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RAG & Knowledge Systems

Reader

Reader is a web-reading and search service that converts URLs and search-result pages into LLM-friendly content for language models, agents and retrieval-augmented generation systems.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Reader — OpenViST project profile in RAG & Knowledge Systems.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Reader when an AI workflow needs processed page content from a URL, or when a web-search step should return retrieved result-page content rather than only search-engine snippets.

Who it is for

  • Developers building LLM or RAG applications that need page content as input.
  • Agent builders who want a web-search step that retrieves content from result pages.
  • Teams preparing web pages, PDFs, Office documents or image descriptions for text-based AI workflows.

Documented uses

  • Convert a page URL into content an LLM can process.
  • Search the web and retrieve content from the top five result pages.
  • Prepare supported documents and images as text-oriented material for downstream models.
  • Choose among documented response formats such as Markdown, HTML, text or screenshot.
Before you choose

Requirements & limits

The repository describes the Read and Search services as free to use and points to a rate-limit page; consult that page for current limits. The public repository is licensed under Apache-2.0.

  • Read handles a supplied URL; Search accepts a query and fetches content from the top five results.
  • Supported inputs include web pages, PDFs, Word, Excel and PowerPoint documents, and images.
  • Page handling may use headless Chrome or curl-impersonate; PDFs use PDF.js, Office files use LibreOffice, and images are captioned by a vision-language model.
  • The API offers multiple response formats through request headers.
  • The open-source repository runs statelessly and describes optional MinIO or S3-compatible bucket caching; its MongoDB-backed SaaS storage layer is excluded.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Search the web and retrieve result-page content

Get search results with content fetched from the top five result pages.

Before you start

  • A search query.
  • A browser or HTTP client that can request a URL-encoded query.

Steps

  1. URL-encode the search query.

  2. Place it after https://s.jina.ai/.

  3. Request the resulting URL to receive the search response and processed content from the top five result pages.

Expected outcome

Reader returns search results with content from the pages it visits, rather than only search-engine titles, URLs and descriptions.

Guide limitations

  • The described flow fetches the top five results; the source does not specify controls for changing that count.
  • For code requests, the query must be URL-encoded.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
7 October 2026
Original website title
jina-ai/reader · Official homepage title · retained in its source language
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