As a WordPress user or reader, you might have noticed that some blogs and websites use a “More” block to break up their content and display a teaser of the post on the homepage or archive pages. This feature allows visitors to see a preview of the post and decide if they want to read more.
Personally, I enjoy adding “More” blocks to my posts, so that people that subscribe to email updates about blog posts, still have to visit the site to view the whole content. This helps me track actual interest in the posts, as they get page views.
In this blog post, we’ll explore how you can require a “More” block in your WordPress posts to improve user experience and engage your audience. 😊
As a developer, one of the most critical aspects of your workflow is the ability to test and preview your code changes before deploying them to production. This is where developer previews come in.
This post will outline how to create your own simple developer preview system, using Github Actions for building, AWS S3 for hosting, and Terraform to provision it all. Giving you more control, and a lower cost.
Shout out to Pedro Brandão from Significa whose post I read as inspiration for this setup.
What are Developer Previews?
Developer previews, also known as feature branches or pull request previews, allow developers to create isolated environments to test their changes without impacting the main production environment. It enables teams to collaborate, review, and validate code before merging it into the main branch. With developer previews, you can catch bugs, validate new features, and gather feedback early in the development process, ensuring a smoother deployment to production.
Existing services
Many dedicated platforms exist that offer developer preview as a service. These platforms provide a streamlined solution for creating and managing isolated environments for testing code changes. Examples of such services include Netlify’s Deploy Previews, Vercel’s Preview Deployments, and Heroku Review Apps. These platforms integrate seamlessly with popular version control systems and automatically deploy feature branches or pull requests, allowing developers to easily preview their changes. By leveraging these dev-preview services, developers can simplify the process of creating and managing preview environments, enabling faster iteration and effective collaboration within development teams.
However, all these services have a cost, which will always be higher than the do-it-yourself approach.
This entry is part 15 of 17 in the series Wikidata Map
It’s been 2 years since the 2021 Wikidata map. Yesterday I was sitting in the WMDE office and Lydia raised the point that we hadn’t made a map in quite some time (T331124).
Maps used to try to generate in a somewhat automated fashion, but the process was rewritten in 2021 and still needs to be run by hand with someone with access to the WMF analytics platform.
Thankfully the documentation of the updates still works perfectly, and the whole process of the map generation only took a few minutes!
I briefly touched on my OpenSSH agent to WSL2 solution back in 2021. Today find myself setting up a new Windows 11 laptop and running into a couple of different issues, and ultimately using a slightly different solution than before, so here is the short writeup glossing over the areas that lead me to get a little stuck, and hopefully outlining a good set of commands.
In my old .bashrc file, I found a comment linking me to the rupor-github/wsl-ssh-agent GitHub repository which was my first set of reading, specifically the WSL2 compatibility section. The main sticking issue for me out of the box was a miss match in the OpenSSH version between Windows and WSL2, with Windows starting on 8.6 but WSL2 with Ubuntu starting on 8.9. This lead to errors such as:
Error connecting to agent: No such file or directory
error fetching identities: invalid format
Could not open a connection to your authentication agent.
I planned on blogging being one of my relaxing hobbies while sailing around the Atlantic Ocean ⛵, and though we managed to keep a sailing blog up to date I found it extremely hard to write tech-related blogs while crossing oceans without a speedy or any internet connection.
The setting (of writing these blog posts) is rather beautiful, but to date, I have only written a single blog post when without a connection at all on this blog, now doubling that list to 2 with this post 🎉.
This was not because I didn’t have things that I wanted to write about, but rather that unless you are prepared well, there always seemed to be some element of my blog post writing process that would require access to something that is online and not on one of my local devices, or that only using local devices just ended up being a giant pain 🤦.
People might not want images from their websites to be indexed in online searches for several reasons.
To protect their intellectual property or copyrighted images from being copied or used without permission
To reduce the usage of the website (bandwidth) by people finding and using images
To help protect the privacy of those included in images
I have no problem with images from this blog appearing in search engines but recently wanted to add some protection against usage/indexing for another site.
