📚 This is an adapted version of Jina AI's Reader for local deployment using Docker. Convert any URL to an LLM-friendly input with a simple prefix http://127.0.0.1:3000/https://website-to-scrape.com/
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Reader Clone which is deployable locally!

  • Jina.ai 's reader API helps get better output from LLMs by converting URLs to LLM-friendly input. Though the version hosted on github cannot really be used by 3rd parties as it depends on multiple internal packages. This repo is a clone of the reader API without any of the internal dependencies which you can run locally and self-host.

Install and Setup

You will need the following tools to run the project:

  • Node v18 (The build fails for Node version >18)
  • Firebase CLI (npm install -g firebase-tools)

To set up the project:

  1. Clone the repository:

    git clone git@github.com:hargup/reader.git
    
  2. Navigate to the backend functions directory:

    cd reader/backend/functions
    
  3. Install the npm dependencies:

    npm install
    

Usage

To run the express service:

  1. In the backend/functions directory, start the service using nodemon:

    npx nodemon --watch ./src --exec "npm run build && node build/server.js"
    
  2. Once the service is running, you can use curl to make requests. For example:

    curl -H "X-Respond-With: markdown" http://localhost:3000/https://example.com
    

This will fetch the content from https://example.com and return it in markdown format.

You can customize the request by changing the X-Respond-With header to other supported formats like html, text, screenshot, or pageshot.


Reader

Your LLMs deserve better input.

Reader does two things:

  • Read: It converts any URL to an LLM-friendly input with https://r.jina.ai/https://your.url. Get improved output for your agent and RAG systems at no cost.
  • Search: It searches the web for a given query with https://s.jina.ai/your+query. This allows your LLMs to access the latest world knowledge from the web.

Check out the live demo

Or just visit these URLs (Read) https://r.jina.ai/https://github.com/jina-ai/reader, (Search) https://s.jina.ai/Who%20will%20win%202024%20US%20presidential%20election%3F and see yourself.

Feel free to use Reader API in production. It is free, stable and scalable. We are maintaining it actively as one of the core products of Jina AI. Check out rate limit

image image

Updates

  • 2024-07-15: To restrict the results of s.jina.ai to certain domain/website, you can set e.g. site=jina.ai in the query parameters, which enables in-site search. For more options, try our updated live-demo.
  • 2024-07-01: We have resolved a DDoS attack and other traffic abusing since June 27th. We also found a bug introduced on June 28th which may cause higher latency for some websites. The attack and the bug have been solved; if you have experienced high latency of r.jina.ai between June 27th-30th, it should back to normal now.
  • 2024-05-30: Reader can now read abitrary PDF from any URL! Check out this PDF result from NASA.gov vs the original.
  • 2024-05-15: We introduced a new endpoint s.jina.ai that searches on the web and return top-5 results, each in a LLM-friendly format. Read more about this new feature here.
  • 2024-05-08: Image caption is off by default for better latency. To turn it on, set x-with-generated-alt: true in the request header.
  • 2024-05-03: We finally resolved a DDoS attack since April 29th. Now our API is much more reliable and scalable than ever!
  • 2024-04-24: You now have more fine-grained control over Reader API using headers, e.g. forwarding cookies, using HTTP proxy.
  • 2024-04-15: Reader now supports image reading! It captions all images at the specified URL and adds Image [idx]: [caption] as an alt tag (if they initially lack one). This enables downstream LLMs to interact with the images in reasoning, summarizing etc. See example here.

Usage

Using r.jina.ai for single URL fetching

Simply prepend https://r.jina.ai/ to any URL. For example, to convert the URL https://en.wikipedia.org/wiki/Artificial_intelligence to an LLM-friendly input, use the following URL:

https://r.jina.ai/https://en.wikipedia.org/wiki/Artificial_intelligence

Using r.jina.ai for a full website fetching (Google Colab)

Simply prepend https://s.jina.ai/ to your search query. Note that if you are using this in the code, make sure to encode your search query first, e.g. if your query is Who will win 2024 US presidential election? then your url should look like:

https://s.jina.ai/Who%20will%20win%202024%20US%20presidential%20election%3F

Behind the scenes, Reader searches the web, fetches the top 5 results, visits each URL, and applies r.jina.ai to it. This is different from many web search function-calling in agent/RAG frameworks, which often return only the title, URL, and description provided by the search engine API. If you want to read one result more deeply, you have to fetch the content yourself from that URL. With Reader, http://s.jina.ai automatically fetches the content from the top 5 search result URLs for you (reusing the tech stack behind http://r.jina.ai). This means you don't have to handle browser rendering, blocking, or any issues related to JavaScript and CSS yourself.

Simply specify site in the query parameters such as:

curl 'https://s.jina.ai/When%20was%20Jina%20AI%20founded%3F?site=jina.ai&site=github.com'

Interactive Code Snippet Builder

We highly recommend using the code builder to explore different parameter combinations of the Reader API.

image

Using request headers

As you have already seen above, one can control the behavior of the Reader API using request headers. Here is a complete list of supported headers.

