
In my previous post, I've proudly announced that:

> [I have] Added [hypothes.is](https://web.hypothes.is/) sidebar to the site.

Well, while technically it was true, practically I screwed it badly. To the point where it was not really usable.

## What is Hypothesis?

**TL;DR:** This sidebar on the right side of the page, hopefully somewhere there >>>

Upfront let me give a quick intro to what Hypothesis is. Hypothesis is an organization focused on delivering an open conversation layer for digital documents based on web annotation standard by [W3C Web Annotation Working Group](https://www.w3.org/annotation/).

As part of their effort, they work on [hypothes.is](https://web.hypothes.is/), which is an open-source (mainly 2 clause BSD) platform for web annotations. The main parts of the ecosystem are:

- _h_ - web service for annotations, it is backing whole ecosystem APIs.
- _client_ - web-based client for consuming and creating annotations. It can be used in a form of a browser extension or it can be directly embedded into a webpage by the author.
- integrations with different Learning Management Systems (big focus here) and Content Management Systems.

![Hypothesis client usage example on this page](/images/hypothesis-setup-client-example.png)
_Hypothesis client usage example on this page_

But what is the actual benefit of using Hypothesis? Let me cite their website:

> Using annotation, we enable sentence-level note taking or critique on top of classroom reading, news, blogs, scientific articles, books, terms of service, ballot initiatives, legislation and more.

Sounds great to me! Reviewing, commenting, taking notes on things with the capability of preserving precise context, seems like a proper way of doing online discourse.

Assuming that the client is still embedded by the time you are reading this, you can give it a try just now. Select any part of the text and you should see the annotator tooltip with "annotate" and "highlight" options.

![Hypothesis client Annotator tooltip](/images/hypothesis-setup-annotator-example.png)
_Hypothesis client Annotator tooltip_

## What went wrong?

In theory embedding Hypothesis client is dead simple:

> To add Hypothesis to your web site, simply add the following line to the HTML source of your page:
>
> `<script src="https://hypothes.is/embed.?js" async></script>`

So I did. But my site is Next.js based, so instead of HTML source I've edited my `BasicMeta.tsx` component:

```tsx
export default function BasicMeta([...]: Props) {
  return (
    <Head>
      [...]
      <script src="https://hypothes.is/embed.js" async></script>
    </Head>
  );
```

And boy, did I screw up badly! At first glance everything was fine, the client sidebar was displayed where it should be, and it was possible to annotate my webpage (I even tested it, created one annotation and checked if it was visible in Hypothesis API - it was). However, a few days later I have found that there is this little, little problem. Annotations were not persisted under correct URLs. For example I was able to see annotations I've made on my first post right on the welcome page. On the other hand, they were not present if I navigated directly to that post. How does that happen? Well, two things needs to be considered to answer that question.

The first one, is how my site is built. You see, _Next.js_ apps are kinda hybrid, the site is server-side generated for fast load time, but for the same reason, sub-sequential routing events can be handled on the client-side, with fetching only necessary data from the server as a `json`. Thanks to browser history API page address changes, data is rendered by React in a hydration process, but the page never reloads.

And this is where we are getting to the second factor: how Hypothesis client works. One of the core principles of web annotations is that they are meant for digital documents, and on the web those are identified by URLs. When the script is loaded, it retrieves the current page address, so it knows what annotations it should fetch and create. However, due to some technical complexity of tracking content changes, the client lacks proper support for SPAs and client-side routing. So it never knew that document changed when I navigated to the blog post from the welcome page. That is why annotations were persisted with wrong metadata and associated with a wrong URL.

## How to unscrew this?

Unfortunately, the Hypothesis client lacks APIs for interacting with it from a webpage level. This is not a bad thing per se, it probably helps to keep it simple and easier to maintain. So this is a design choice which needed to be overcome somehow.

The obvious solution is of course to unload the client manually and load it again when client-side routing happens. This approach has some drawbacks, the biggest one being probably that a lot of code and logic related to the client is unnecessary executed multiple times. Fortunately, I was not the first person to try that, and there were some bits of knowledge (to be humble it is not very popular technology) that I was able to find on the web. In the discussion under this [issue](https://github.com/hypothesis/product-backlog/issues/1135), [Matthew King](https://github.com/matt-e-king) points to this, slightly obsolete, [gist](https://gist.github.com/robertknight/b71af79a7dbe25712fad192e44bc6f5f), where [Robert Knight](https://github.com/robertknight) (one of the Hypothesis core developers) describes this approach as currently recommended one. There is also a comment by Robert to use code analogic to [this](https://github.com/hypothesis/browser-extension/blob/8c1548dda1c840016c0bbc876e051b6b1f4d810e/src/unload-client.js) to unload the client (which is why I called the gist slightly obsolete in the first place).

At this point the only missing part is how to tell when the client should be unloaded. This is where _Next.js_ [router](https://nextjs.org/docs/api-reference/next/router) kicks in. To get access to the router we can use the `useRouter()` _React_ hook. It exposes several events related to navigation on which it is possible to subscribe and perform custom logic.

