Merge pull request #43 from ScrapeGraphAI/revert-v2-docs-pr39

Revert "feat: v2 documentation with versioned navigation and updated SDKs" (PR #39)

Author: VinciGit00

.gitignore

@@ -1 +0,0 @@
-DS_Store

api-reference/endpoint/smartcrawler/start.mdx

@@ -229,7 +229,7 @@ sha256={your_webhook_secret}
 
 To verify that a webhook request is authentic:
 
-1. Retrieve your webhook secret from the [dashboard](https://scrapegraphai.com/dashboard)
+1. Retrieve your webhook secret from the [dashboard](https://dashboard.scrapegraphai.com)
 2. Compare the `X-Webhook-Signature` header value with `sha256={your_secret}`
 
 <CodeGroup>
@@ -305,5 +305,5 @@ The webhook POST request contains the following JSON payload:
 | result | string | The crawl result data (null if failed) |
 
 <Note>
-Make sure to configure your webhook secret in the [dashboard](https://scrapegraphai.com/dashboard) before using webhooks. Each user has a unique webhook secret for secure verification.
+Make sure to configure your webhook secret in the [dashboard](https://dashboard.scrapegraphai.com) before using webhooks. Each user has a unique webhook secret for secure verification.
 </Note>

api-reference/errors.mdx

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

api-reference/introduction.mdx

@@ -9,7 +9,7 @@ The ScrapeGraphAI API provides powerful endpoints for AI-powered web scraping an
 
 ## Authentication
 
-All API requests require authentication using an API key. You can get your API key from the [dashboard](https://scrapegraphai.com/dashboard).
+All API requests require authentication using an API key. You can get your API key from the [dashboard](https://dashboard.scrapegraphai.com).
 
 ```bash
 SGAI-APIKEY: your-api-key-here

cookbook/examples/pagination.mdx

@@ -349,16 +349,21 @@ if __name__ == "__main__":
 ## JavaScript SDK Example
 
 ```javascript
-import { extract } from 'scrapegraph-js';
+import { smartScraper } from 'scrapegraph-js';
 import 'dotenv/config';
 
-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 apiKey = process.env.SGAI_APIKEY;
+
+const response = await smartScraper(apiKey, {
+  website_url: 'https://www.amazon.in/s?k=tv&crid=1TEF1ZFVLU8R8&sprefix=t%2Caps%2C390&ref=nb_sb_noss_2',
+  user_prompt: 'Extract all product info including name, price, rating, and image_url',
+  total_pages: 3,
 });
 
