Cluster creation
Dashboard page
The dashboard serves as the central hub for managing your clusters. It provides a comprehensive view of all your clusters and easy access to various management options through the sidebar. This guide will walk you through the dashboard layout and the process of creating a new cluster.
Layout
When you first access the dashboard, you'll notice a streamlined interface designed for ease of navigation and efficiency:
Clusters List: The main area of the dashboard displays a list of your existing clusters. Each cluster entry shows relevant details such as the cluster name, status, and quick action buttons for convenient management.
Sidebar Options: The sidebar on the left-hand side contains multiple options allowing you to navigate through different sections of the platform. These options include but are not limited to, cluster management, settings, account information, and support.
Create a Cluster Button: Located at the top-right corner of the dashboard, the "Create a Cluster" button is prominently displayed. This button is your starting point for adding new clusters to your account.
Creating a Cluster
Follow these steps to create a new cluster:
Navigate to the Create a Cluster Button: Look to the top-right corner of the dashboard page and locate the "Create a Cluster" button.
Initiate Cluster Creation: Click on the "Create a Cluster" button. You will be redirected to the cluster creation page, where you can specify the configurations for your new cluster.
Cluster Creation Page
Upon clicking the "Create a Cluster" button, you will land on the Cluster Creation Page. This page guides you through the setup process, including naming your cluster, selecting the embedding model type, and defining any specific settings required for your cluster's operation.
Cluster configuration: Start by entering a name for your cluster and selecting the desired embedding model from the options provided. Depending on your needs, you may choose from various model that best suit your project. Cluster name have to be unique for a single user. Right now Bagel DB supports two embedding model to store vector embeddings:
bagel-text: Tailored for textual data, this model generates embeddings with a dimensionality of 768, capturing the intricate semantic relationships within text.bagel-multimodal: Perfect for datasets containing both text and images, this model creates comprehensive embeddings with a dimensionality of 1408, reflecting the multifaceted nature of multimedia content.
Confirmation and Next Steps: After creating the cluster, you will receive a confirmation message, and your new cluster will appear on the dashboard's cluster list. From there, you can manage your cluster, deploy applications, or perform further configurations as needed.
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