From 8a038f180ec37af1555be09e29770252c77688e4 Mon Sep 17 00:00:00 2001 From: Ralf Stockmann Date: Fri, 19 May 2023 16:32:11 +0200 Subject: [PATCH] Update README.md 1.0 notes --- README.md | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index cad4871..f71283f 100644 --- a/README.md +++ b/README.md @@ -1,14 +1,19 @@ -# Mastowall 0.2 +# Mastowall 1.0 Mastowall is a social wall application that displays posts from the [Mastodon](https://joinmastodon.org/) social network based on specified hashtags. It has been updated with new features to improve its usability and appearance. -image +image Try it live: [Mastowall for the BiblioCon conference]([https://rstockm.github.io/mastowall/?hashtags=111bibliocon,bibliocon,bibliocon23&server=https://openbiblio.social)) Use your own hashtags and server: -image +image + +JSON config file: + +image + ## Features @@ -27,6 +32,10 @@ Use your own hashtags and server: - **Navbar Hashtag Navigation:** Clicking on the hashtags in the navbar takes you to the form screen, allowing you to change the existing hashtags easily. +- **Navbar Color Customization:** The color of the navigation bar can now be customized via the `config.json` file. + +- **Including Replies:** By default, replies are excluded from the wall. However, this behavior can be changed by setting includeReplies to true in the `config.json` file. + ## Technology Stack Mastowall is built using the following technologies: @@ -57,7 +66,7 @@ Enjoy using Mastowall 0.2! ## AI-Guided Development: A Proof of Concept -Mastowall 0.2 serves as an example of how artificial intelligence can aid and accelerate the software development process. The development of this version of the app was guided by OpenAI's GPT-4, a large language model. +Mastowall may serve as an example of how artificial intelligence can aid and accelerate the software development process. The development of this version of the app was guided by OpenAI's GPT-4, a large language model. In this process, the human developer posed problems, asked questions, and described the desired features and functionalities of the application. GPT-4 then provided solutions, answered queries, generated code snippets, and suggested optimal ways to implement these features.