  • You can enable the image caption feature via the x-with-generated-alt: true header.
  • You can ask the Reader API to forward cookies settings via the x-set-cookie header.
    • Note that requests with cookies will not be cached.
  • You can bypass readability filtering via the x-respond-with header, specifically:
    • x-respond-with: markdown returns markdown without going through reability
    • x-respond-with: html returns documentElement.outerHTML
    • x-respond-with: text returns document.body.innerText
    • x-respond-with: screenshot returns the URL of the webpage's screenshot
  • You can specify a proxy server via the x-proxy-url header.
  • You can customize cache tolerance via the x-cache-tolerance header (integer in seconds).
  • You can bypass the cached page (lifetime 3600s) via the x-no-cache: true header (equivalent of x-cache-tolerance: 0).
  • If you already know the HTML structure of your target page, you may specify x-target-selector or x-wait-for-selector to direct the Reader API to focus on a specific part of the page.
    • By setting x-target-selector header to a CSS selector, the Reader API return the content within the matched element, instead of the full HTML. Setting this header is useful when the automatic content extraction fails to capture the desired content and you can manually select the correct target.
    • By setting x-wait-for-selector header to a CSS selector, the Reader API will wait until the matched element is rendered before returning the content. If you already specified x-wait-for-selector, this header can be omitted if you plan to wait for the same element.

Using r.jina.ai for single page application (SPA) fetching

Many websites nowadays rely on JavaScript frameworks and client-side rendering. Usually known as Single Page Application (SPA). Thanks to Puppeteer and headless Chrome browser, Reader natively supports fetching these websites. However, due to specific approach some SPA are developed, there may be some extra precautions to take.

SPAs with hash-based routing

By definition of the web standards, content come after # in a URL is not sent to the server. To mitigate this issue, use POST method with url parameter in body.

curl -X POST 'https://r.jina.ai/' -d 'url=https://example.com/#/route' 

SPAs with preloading contents

Some SPAs, or even some websites that are not strictly SPAs, may show preload contents before later loading the main content dynamically. In this case, Reader may be capturing the preload content instead of the main content. To mitigate this issue, here are some possible solutions:

Specifying x-timeout

When timeout is explicitly specified, Reader will not attempt to return early and will wait for network idle until the timeout is reached. This is useful when the target website will eventually come to a network idle.

curl 'https://example.com/' -H 'x-timeout: 30'
Specifying x-wait-for-selector

When wait-for-selector is explicitly specified, Reader will wait for the appearance of the specified CSS selector until timeout is reached. This is useful when you know exactly what element to wait for.

curl 'https://example.com/' -H 'x-wait-for-selector: #content'

Streaming mode

Streaming mode is useful when you find that the standard mode provides an incomplete result. This is because the Reader will wait a bit longer until the page is stablely rendered. Use the accept-header to toggle the streaming mode:

curl -H "Accept: text/event-stream" https://r.jina.ai/https://en.m.wikipedia.org/wiki/Main_Page

The data comes in a stream; each subsequent chunk contains more complete information. The last chunk should provide the most complete and final result. If you come from LLMs, please note that it is a different behavior than the LLMs' text-generation streaming.

For example, compare these two curl commands below. You can see streaming one gives you complete information at last, whereas standard mode does not. This is because the content loading on this particular site is triggered by some js after the page is fully loaded, and standard mode returns the page "too soon".

curl -H 'x-no-cache: true' https://access.redhat.com/security/cve/CVE-2023-45853
curl -H "Accept: text/event-stream" -H 'x-no-cache: true' https://r.jina.ai/https://access.redhat.com/security/cve/CVE-2023-45853

Note: -H 'x-no-cache: true' is used only for demonstration purposes to bypass the cache.

Streaming mode is also useful if your downstream LLM/agent system requires immediate content delivery or needs to process data in chunks to interleave I/O and LLM processing times. This allows for quicker access and more efficient data handling:

Reader API:  streamContent1 ----> streamContent2 ----> streamContent3 ---> ... 
                          |                    |                     |
                          v                    |                     |
Your LLM:                 LLM(streamContent1)  |                     |
                                               v                     |
                                               LLM(streamContent2)   |
                                                                     v
                                                                     LLM(streamContent3)

Note that in terms of completeness: ... > streamContent3 > streamContent2 > streamContent1, each subsequent chunk contains more complete information.

JSON mode

This is still very early and the result is not really a "useful" JSON. It contains three fields url, title and content only. Nonetheless, you can use accept-header to control the output format:

curl -H "Accept: application/json" https://r.jina.ai/https://en.m.wikipedia.org/wiki/Main_Page

JSON mode is probably more useful in s.jina.ai than r.jina.ai. For s.jina.ai with JSON mode, it returns 5 results in a list, each in the structure of {'title', 'content', 'url'}.

Generated alt

All images in that page that lack alt tag can be auto-captioned by a VLM (vision langauge model) and formatted as !(Image [idx]: [VLM_caption])[img_URL]. This should give your downstream text-only LLM just enough hints to include those images into reasoning, selecting, and summarization. Use the x-with-generated-alt header to toggle the streaming mode:

curl -H "X-With-Generated-Alt: true" https://r.jina.ai/https://en.m.wikipedia.org/wiki/Main_Page

License

Apache-2.0