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AgentWork PDF Text Extraction
x402
AgentWork PDF Text Extraction is a paid API for AI agents from api.agentwork.run, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).
Extracts embedded text from a public PDF URL into page-numbered JSON, including SHA-256 hashes and warnings, for RAG pipelines and document ingestion.
Price / call$0.01
Success—
StatusUnknown
How this service works
PDF text extraction — extract text from a public digital PDF into page-numbered JSON for RAG (no OCR). $0.01 USDC Base or Algorand. Caps 20 pages / 5 MiB / 100k chars; source + text SHA-256. No passwords or table reconstruction. Failed extractions not settled.
Output
A JSON object with ok status, the full extracted text as a single string, an array of page objects each containing page number, page text, and character count, plus page_count, ocr_performed flag (always false), source and text SHA-256 hashes, and a warnings array flagging empty pages or truncation if the document exceeds 20 pages, 5 MiB, or 100,000 characters.
Example use cases
RAG pipeline document ingestion
“I need to ingest this public PDF into my RAG system — can you pull out all the embedded text from https://arxiv.org/pdf/2301.00001.pdf and return it organized by page so I can chunk and embed it?”
Research paper content extraction
“Can you read the full text of this research paper PDF at https://example.com/whitepaper.pdf and give me all the content page by page, including any warnings if some pages are empty?”
Contract text retrieval for analysis
“I have a contract at https://company.com/contracts/agreement.pdf — please extract all the text from it with page numbers so I can search through the clauses.”
Technical details
Endpoint
GEThttps://api.agentwork.run/v1/pdf/read?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need reliable, page-numbered plain-text extraction from a digitally-created (not scanned) public PDF for downstream RAG, search indexing, or document analysis. It is ideal when you need SHA-256 hashes for deduplication or change detection, and when you do not need OCR, table reconstruction, or image understanding. Prefer this over general web scrapers when your source is specifically a PDF file.
Side effects
- PDF is password-protected — extraction fails and no charge is made
- URL is not publicly accessible or requires authentication — request rejected
- PDF contains only scanned images with no embedded text — returns empty or near-empty pages with warnings
- Document exceeds 20 pages, 5 MiB, or 100,000 characters — content is truncated with a warning
- URL points to a non-PDF resource — extraction fails
- Network timeout or unreachable URL — extraction fails with no settlement
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"text": "Dummy PDF file",
"pages": [
{
"page": 1,
"text": "Dummy PDF file",
"characters": 14
}
],
"warnings": [
"Embedded text only; images and table structure are not extracted."
],
"page_count": 1,
"ocr_performed": false
}
}Tags
x402
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