delvedor /
fastify-example
This project is a small but feature complete application build with Fastify and Svelte, and it aims to show all the core concepts of Fastify, best practices, and recommendations.
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LuixBits / repository
This is the repository for my master thesis. Its about visualising connections between bits of information using different AI tools and visualisation techniques
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TextSight is an Obsidian plugin that leverages OpenAI's advanced language models to analyze your notes and uncover connections based on topics, keywords, and named entities. It utilizes Dexie.js as a wrapper for IndexedDB, facilitating efficient data management and retrieval within the plugin. TextSight helps you visualize these connections in a 3D environment, providing a holistic view of your research or notes. This tool is designed to assist you in discovering hidden insights, navigating through your ideas, and gaining a deeper understanding of your data.
The current prototype only allows it to analyse 1 document at a time. For that, you have to open the sidebar either through a click on the icon on the left or a click on the status bar.
Analysis tab of the sidebar, make sure that the correct document is selected in the dropdown. Then press Analyse Textctrl + shift + i.Analyse Connections. Once that is done you have to reload the visualisation (top right button)ctrl + p and search for Reload app without savingAll of this happens in the command line. If you have not installed it go here. Open the command line and navigate to your Vault.
Clone the Plugin
Navigate to your Obsidian vault's plugins folder. This is typically located in your vault's root directory under .obsidian/plugins/. Clone the TextSight repository into this directory using the following command:
git clone https://github.com/devluixos/TextSight.git
Install Dependencies:
Navigate into the TextSight directory in .obsidian/plugins/. and open the console here. You will have to have nodejs installed.
Run the following command to install the necessary dependencies:
npm install
Run the build for the plugin The last step is to create a build of the code for it to work inside obsidian:
npm run build
Enable in Obsidian:
Open Obsidian, go to Settings -> Community Plugins, disable Safe Mode, and enable TextSight from the list.
API Key Setup:
Open the plugin settings from the sidebar and enter your OpenAI API key.

If you want to contribute to the development of TextSight or customize it further, follow these steps:
Fork and Clone the Repository: Fork the repository on GitHub and clone your fork to your local machine:
git clone https://github.com/yourusername/TextSight.git
Install Dependencies: Navigate into the TextSight directory and install the dependencies:
npm install
API Key Setup: Run the setup script and enter your OpenAI API key when prompted:
npm run setup
Start the Development Server: Start the development server to watch for changes and automatically reload:
npm run dev
Make Your Changes: Implement your features or bug fixes. Ensure that your code follows common sense.
Commit and Push: Commit your changes and push them to your forked repository:
git add .
git commit -m "Your commit message"
git push origin main
Create a Pull Request: Create a pull request to the main repository. Provide a detailed description of your changes and the problem they solve.
We welcome contributions from the community! Whether you're a developer, designer, or tester, there's a place for you in the TextSight project. Check out our Discord)
If you'd like to write some code but don't know where to start, we've written some ToDos.
Testers are always welcome. Give TextSight a try, analyze a few documents, and provide feedback (preferably on Discord). Your insights are invaluable in making TextSight better.
TextSight currently uses OpenAI's GPT-4o model, so you need an API key. If you cannot get one, we have a few keys with a $5 budget each for you. With $5 you'll be able to analyze a significant number of documents.
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delvedor /
This project is a small but feature complete application build with Fastify and Svelte, and it aims to show all the core concepts of Fastify, best practices, and recommendations.
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