PDF to Markdown: DOCX, PPTX, XLSX, OCR & RAG Chunks

Convert PDF, DOCX, PPTX, XLSX and HTML files into clean Markdown and heading-aware RAG chunks, with optional OCR for scanned PDFs. The output is GitHub-flavored Markdown with headings, pipe tables and page markers kept, and each chunk is tagged with source, page and section, ready for an embedding model or vector store. OCR uses Tesseract (English only) and is off by default. Conversion runs inside the Actor on open-source libraries, with no paid parsing APIs. You pay per successful document, and failed documents are free.

Features

• Formats: PDF, DOCX, PPTX, XLSX, HTML, plus PNG/JPEG/TIFF/WebP when OCR is on
• Sources: URL list, Console file upload, or an existing Apify key-value store
• Tables and headings as | pipe tables and ATX # headings
• Page markers in the Markdown (<!-- page:3 -->) so you can cite a page
• Quality modes
  • auto (default) — MarkItDown for office/HTML, PyMuPDF for born-digital PDFs
  • fast — the same Fast converters
  • accurate — Docling layout and table reconstruction if Docling is installed in the image. This Store build does not include Docling, so Accurate falls back to Fast and still returns Markdown
• OCR off by default. English only (eng)
• RAG chunking — configurable size / overlap, heading-aware, tables kept whole
• Per-document errors — one corrupt file does not fail the run
• Size, page, and timeout caps so a huge upload cannot blow the run

What’s new in 1.1.0

Titles come from PDF metadata or the first real heading, never a page marker like <!-- page:1 -->. PDF tables keep multi-level headers and colspans (no more BL|EU splits). Math decimals such as 0 _._ 1 are cleaned to 0.1.

Input

Provide at least one of: document URLs, uploaded files, or a key-value store.

Field	Default	What it does
startUrls	(prefilled example PDF)	HTTP(S) links to documents or HTML pages
files	—	Console file upload (PDF / Office / HTML)
keyValueStoreId + keyValueStoreKeys	—	Read records from an existing store. Empty keys = every supported record
quality	auto	auto / fast / accurate (Accurate falls back to Fast on this build)
enableOcr	false	Tesseract on pages with no text layer
ocrLanguage	eng	English only on this build
enableChunking	true	Build RAG chunks
chunkSize	1000	Target characters per chunk
chunkOverlap	150	Overlap between windows
headingAware	true	Split on heading changes; store heading path as section
pushChunksAsItems	false	Also emit one dataset row per chunk
saveMarkdownToKvs	true	Write document-*.md files to the default key-value store
maxFileSizeMb	50	Skip oversized files
maxPages	100	PDF pages / PPTX slides / XLSX sheets
timeoutSeconds	300	Per-document timeout
maxDocuments	50	Cap sources in input order

Example input

{
    "startUrls": [
        { "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" },
        { "url": "https://example.com" }
    ],
    "quality": "auto",
    "enableOcr": false,
    "enableChunking": true,
    "chunkSize": 1000,
    "chunkOverlap": 150
}

Output

Each document becomes one dataset item. Failed files become status: "error" rows with an error message; the run continues.

{
    "type": "document",
    "status": "success",
    "source": "https://example.com/report.pdf",
    "sourceType": "url",
    "format": "pdf",
    "title": "Annual Report",
    "markdown": "<!-- page:1 -->\n\n# Annual Report\n\n| Metric | 2025 |\n| --- | --- |\n| Revenue | 14 |\n",
    "markdownKey": "document-report-1.md",
    "pageCount": 12,
    "ocrPages": 0,
    "converter": "pymupdf4llm",
    "chunkCount": 8,
    "chunks": [
        {
            "text": "# Annual Report\n\n...",
            "source": "https://example.com/report.pdf",
            "page": 1,
            "section": "Annual Report > Financials",
            "chunkIndex": 0,
            "startChar": 0,
            "endChar": 980
        }
    ]
}

When saveMarkdownToKvs is on, the same Markdown is also a downloadable key-value store record.

Pricing (pay-per-event)

Users pay only for these events — not extra platform usage on top.

Event	When it fires	Price
document-processed	Once per successful document (up to 10 pages)	$0.005
extra-page	Each page after the first 10	$0.001
ocr-page	Each page that actually ran OCR	$0.008

Failed documents are free.

Examples:

• 8-page DOCX, no OCR → $0.005
• 24-page PDF, no OCR → $0.005 + 14 × $0.001 = $0.019
• 12-page scanned PDF, all pages OCR’d → $0.005 + 2 × $0.001 + 12 × $0.008 = $0.103

Default run memory is 2048 MB. For OCR on many pages, raise the run to 4096 MB.

How it works

1. Download each source (URL, upload, or key-value store) with a streaming size cap.
2. Detect format from extension / Content-Type.
3. Convert:
   • Office & HTML → MarkItDown (HTML first goes through readability)
   • Born-digital PDF → PyMuPDF (Markdown tables, page markers)
   • Scanned PDF / image → Tesseract OCR when enableOcr is on (English)
   • quality=accurate → Docling when present, otherwise the Fast path above
4. Optionally chunk on headings, keeping pipe tables atomic.
5. Charge the events above, push the dataset row, save the .md file.

Limits

• Default 50 MB / 100 pages / 180 s / 50 documents per run — raise in input if you need more
• .doc / .ppt / .xls (legacy binary) are best-effort; prefer OOXML
• OCR is English only
• Accurate/Docling is not in this Store image; the Fast converter is used instead
• This Actor does not call Unstructured, Azure Document Intelligence, or any other paid parser

More actors from this developer

• Google Trends Scraper & API: Interest, Related, Trending: interest over time, by region, and related queries from Google Trends.
• Google News Scraper: Full-Text Articles to Markdown: Google News articles as Markdown and RAG chunks for any topic or company.
• Greenhouse, Lever, Ashby & Workable Jobs API: one clean jobs feed from company job boards, with salaries when posted.
• Website Screenshot & URL to PDF API (Bulk, Full Page): full-page and mobile screenshots (PNG, JPEG, WebP) and PDFs of any URL.
• Wayback Machine API: Snapshots & Archived Pages: every archived capture of a URL or domain, the snapshot closest to a date, and archived pages as Markdown.

License

MIT. Third-party libraries keep their own licenses (MIT MarkItDown, Apache-2.0 PyMuPDF, Apache-2.0 Tesseract).