✨ClusterF*ck✨

ClusterF*ck is a GitHub project that utilizes text embeddings to cluster notes and provides a user-friendly interface for editing the position of these notes using a simple slick and drag mechanism. The project is built with Next.js and Tailwind CSS, and it uses Supabase as the database, which runs on PostgreSQL.

Getting Started

To initialize a Next.js project cloned from GitHub and set up ClusterF*ck, follow these steps:

Clone the repository:

git clone https://github.com/your-username/ClusterF*ck.git

Navigate to the project directory:

cd ClusterF*ck

Install the dependencies:

npm install

Configure Supabase:

Set up a Supabase project and obtain the necessary credentials. Create a .env.local file in the project root directory. Add the following environment variables to the .env.local file:

NEXT_PUBLIC_SUPABASE_URL=<your-supabase-url>
NEXT_PUBLIC_SUPABASE_KEY=<your-supabase-key>

Run the development server:

npm run dev

Open your browser and navigate to http://localhost:3000 to see the ClusterF*ck application.

Futureproofing for Adding the Embeddings Feature

When building up the interface and planning to add the embeddings feature to ClusterF*ck, consider the following steps: Identify the functionality and requirements of the embeddings feature. Determine how the text embeddings will be generated and how they will be used for clustering. Research and select a suitable text embeddings library or service that integrates well with Next.js and aligns with your project requirements. Some popular options include TensorFlow.js, Hugging Face Transformers, or Sentence Transformers. Update the project dependencies to include the chosen text embeddings library. This may involve modifying the package.json file and running npm install to install the required packages. Plan the integration of the embeddings feature into the existing codebase. Identify the components or pages that will be affected and create a roadmap for implementing the necessary changes. Consider creating a separate branch or feature branch to work on the embeddings feature. This will allow you to isolate your changes and iterate on them without affecting the main codebase. Begin implementing the necessary code changes to add the embeddings feature. Follow best practices and modularize your code to ensure maintainability and scalability. Test the embeddings feature thoroughly to ensure it functions as expected. Write unit tests and conduct user testing to validate its accuracy and usability. Consider documenting the integration of the embeddings feature in the project's documentation or README file. Provide instructions on how to use the feature and any relevant configuration options.

By following these steps, you can effectively futureproof the ClusterF*ck project while adding the embeddings feature, ensuring a smooth integration and providing a robust and user-friendly experience. 😄😄