-if (result.status === 'success') {
-  console.log('Response:', JSON.stringify(result.data?.json, null, 2));
+if (response.status === 'error') {
+  console.error('Error:', response.error);
+} else {
+  console.log('Response:', JSON.stringify(response.data, null, 2));
 }
 ```
 

cookbook/introduction.mdx

@@ -87,7 +87,7 @@ Each example is available in multiple implementations:
 4. Experiment and adapt the code for your needs
 
 <Note>
-Make sure to have your ScrapeGraphAI API key ready. Get one from the [dashboard](https://scrapegraphai.com/dashboard) if you haven't already.
+Make sure to have your ScrapeGraphAI API key ready. Get one from the [dashboard](https://dashboard.scrapegraphai.com) if you haven't already.
 </Note>
 
 ## Additional Resources

dashboard/overview.mdx

@@ -19,6 +19,21 @@ The ScrapeGraphAI dashboard is your central hub for managing all your web scrapi
 - **Last Used**: Timestamp of your most recent API request
 - **Quick Actions**: Buttons to start new scraping jobs or access common features
 
+## Usage Analytics
+
+Track your API usage patterns with our detailed analytics view:
+
+<Frame>
+  <img src="/images/dashboard/dashboard-2.png" alt="Usage Analytics Graph" />
+</Frame>
+
+The usage graph provides:
+- **Service-specific metrics**: Track usage for SmartScraper, SearchScraper, and Markdownify separately
+- **Time-based analysis**: View usage patterns over different time periods
+- **Interactive tooltips**: Hover over data points to see detailed information
+- **Trend analysis**: Identify usage patterns and optimize your API consumption
+
+
 ## Key Features
 
 - **Usage Statistics**: Monitor your API usage and remaining credits
@@ -28,7 +43,7 @@ The ScrapeGraphAI dashboard is your central hub for managing all your web scrapi
 
 ## Getting Started
 
-1. Log in to your [dashboard](https://scrapegraphai.com/dashboard)
+1. Log in to your [dashboard](https://dashboard.scrapegraphai.com)
 2. View your API key in the settings section
 3. Check your available credits
 4. Start your first scraping job

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

@@ -27,24 +27,24 @@ 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 { extract } from 'scrapegraph-js';
+import { smartScraper } from 'scrapegraph-js';
 import Anthropic from '@anthropic-ai/sdk';
 
+const apiKey = process.env.SGAI_APIKEY;
 const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
 
-const result = await extract(process.env.SGAI_APIKEY!, {
-    url: 'https://scrapegraphai.com',
-    prompt: 'Extract all content from this page',
+const scrapeResult = await smartScraper(apiKey, {
+    website_url: 'https://scrapegraphai.com',
+    user_prompt: 'Extract all content from this page',
 });
 
-const data = result.data?.json;
-console.log('Scraped content length:', JSON.stringify(data).length);
+console.log('Scraped content length:', JSON.stringify(scrapeResult.data.result).length);
 
 const message = await anthropic.messages.create({
     model: 'claude-haiku-4-5',
     max_tokens: 1024,
     messages: [
-        { role: 'user', content: `Summarize in 100 words: ${JSON.stringify(data)}` }
+        { role: 'user', content: `Summarize in 100 words: ${JSON.stringify(scrapeResult.data.result)}` }
     ]
 });
 
@@ -56,11 +56,12 @@ 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 { extract } from 'scrapegraph-js';
+import { smartScraper } from 'scrapegraph-js';
 import { Anthropic } from '@anthropic-ai/sdk';
 import { z } from 'zod';
 import { zodToJsonSchema } from 'zod-to-json-schema';
 
+const apiKey = process.env.SGAI_APIKEY;
 const anthropic = new Anthropic({
     apiKey: process.env.ANTHROPIC_API_KEY
 });
@@ -90,13 +91,12 @@ if (toolUse && toolUse.type === 'tool_use') {
     const input = toolUse.input as { url: string };
     console.log(`Calling tool: ${toolUse.name} | URL: ${input.url}`);
 
-    const result = await extract(process.env.SGAI_APIKEY!, {
-        url: input.url,
-        prompt: 'Extract all content from this page',
+    const result = await smartScraper(apiKey, {
+        website_url: input.url,
+        user_prompt: 'Extract all content from this page',
     });
 
-    const data = result.data?.json;
-    console.log(`Scraped content preview: ${JSON.stringify(data)?.substring(0, 300)}...`);
+    console.log(`Scraped content preview: ${JSON.stringify(result.data.result)?.substring(0, 300)}...`);
     // Continue with the conversation or process the scraped content as needed
 }
 ```
@@ -106,10 +106,11 @@ if (toolUse && toolUse.type === 'tool_use') {
 This example demonstrates how to use Claude to extract structured data from scraped website content.
 
 ```typescript
-import { extract } from 'scrapegraph-js';
+import { smartScraper } from 'scrapegraph-js';
 import Anthropic from '@anthropic-ai/sdk';
 import { z } from 'zod';
 
+const apiKey = process.env.SGAI_APIKEY;
 const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });
 
 const CompanyInfoSchema = z.object({
@@ -118,11 +119,10 @@ const CompanyInfoSchema = z.object({
     description: z.string().optional()
 });
 
-const result = await extract(process.env.SGAI_APIKEY!, {
-    url: 'https://stripe.com',
-    prompt: 'Extract all content from this page',
+const scrapeResult = await smartScraper(apiKey, {
+    website_url: 'https://stripe.com',
+    user_prompt: 'Extract all content from this page',
 });
-const data = result.data?.json;
 
 const prompt = `Extract company information from this website content.
 
@@ -135,7 +135,7 @@ Output ONLY valid JSON in this exact format (no markdown, no explanation):
 }
 
 Website content:
-${JSON.stringify(data)}`;
+${JSON.stringify(scrapeResult.data.result)}`;
 
 const message = await anthropic.messages.create({
     model: 'claude-haiku-4-5',

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

@@ -27,22 +27,22 @@ 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 { extract } from 'scrapegraph-js';
+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 result = await extract(process.env.SGAI_APIKEY!, {
-    url: 'https://scrapegraphai.com',
-    prompt: 'Extract all content from this page',
+const scrapeResult = await smartScraper(apiKey, {
+    website_url: 'https://scrapegraphai.com',
+    user_prompt: 'Extract all content from this page',
 });
-const data = result.data?.json;
 
-console.log('Scraped content length:', JSON.stringify(data).length);
+console.log('Scraped content length:', JSON.stringify(scrapeResult.data.result).length);
 
 const response = await ai.models.generateContent({
     model: 'gemini-2.5-flash',
-    contents: `Summarize: ${JSON.stringify(data)}`,
+    contents: `Summarize: ${JSON.stringify(scrapeResult.data.result)}`,
 });
 
 console.log('Summary:', response.text);
@@ -53,26 +53,26 @@ console.log('Summary:', response.text);
 This example shows how to analyze website content using Gemini's multi-turn conversation capabilities.
 
 ```typescript
-import { extract } from 'scrapegraph-js';
+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 result = await extract(process.env.SGAI_APIKEY!, {
-    url: 'https://news.ycombinator.com/',
-    prompt: 'Extract all content from this page',
+const scrapeResult = await smartScraper(apiKey, {
+    website_url: 'https://news.ycombinator.com/',
+    user_prompt: 'Extract all content from this page',
 });
-const data = result.data?.json;
 
-console.log('Scraped content length:', JSON.stringify(data).length);
+console.log('Scraped content length:', JSON.stringify(scrapeResult.data.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${JSON.stringify(data)}`
+    message: `Based on this website content from Hacker News, what are the top 3 stories right now?\n\n${JSON.stringify(scrapeResult.data.result)}`
 });
 console.log('Top 3 Stories:', result1.text);
 
@@ -88,22 +88,22 @@ 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 { extract } from 'scrapegraph-js';
+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 result = await extract(process.env.SGAI_APIKEY!, {
-    url: 'https://stripe.com',
-    prompt: 'Extract all content from this page',
+const scrapeResult = await smartScraper(apiKey, {
+    website_url: 'https://stripe.com',
+    user_prompt: 'Extract all content from this page',
 });
-const data = result.data?.json;
 
-console.log('Scraped content length:', JSON.stringify(data).length);
+console.log('Scraped content length:', JSON.stringify(scrapeResult.data.result).length);
 
 const response = await ai.models.generateContent({
     model: 'gemini-2.5-flash',
-    contents: `Extract company information: ${JSON.stringify(data)}`,
+    contents: `Extract company information: ${JSON.stringify(scrapeResult.data.result)}`,
     config: {
         responseMimeType: 'application/json',
         responseSchema: {