I did some thinking and research here. Search engines have some help pages for their indexing such as Google, but each each search engines help pages only talk about their own search. In reality you probably want to use User-agent: *
So here are some easy to copy and paste chunks that you could look at using…
This is the third in a series of posts where I ask language models, or modern conversational chat bots the question “what is wikibase cloud” to generally see the way they like to answer, and be able to make some sort of comparison of them. The previous posts were for Chat GPT and Bing, but now I find myself with access to Bard by Google.
Firstly, “What is Bard?”
Bard is a large language model, also known as a conversational AI or chatbot trained to be informative and comprehensive. I am trained on a massive amount of text data, and I am able to communicate and generate human-like text in response to a wide range of prompts and questions. For example, I can provide summaries of factual topics or create stories.
Bard, 24 March 2023
On to the main event….
“What is wikibase cloud?”
As a language model, I’m not able to assist you with that.
I previously compared Chat GPT and the Bing chat AI when it came to the question of “What is Wikibase Cloud”.
This comparison and further discussion highlighted problems with using Chat GPT alone. It seems to like inventing URLs that look right but have never existed, as it primarily wants to have a good conversation. And it seems to also do this for things such as Wikidata identifiers when referenced.
So, let’s take this same problem, test it out with the Bing chat AI, and see how it fares.
Firstly, how do we make the Bing chat AI actually reference Wikidata?
If we simply ask questions like “What is the capital of Germany?” or “Who is the prime minister of the UK?” we get mostly accurate responses referencing a variety of sources, including Wikipedia but not Wikidata.
Note I say mostly accurate here as the answer about Rishi Sunak is inaccurate as he became prime minister after Lizz Truss resigned, not Boris Johnson!
Asking the same questions with a follow-up request to “Please reference your answer with Wikidata Items!” seems to get us part of the way.
This is one of the first times I’m going to have purposefully used Bing since its launch!
As before, Messages to Bing AI will be in bold, things that are wrong, in red, and things that are right in green.
I’ll try to steer the conversation through the same questions that I used with ChatGPT.
Firstly, “What is Bing AI?”
Bing AI is a term that refers to various features and capabilities of Bing that are powered by artificial intelligence. For example, Bing AI can help you find answers, chat with you, generate content, and personalize your web experience²³.
I’m really liking the fact that the responses come with references, whereas with ChatGPT you need to ask for the resources that were used to generate the answers. Also, it looks like the “Accessed” date for all of these resources is much more recent, perhaps this means Bing will be better at conversations about more recent ongoings?
This is all also nicely displayed in the UI.
So, “What is Wikibase Cloud?”
Wikibase Cloud is a cloud-based platform that hosts instances of Wikibase, an open-source software suite for creating collaborative knowledge bases¹². It’s currently an invite-only beta service provided by Wikimedia Deutschland¹⁴.
Are you interested in applying for early access to Wikibase Cloud?
So, now we are apparently reaching the point of self-referential AI, as Bing is referencing the blog post that I wrote a few days ago pointing out where ChatGPT was incorrect about various points regarding Wikibase Cloud.
There is also an interesting prompt by Bing to continue the conversation asking if I want to apply for early access, so let’s give it a go with a simple “Yes”.
In this post, I’ll be asking ChatGPT a bunch of questions about Wikibase Cloud. mainly to see how accurate it manages to be, and how helpful the information is.
Messages to Chat GPT will be in bold, things that are wrong, in red, and things that are right in green.
But I needed to follow up, asking “Can you answer again but in the third person?“
ChatGPT is a large language model developed by OpenAI that has been trained on a vast corpus of text data. The acronym GPT stands for “Generative Pretrained Transformer,” which refers to the model’s ability to generate natural language responses to text-based prompts. ChatGPT uses a transformer neural network architecture that enables it to process and comprehend long sequences of text. Its training data is sourced from a diverse range of materials, including books, articles, and websites, and covers a broad spectrum of topics. ChatGPT has been designed to assist users with natural language processing tasks such as answering questions, summarizing text, and generating human-like responses in conversation.
But when asking about Wikibase Cloud it gets a little confused and answers incorrectly…
What is Wikibase Cloud?
Wikibase Cloud is a hosting service provided by Wikimedia Cloud Services that allows users to create and manage their own Wikibase instances in the cloud. …
