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Document to Markdown: PDF, DOCX & HTML for RAG

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Convert PDF, Word (DOCX), HTML pages, CSV and text into clean Markdown + JSON for LLMs and RAG: headings, tables, links, metadata and ready-to-embed chunks with heading paths and page numbers. URLs, Drive/Dropbox links or base64. No OCR, no AI cost.

Pricing

from $1.00 / 1,000 pages

Rating

0.0

(0)

Developer

Dodi Abak

Actor stats

Bookmarked

Total users

Monthly active users

5 days ago

Last modified

Categories

You can access the Document to Markdown: PDF, DOCX & HTML for RAG programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1import { ApifyClient } from 'apify-client';
2
3// Initialize the ApifyClient with your Apify API token
4// Replace the '<YOUR_API_TOKEN>' with your token
5const client = new ApifyClient({
6    token: '<YOUR_API_TOKEN>',
7});
8
9// Prepare Actor input
10const input = {
11    "sources": [
12        {
13            "url": "https://arxiv.org/pdf/1706.03762v7"
14        },
15        {
16            "url": "https://en.wikipedia.org/wiki/Markdown"
17        },
18        {
19            "html": "<h1>Price list</h1><p>Valid from <b>1 May</b>.</p><table><tr><th>Plan</th><th>Price</th></tr><tr><td>Basic</td><td>$9</td></tr><tr><td>Pro</td><td>$29</td></tr></table>",
20            "id": "inline-html-example"
21        }
22    ]
23};
24
25// Run the Actor and wait for it to finish
26const run = await client.actor("dodiabak/document-to-markdown").call(input);
27
28// Fetch and print Actor results from the run's dataset (if any)
29console.log('Results from dataset');
30console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
31const { items } = await client.dataset(run.defaultDatasetId).listItems();
32items.forEach((item) => {
33    console.dir(item);
34});
35
36// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

PDF to Markdown API: DOCX & HTML for LLMs & RAG API in JavaScript

The Apify API client for JavaScript is the official library that allows you to use Document to Markdown: PDF, DOCX & HTML for RAG API in JavaScript or TypeScript, providing convenience functions and automatic retries on errors.

Install the apify-client

$npm install apify-client

Other API clients include:

Document to Markdown: PDF, DOCX & HTML for RAG API in Python

Document to Markdown: PDF, DOCX & HTML for RAG API through CLI

Document to Markdown: PDF, DOCX & HTML for RAG OpenAPI definition

Document to Markdown: PDF, DOCX & HTML for RAG API

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🚀 Transform web content into clean, LLM-ready Markdown! 📘 Scrape multiple pages, extract main content, and convert to Markdown format. Perfect for AI researchers, data scientists, and LLM developers. Fast, efficient, and customizable. Supercharge your AI training data today! 🌐📝🧠

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Web-to-Markdown Generator for AI & RAG Pipelines

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Convert any website into clean, heading-based chunking, LLM-ready Markdown for RAG and AI agents.

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Website Content Extractor for RAG: Markdown, HTML, Text

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Turn docs sites, help centers, blogs, and websites into clean markdown, text, or HTML for RAG, AI knowledge bases, and internal search. Crawl from start URLs or sitemaps and keep the crawl in scope.

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Document to Markdown Converter for RAG

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Convert PDF, DOCX, XLSX, PPTX, HTML and EPUB links to clean Markdown or RAG-ready chunks. No OCR, no browser. $4 per 1,000 documents plus page fees.

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Document Parser — PDF/DOCX to Markdown & JSON for RAG

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Convert PDF, DOCX, PPTX, XLSX, HTML and images into clean Markdown or JSON for RAG and LLM pipelines. Powered by IBM's open-source Docling.

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Doc2RAG AI - Documentation to LLM-Ready Markdown Converter

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Convert technical documentation websites (Stripe, Supabase, Next.js, Mintlify, Docusaurus) into clean, LLM-ready Markdown with preserved multi-language code blocks, tables, and RAG frontmatter. Exports JSON dataset, single llms-full.txt, and ZIP archive.