Buy RAG Page Extractor.
Turn messy web pages into structured text and clean markdown for RAG pipelines without JS bloat.
Drop-In Integration Stage
OpenAPI 3.1 & Gateway Compatibleimport httpx
response = httpx.post(
"https://api.youstostore.com/v1/extractions",
headers={
"X-API-Key": "sk_live_your_key",
"Idempotency-Key": "extract-docs-v2"
},
json={
"url": "https://docs.example.com/api-reference",
"render": "auto",
"authorization_basis": "public_permitted"
}
)
result = response.json()
print(result["job_id"]) # poll GET /v1/extractions/{job_id}
print(result["status"]) # "queued"Developer Tier
Growth Tier
RECOMMENDEDEnterprise Tier
Clean web content for RAG, without running your own extraction stack
RAG Page Extractor converts authorized public HTTP and HTTPS pages into compact Markdown while removing common non-content elements. The asynchronous create-and-read API returns a canonical URL, a stable content hash, Markdown, and block-level provenance fields that help your team trace retained text and detect unchanged pages.
Engineering Pain & Fragility
Web pages are designed for browsers, not retrieval pipelines. Navigation, scripts, styles, footers, repeated chrome, and layout text can waste tokens and reduce the signal in a vector index. A basic HTML-to-text call may remove markup, but it rarely gives an ingestion team enough provenance to answer operational questions such as:
- Did the meaningful page content change since the last crawl?
- Which retained section produced a quoted answer?
- Can a failed or repeated job be retried safely?
- How do we stop a URL ingestion feature from reaching internal network targets?
- How do we enforce a clear authorization policy rather than quietly becoming a scraping platform?
Building this well means maintaining retrieval, parsing, browser isolation, SSRF defenses, redirect handling, idempotency, storage, and stable response contracts. RAG Page Extractor packages that workflow behind two authenticated endpoints.
What the API Solves
Submit a permitted public page and an explicit authorization basis. The service retrieves the page, strips common non-content elements, normalizes the retained text into Markdown, calculates SHA-256 content and block hashes, stores the result for later reads, and returns a job identifier.
You can also send the content hash from a previous extraction. If the normalized content is unchanged, the result can return `not_modified` with `markdown: null`, allowing your pipeline to skip unnecessary chunking and embedding work.
The request contract supports three authorization declarations: `owned`, `licensed`, and `public_permitted`. It also accepts a `render` preference of `auto`, `never`, or `always`. The current bounded implementation performs HTTP-first retrieval and content cleanup; browser-backed rendering is deployment-dependent and should be validated for your target pages before production use.
How it works. Step by step.
Submit an extraction.
Call `POST /v1/extractions` with the page URL, authorization basis, render preference, and optional `previous_content_hash`.
Receive a queued job.
A successful create returns HTTP `202` with a `job_id` and `status: queued`.
Read the result.
Call `GET /v1/extractions/{job_id}` with the same tenant-scoped API credentials.
Use the normalized output.
On success, index the Markdown and retain the content and block hashes alongside your chunks.
Skip unchanged content.
Supply the prior content hash during the next extraction. A `not_modified` result tells your pipeline not to re-embed the page.
Built for enterprise production standards.
Asynchronous create/read workflow for page ingestion.
Clean Markdown output that excludes common scripts, styles, navigation, footers, and `noscript` content.
Stable SHA-256 page and block hashes.
Optional previous-hash comparison with `not_modified` handling.
Provenance fields for DOM path and Markdown offsets.
Explicit ownership or permission declaration on every extraction.
API-key authentication and tenant-scoped resources.
Required idempotency for safe create retries.
Structured errors rather than leaked upstream bodies or stack traces.
Public-target validation designed to reject localhost and non-global network addresses.
Ideal use cases & engineering workflows.
RAG and search platform teams
Normalize owned documentation before chunking, embedding, and retrieval. Store hashes with source metadata so refresh jobs can avoid unchanged pages.
Developer-tool companies
Ingest public API references, guides, changelogs, and help content into an assistant or federated documentation search experience.
Knowledge operations teams
Create repeatable snapshots of permitted public knowledge pages without maintaining extraction heuristics inside every workflow.
AI product teams that need provenance
Keep source URL, offsets, DOM-path context, and hashes near indexed text so debugging does not end at an opaque text blob.
Content monitoring workflows
Use normalized content hashes to identify meaningful page changes while reducing noise from common page chrome.
Why buy instead of building internally?
A page fetch is easy. A controlled ingestion service is not. Internal implementations tend to accumulate one-off parsing rules, unsafe URL handling, brittle retry behavior, and jobs that silently duplicate work. Supporting rendered pages adds a browser runtime, resource caps, sandboxing, and cleanup. Supporting customer-facing ingestion adds tenant isolation, stable errors, retention decisions, and abuse controls.
RAG Page Extractor gives you a narrow API contract and a policy boundary from the start. Your team can focus on chunking, retrieval quality, and product behavior rather than maintaining a general-purpose crawler. Just as important, its limitations are explicit: the service processes authorized public pages and refuses to compete with target-site controls.
Security, privacy and operational integrity.
Customer data routes use `X-API-Key`. The production design specifies high-entropy keys, SHA-256 digests at rest, server-side tenant resolution, scope checks, and tenant-isolated resource reads. Cross-tenant resource identifiers should resolve as not found rather than revealing existence.
Public-target validation rejects localhost and resolved non-global addresses to reduce SSRF and internal-metadata risk. The production contract also calls for redirect limits, response-size limits, a browser execution cap, robots and site-policy controls, sandboxed rendering where used, and destruction of the raw browser profile after each job.
The specified service envelope is 120 creates per minute per tenant, up to 10 concurrent rendered jobs, up to 10 redirects, a 10 MiB response limit, and a 30-second browser cap. The bounded HTTP fetcher in the inspected implementation uses a smaller 2,000,000-byte page limit and does not follow redirects, so confirm deployed limits during onboarding.
The production data policy specifies encrypted normalized content and block provenance retained for seven days by default, content-hash and diff metadata for 30 days, and no cookie collection in the MVP. These are deployment requirements, not compliance certifications.
Architectural Scope & Production Boundaries
Questions & answers for engineering leads.
It is a controlled extraction API for public pages you own, license, or are permitted to process. It does not provide credentials, CAPTCHA solving, residential proxies, or techniques for bypassing access controls.
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