Putting together everything mentioned above, I was able to implement this custom hook which I am calling in my `App` component:

```ts
import { useRouter } from "next/router";
import { useEffect } from "react";

/*
  React hook for unloading Hypothes.is client sidebar on Next.js router
  change. Allows loading client again with proper url if needed.

  Based on: https://github.com/hypothesis/browser-extension/blob/master/src/unload-client.js
*/
const useUnloadHypothesis = () => {
  const router = useRouter();
  useEffect(() => {
    const handleRouteChange = () => {
      const annotatorSelector = 'link[type="application/annotator+html"]';
      const annotatorLink = document.querySelector(annotatorSelector);
      if (annotatorLink) {
        annotatorLink.dispatchEvent(new Event("destroy"));
      }
    };
    router.events.on("routeChangeStart", handleRouteChange);
    // If the component is unmounted, unsubscribe
    // from the event with the `off` method:
    return () => {
      router.events.off("routeChangeStart", handleRouteChange);
    };
  }, []);
};

export default useUnloadHypothesis;
```

I have also decided that I want to embed Hypothesis only into posts pages. That is why I've created the new meta component which I include only in my post layout:

```ts
import Head from "next/head";

export default function HypothesisMeta() {
  return (
    <Head>
      <script src="https://hypothes.is/embed.js" async></script>
    </Head>
  );
}
```

So far it seems to be working just fine. Of course, it would be better if the client could handle history API changes by itself, but in the end, working around its limitations was not that hard.

PS. Try Hypothesis yourself!


Screwing up Hypothesis client setup


## TL;DR

Before publishing this post: Nothing at all.

After publishing this post: There is an article mentioning _DALL-E_ on this site.

## Hacker News - the root of all evil

There was a time when I was reading
[Hacker News](https://news.ycombinator.com/news) on regular basis but now I tend
to avoid it. Most of the time, when I was visiting it and checking all those shiny
projects and articles that people create, after a few moments of
excitement, I was ending (best case) a little melancholic about my own
achievements. So it was rather counterproductive to keep doing that. But
somehow I ended up there again last night (I was venting out some frustration
about Medium ~~comments~~ responses system in google search and one of the top
hits was HN).

And there it was - someone posted a link to _Open AI_'s
[DALL-E](https://openai.com/blog/dall-e/). And I was lost.

## DALL-E

So what is DALL-E? I will simply quote the article's introduction:

> DALL·E is a 12-billion parameter version of GPT-3 trained to generate images
> from text descriptions, using a dataset of text–image pairs. We’ve found that
> it has a diverse set of capabilities, including creating anthropomorphized
> versions of animals and objects, combining unrelated concepts in plausible
> ways, rendering text, and applying transformations to existing images.

My knowledge of generative networks never reached beyond simple GANNs and style
transfer (which is still better than my grasp on NLP). However, the article is
only 27 minutes read and not very detailed on a technical level, so it is
digestable for me. The most important thing though, are the examples of what
_DALL-E_ is capable of. It can generate:

> an illustration of a baby capybara in a wizard hat playing a guitar

and the results are great:

![DALL-E capybara example](/images/dall-e-capybara-example.png)
_Examples of DALL-E output for prompt shown above, all credit goes to Open AI_

I mean, come on! That is impressive.

Yet again, similar to the introduction
of GPT-3 architecture itself in May 2020, it makes you wonder when those models
will start replacing humans (poor me as a developer - it might seem like a joke,
but the fear is real). We should prompt some GPT-3 model to generate new
JavaScript frontend framework every week or so.

There was a vivid discussion on HN
([link here](https://news.ycombinator.com/item?id=25649557)) under the article.
Some clever points were made there. Some of them might give us, humans, some
hope for the near future. Here are those which appealed most to me:

- Some concepts probably are much more well-defined (overrepresented) in the
  training input set. And there is such possibility that those examples belong
  to those classes. And, same as the model itself, the dataset is huge, so it
  is not a surprise that you can find `anthropomorphized radish` there (search
  for `大根アニメ`, [click](https://www.google.com/search?q=%E5%A4%A7%E6%A0%B9%E3%82%A2%E3%83%8B%E3%83%A1)).
- It is a language model, so what it learns about is language (translation of
  written language to visual one in this case). It might not be as general as
  it is presented by researchers.
- The original _GPT-3_ model is 175 billion parameters (it is even hard to tell
  how _Open AI_ deploys it for training, heck even interference seems hard).
  I've read some claims that this is enough to encode around a third of the input
  data directly. With 12 billion parameters, _DALL-E_ is slightly thinner, but
  it is still big enough to be called enormous. So there are some controversies
  about reasoning capabilities of those transformer models. Do they reason or
  simply memorize the data? That would make them, very sophisticated and ML-based
  indeed, but only search algorithms (I know, exaggerating a little bit here ;) ).
- Black-box problem, which is becoming even more relevant with those models
  scaling more and more. We, humans, cannot reason about how the model works.
  We can't predict and explain why it made its decisions. It might work well in
  non-critical usages (creative work) but an unpredictable model is a no-go in
  many areas i.e. medicine or wealth management (sic!).
- Also, god only knows how processing-intensive training those transformers
  networks is, some people
  [claim](https://lambdalabs.com/blog/demystifying-gpt-3/) that for original
  _GPT-3_ it would be 355 years and a few million dollars. Better not dive into
  this topic, and not convert it to CO<sub>2</sub> tonnes equivalent.

