url: 'https://scrapegraphai.com',
     prompt: 'Extract all content from this page',
 });
+const data = result.data?.json;
 
 console.log('Scraped content length:', JSON.stringify(data).length);
 
@@ -52,15 +53,16 @@ console.log('Summary:', response.text);
 This example shows how to analyze website content using Gemini's multi-turn conversation capabilities.
 
 ```typescript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } 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/', {
+const result = await extract(process.env.SGAI_APIKEY!, {
+    url: 'https://news.ycombinator.com/',
     prompt: 'Extract all content from this page',
 });
+const data = result.data?.json;
 
 console.log('Scraped content length:', JSON.stringify(data).length);
 
@@ -86,15 +88,16 @@ console.log('4th and 5th Stories:', result2.text);
 This example demonstrates how to extract structured data using Gemini's JSON mode from scraped website content.
 
 ```typescript
-import { scrapegraphai } from 'scrapegraph-js';
+import { extract } 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', {
+const result = await extract(process.env.SGAI_APIKEY!, {
+    url: 'https://stripe.com',
     prompt: 'Extract all content from this page',
 });
+const data = result.data?.json;
 
 console.log('Scraped content length:', JSON.stringify(data).length);
 

integrations/vercel_ai.mdx

@@ -57,21 +57,7 @@ The ScrapeGraph SDK can be used like any other tool. See [Vercel AI tool calling
 import { z } from "zod";
 import { generateText, tool } from "ai";
 import { openai } from "@ai-sdk/openai";
-import { scrapegraphai } from "scrapegraph-js";
-
-const sgai = scrapegraphai({ apiKey: process.env.SGAI_API_KEY });
-
-const ArticleSchema = z.object({
-  title: z.string().describe("The article title"),
-  author: z.string().describe("The author's name"),
-  publishDate: z.string().describe("Article publication date"),
-  content: z.string().describe("Main article content"),
-  category: z.string().describe("Article category"),
-});
-
-const ArticlesArraySchema = z
-  .array(ArticleSchema)
-  .describe("Array of articles");
+import { extract } from "scrapegraph-js";
 
 const result = await generateText({
   model: openai("gpt-4.1-mini"),
@@ -82,11 +68,29 @@ const result = await generateText({
         url: z.string().describe("The exact URL."),
       }),
       execute: async ({ url }) => {
-        const response = await sgai.extract(url, {
+        const response = await extract(process.env.SGAI_API_KEY!, {
+          url,
           prompt: "Extract the article information",
-          schema: ArticlesArraySchema,
+          schema: {
+            type: "object",
+            properties: {
+              articles: {
+                type: "array",
+                items: {
+                  type: "object",
+                  properties: {
+                    title: { type: "string" },
+                    author: { type: "string" },
+                    publishDate: { type: "string" },
+                    content: { type: "string" },
+                    category: { type: "string" },
+                  },
+                },
+              },
+            },
+          },
         });
-        return response.data;
+        return response.data?.json;
       },
     }),
   },

knowledge-base/account/api-keys.mdx

@@ -24,10 +24,12 @@ client = Client(api_key="your-api-key")
 ```
 
 ```javascript JavaScript
-import { scrapegraphai } from "scrapegraph-js";
+import { extract } from "scrapegraph-js";
 
-const sgai = scrapegraphai({ apiKey: "your-api-key" });
-const { data } = await sgai.extract(url, { prompt });
+const result = await extract("your-api-key", {
+  url: "https://example.com",
+  prompt: "Extract the title",
+});
 ```
 
 ```bash cURL

knowledge-base/ai-tools/cursor.mdx

@@ -53,12 +53,11 @@ Ask Cursor:
 > Write a JavaScript function using scrapegraph-js that extracts product details from an e-commerce page.
 
 ```javascript
-import { scrapegraphai } from "scrapegraph-js";
+import { extract } from "scrapegraph-js";
 
-const sgai = scrapegraphai({ apiKey: "your-api-key" });
-
-async function extractProduct(url) {
-  return await sgai.extract(url, {
+async function extractProduct(apiKey, url) {
+  return await extract(apiKey, {
+    url,
     prompt: "Extract the product name, price, and availability",
   });
 }

knowledge-base/scraping/custom-headers.mdx

@@ -26,10 +26,10 @@ response = client.smartscraper(
 ```
 
 ```javascript
-import { scrapegraphai } from "scrapegraph-js";
+import { extract } from "scrapegraph-js";
 
-const sgai = scrapegraphai({ apiKey: "your-api-key" });
-const { data } = await sgai.extract("https://example.com/protected-page", {
+const result = await extract("your-api-key", {
+  url: "https://example.com/protected-page",
   prompt: "Extract the main content",
   fetchConfig: {
     headers: {

knowledge-base/scraping/javascript-rendering.mdx

@@ -26,10 +26,10 @@ response = client.smartscraper(
 ```
 
 ```javascript
-import { scrapegraphai } from "scrapegraph-js";
+import { extract } from "scrapegraph-js";
 
-const sgai = scrapegraphai({ apiKey: "your-api-key" });
-const { data } = await sgai.extract("https://example.com/products", {
+const result = await extract("your-api-key", {
+  url: "https://example.com/products",
   prompt: "Extract all product names and prices",
   fetchConfig: { wait: 2000 },
 });

knowledge-base/scraping/pagination.mdx

@@ -43,17 +43,19 @@ print(f"Total products extracted: {len(all_results)}")
 ```
 
 ```javascript
-import { scrapegraphai } from "scrapegraph-js";
+import { extract } from "scrapegraph-js";
 
-const sgai = scrapegraphai({ apiKey: "your-api-key" });
 const allResults = [];
 
 for (let page = 1; page <= 5; page++) {
   const url = `https://example.com/products?page=${page}`;
-  const { data } = await sgai.extract(url, {
+  const result = await extract("your-api-key", {
+    url,
     prompt: "Extract all product names and prices on this page",
   });
-  allResults.push(...(data?.products ?? []));
+  if (result.status === "success") {
+    allResults.push(...(result.data?.json?.products ?? []));
+  }
 }
 ```