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Task Relay PDF Text Extractor
x402
Task Relay PDF Text Extractor is a paid API for AI agents from task-relay-production.up.railway.app, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Fetches a public PDF URL and extracts text-layer content page by page, returning structured results with text, page counts, hashes, truncation flags, and warnings.
Price / call$0.01
Success—
StatusUnknown
How this service works
When a machine needs plain text from a public PDF URL for ingestion or indexing, Task Relay fetches the PDF and extracts text-layer content page by page into a statused result with text, page counts, hashes, truncation flags, and warnings. Text-layer extraction only; NO OCR; no summarization; scanned image-only PDFs may return status no_text.
Output
Returns a structured result containing: extraction status (e.g. success, no_text), extracted text content per page, total page count, content hash, truncation flags indicating if content was cut off, and any warnings (e.g. if the PDF is scanned image-only and has no text layer).
Example use cases
Research paper ingestion pipeline
“I need to pull the full text out of this academic paper PDF at https://arxiv.org/pdf/2301.00001 so I can index it in my search system — can you extract it page by page?”
Legal document text extraction
“Extract all the text from this public contract PDF at https://storage.example.com/contracts/lease-agreement.pdf so I can run keyword analysis on it.”
Financial report content indexing
“Fetch the annual report PDF at https://investor.acmecorp.com/2023-annual-report.pdf and give me the raw text with page counts so I can load it into our document store.”
Technical details
Endpoint
POSThttps://task-relay-production.up.railway.app/x402/pdf-textWhen to prefer
Choose this endpoint when you need to programmatically extract raw text from a publicly accessible PDF URL for downstream ingestion, indexing, or transformation workflows. It is specifically suited for text-layer PDFs (not scanned images) and returns structured metadata (page count, hash, truncation flags) alongside the text. Prefer this over generic scraping when the source is a PDF file and you need per-page structure and status signals.
Side effects
- PDF URL is not publicly accessible — returns an error or unreachable status
- PDF is a scanned image-only document with no text layer — returns status 'no_text'
- PDF is password-protected or encrypted — extraction fails
- PDF URL is malformed or does not point to a valid PDF — returns an error
- Text content exceeds size limits — truncation flag is set and partial text is returned
- Network timeout fetching the remote PDF URL
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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