Nevertheless, _DALL-E_ is still an IMPRESSIVE and TREMENDOUS work pushing both
natural language processing and image generation next step further.

I could probably go on and on, and try to write something about _Open AI's_
[CLIP](https://openai.com/blog/clip/) which was used in _DALL-E_'s training. Or
list some highlights about _DALL-E,_ so it doesn't seem that I am a bitter man
who can't admire the significance of this work (once again it is great). But it
is getting late (1:36 AM) so it would be probably good for me to get some sleep.

## So, what I am working on?

The whole _DALL-E_ thing was supposed to be just a short (kinda ironic) intro
from which I would move into site improvements that I am working on currently.
But again, it is getting late, so I will limit myself to listing them here:

- Added reading time (Medium like) information component to posts. But it is not
  yet populated with the correct value.
- Addition of some CSS theme mechanism to the template, so I don't need to
  remember what is hex for that gray color used in posts meta info.
- Added [hypothes.is](https://web.hypothes.is/) sidebar to the site. Found it
  accidentally during my Medium ~~comments~~ responses rage. Seems like a very
  nice concept so I've decided to give it a try.
- Read a little about SSR (funny how we, as industry, circled back to it) and web performance. Checked
  my site performance using
  [Lighthouse](https://developers.google.com/web/tools/lighthouse). Everything
  would be fine, except that adding hypothes.is sidebar gives huge performance
  penalty.

It is not rocket science nor transformer based deep learning algorithms. But
it is fun!


What have DALL-E and my site in common?

## Why was it made?

I was never good at writing nor I wanted to write. So why even bother with
personal website (for some reason I like that term better than blog)?
Well... because I can.

Maybe having a place like this will motivate me to work on some of my
side-projects (I will need something to write about, right?). Or maybe it will die like
most of those projects ;) Time will tell.

## How was it made?

I've read somewhere that it is a tradition to start a blog with a post
about building the site itself. Not sure if it is a real thing, it was some
random programmer's site (just like this one) and I never bothered to verify that.
Anyway, that will give me some volume for this first entry (though not much, things are pretty simple nowadays).

This page is git based and built with [Netlify](https://www.netlify.com/)
(lookup Jamstack if you are interested in more details).
It uses [nextjs-netlify-blog-template](https://github.com/wutali/nextjs-netlify-blog-template).

The process is as straightforward as possible:

1. Go to [nextjs-netlify-blog-template](https://github.com/wutali/nextjs-netlify-blog-template).
2. Click a "Deploy to Netlify" button (or follow this link directly to Netlify:
   [Deploy](https://app.netlify.com/start/deploy?repository=https://github.com/wutali/nextjs-netlify-blog-template&stack=cms)).
3. Connect Netlify to GitHub.
4. Provide repository name for the site and click "Save & Deploy" (template
   already configures Identity and Git Gateway services so they will be installed
   automatically).
5. Set up a domain (in my DNS provider configuration I added a `CNAME` record
   with `site` subdomain host and pointed it to my Netlify subdomain).
6. Do some cleanup of the template (remove default posts and tags).

And that is it.

Writing this paragraph took me many times longer than it took me to go through those
steps.

## Why was it made like that?

Despite working as a developer for quite some time already I had no previous
experience of creating a website all by myself. So my choices might be a little
random and whimsy. Things that led me to this decision (in random order):

* I think that server-side generated static site is a good fit for a personal
  site.
* I like Jamstack idea of git driven CMS (no backend API needed).
* As I work professionally with [Angular](https://angular.io/) lately, I
  decided that [React](https://reactjs.org/) based solution will be nice.
* I read some articles and watched some videos about
  [Next.js](https://nextjs.org/) and wanted to try it out.
* [Netlify](https://www.netlify.com/) was my first search result in Google and
  it has a free tier which should fit my needs for now.
* Medium seems like a go-to platform for blogging (or maybe it is not anymore)
  but I wanted a personal site not an account on yet another social... medium.
  Also, I might be adding something more than just blog posts (some online
  utils, apps), and it is nice to have such possibility out of the box.

I am not saying this is a perfect solution. Heck, it is probably far from optimal
or state of art. At some point I might change it to something else
(self/cloud-hosted?).

But in the end
[the point is not to catch a bunny, but to chase him, but to chase him, but to chase him](https://youtu.be/k2WtBpMkxz8).

Enjoy!

Jan

All posts / nextjs

Screwing up Hypothesis client setup

What have DALL-E and my site in common?

Welcome