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Document QA Prep — Chunked Text Splitter
x402
Document QA Prep — Chunked Text Splitter is a paid API for AI agents from the-stall.intuitek.ai, paid per call via x402, $0.194/call, status unknown (last checked 2026-09-13).
Splits a document into overlapping token-sized chunks suitable for retrieval-augmented generation (RAG) and question-answering pipelines
Price / call$0.194
Success—
StatusUnknown
How this service works
Prepares a document for question-answering and RAG pipelines. Chunks the input text at paragraph/sentence boundaries, assigns deterministic chunk IDs, estimates token counts, and extracts document metadata (word count, type, headings). Returns ready-to-embed chunks with overlap support. No LLM or external API — pure text processing. Use mid-task when you've fetched a document and need it split before querying a vector store.
Output
Returns an ordered array of text chunks derived from the input document, each sized to the requested token window (default 512 tokens) with the specified token overlap (default 50) between consecutive chunks, plus any metadata key-value pairs attached to every chunk. Also includes token count estimates per chunk.
Example use cases
Example prompt
“Chunk this 10,000-word research article into 512-token segments with a 50-token overlap so I can embed them into a vector database — here's the full plain text: [document text]. Tag each chunk with source_url: 'https://example.com/research.pdf'.”
Technical details
Endpoint
GEThttps://the-stall.intuitek.ai/cap/document-qa-prepWhen to prefer
Choose this endpoint when you need to preprocess raw text (plain text, Markdown, or lightly structured prose) into token-sized overlapping chunks ready for embedding or RAG pipelines, especially when you want configurable chunk size and overlap and optional metadata tagging — all without managing API keys, paid via USDC microtransaction on Base.
Side effects
- text field missing or empty — returns 400 validation error
- text exceeds 500,000 character limit — returns 413 or validation error
- chunk_size_tokens exceeds max of 4096 — returns 400
- overlap_tokens exceeds max of 512 — returns 400
- Payment not provided or insufficient USDC — returns HTTP 402
- Network timeout on very large documents near the character limit
Input
{
"input": {
"type": "http",
"method": "GET",
"queryParams": {
"text": "Artificial intelligence is transforming industries by automating complex tasks and enabling data-driven decision making. Machine learning models can process vast amounts of information to identify patterns and generate insights. Natural language processing allows computers to understand and generate human language. Computer vision enables machines to interpret visual information from images and videos. These technologies are being applied in healthcare, finance, manufacturing, and many other sectors to improve efficiency and create new opportunities."
}
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| required | string | |
| properties | string |
Output
{
"chunks": [
{
"id": "1fsjdog",
"text": "Artificial intelligence is transforming industries by automating complex tasks and enabling data-driven decision making. Machine learning models can process vast amounts of information to identify patterns and generate insights. Natural language processing allows computers to understand and generate human language. Computer vision enables machines to interpret visual information from images and videos. These technologies are being applied in healthcare, finance, manufacturing, and many other sectors to improve efficiency and create new opportunities.",
"index": 0,
"char_count": 556,
"token_estimate": 139
}
],
"chunk_count": 1,
"generated_at": "2026-06-12T05:11:41.140Z",
"overlap_tokens": 50,
"avg_chunk_tokens": 139,
"chunk_size_target": 512,
"document_metadata": {
"doc_type": "text",
"headings": [],
"char_count": 556,
"line_count": 1,
"word_count": 72,
"language_hint": "en",
"estimated_tokens": 139
}
}Tags
x402
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