PDF Text Extractor 📄

Turn any PDF into clean, structured text and metadata.

Give it PDF URLs and get back the full text, per-page text, and document metadata (title, author, page count, dates, producer) — clean and ready for AI/RAG pipelines, search, and data extraction. Fast, serverless and no code required.

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⚡ At a glance

📝 Full text	Clean plain text from the whole document
📑 Per-page text	Optional page-by-page array for chunking
🏷️ Metadata	Title, author, page count, dates, producer
🤖 AI/RAG ready	Feed text straight into LLMs & vector DBs
📦 Bulk	Process one PDF or thousands from a list
⚡ Fast	Pure code — no browser, no OCR needed
💾 Export	Excel, CSV, JSON or API

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📌 Why this Actor?

• 📝 Clean text extraction — the full document as readable plain text, with broken PDF spacing fixed.
• 📑 Per-page output — an optional pages array so you can chunk documents page-by-page for embeddings and RAG.
• 🏷️ Rich metadata — title, author, subject, keywords, creator, producer, creation & modification dates and page count.
• 🤖 Built for AI — structured JSON output that drops straight into LLM, embedding and search workflows.
• 📦 Bulk-friendly — pass a big list of PDF URLs and get one clean dataset back.

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✨ What you get (data fields)

Field	Description
text	Full extracted text (plain)
pages	Per-page text array (optional)
pageCount	Number of pages
wordCount	Extracted word count
title	Document title
author	Document author
subject	Document subject
keywords	Document keywords
creator	Creating application
producer	PDF producer
creationDate / modificationDate	Document dates
fileName	File name
fileSizeBytes	File size
url	Source URL
error	Set if extraction failed

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🚀 Quick start

1. Click Try for free / Start.
2. Add your PDF URLs — one per line:

   https://arxiv.org/pdf/1706.03762
   https://example.com/report.pdf
   

3. (Optional) Turn on Include per-page text for chunking, or set Max pages.
4. Click Save & Start, then export from the Dataset tab.

💡 Tip: Have a big list? Use PDF URLs from file / list to load thousands of URLs from a CSV or Google Sheet.

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🎯 Use cases

Use case	What it delivers
🤖 AI / RAG pipelines	Clean, chunked text ready for LLMs, embeddings and vector databases.
🔎 Document search	Index PDF content for full-text search.
📊 Data extraction	Pull text from reports, invoices, contracts and papers at scale.
📚 Research	Extract text from academic papers and whitepapers.
🗂️ Content migration	Convert PDF libraries into structured text.
🧾 Compliance & archiving	Turn document sets into searchable text records.

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⚙️ Input reference

Input	Type	Default	Description
PDF URLs	list	sample	PDF URLs to extract.
PDF URLs from file / list	list	—	Bulk-load URLs from a file or sheet.
Include per-page text	boolean	false	Add a pages array.
Include document metadata	boolean	true	Extract title, author, dates, etc.
Max pages per PDF	number	0	0 = all pages.
Download timeout (seconds)	number	60	Per-PDF download timeout.
Proxy / concurrency	—	Datacenter / 5	Sensible defaults.

📥 Example input

{
  "pdfUrls": ["https://arxiv.org/pdf/1706.03762"],
  "splitPages": true,
  "includeMetadata": true,
  "maxPages": 0
}

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📤 Example output

{
  "url": "https://arxiv.org/pdf/1706.03762",
  "fileName": "1706.03762",
  "fileSizeBytes": 2215244,
  "pageCount": 15,
  "wordCount": 8231,
  "title": "Attention Is All You Need",
  "author": "",
  "producer": "pdfTeX-1.40.25",
  "creationDate": "2024-04-10T21:11:43.000Z",
  "text": "Provided proper attribution is provided, Google hereby grants permission to reproduce…",
  "pages": ["…page 1 text…", "…page 2 text…"],
  "scrapedAt": "2026-07-25T10:00:00.000Z"
}

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💡 Tips & best practices

• ✅ Use splitPages for AI/RAG — page-by-page text is easy to chunk and embed.
• ✅ Cap maxPages for very large documents when you only need the first pages.
• ✅ Bulk-load URLs from a file to process large libraries.
• ✅ Check the error field to spot any URLs that weren't valid PDFs.
• ✅ Scale concurrency for big batches.

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❓ FAQ

What kinds of PDF work? Text-based (digitally created) PDFs. Scanned/image-only PDFs have no embedded text layer, so they return no text (OCR is not performed).

Can I get per-page text? Yes — turn on Include per-page text to add a pages array.

Can I extract metadata? Yes — title, author, subject, keywords, creator, producer and dates are included by default.

Do I need to code? No. Add PDF URLs, click Start, export.

In what format is the data? Structured JSON by default, exportable to CSV, Excel, HTML or via API.

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📊 Output & integrations

Results are stored in a standard Apify dataset — preview as a table, export to JSON, CSV, Excel, HTML, pull via the API, or push to Google Sheets, Make, Zapier and more.

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⚖️ Legal & responsible use

This Actor extracts text from PDFs you provide.

• Ensure you have the right to download and process each document.
• Respect copyright and the terms under which documents are published.
• You are responsible for how you use the extracted data.

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🛟 Support

Found a bug, need an extra field, or want a tweak? Open an issue on the Actor's Issues tab.

Happy extracting! 📄