Building Tadabase apps with your own custom ChatGPT AI Chatbot
Today, we're embarking on an exciting journey where we'll create a complete application harnessing the power of AI tools. Thanks to the recent advancements in OpenAI's Chat GPT, you can now craft your very own AI helpers and chatbots to answer questions based on the knowledge you provide. In this episode, we'll leverage this technology to assist us in designing the data structure and page layout for our database application, essentially building an app from scratch with our personalized AI assistant.
To kick things off, I've already set up my custom AI helper named "Tadabase Helper" using ChatGPT. It can answer questions based on the Tadabase Knowledge Center, making it a valuable resource. Now, let's paste a prompt describing our application's goal: creating an app for my lawn care business. We need guidance on the tables and fields required for a robust connection structure within Tadabase. We'll manage clients, employees, client properties, jobs, and services.
After reviewing the AI's response, I've decided to proceed with two separate tables for clients and employees. While we could store all people in a single users table, separating them makes sense for now. If we want them to log in, we'll create user records and link them to clients or employees. This approach aligns with our AI helper's suggestion.
With our data structure in mind, let's head over to the builder. We'll start by creating the clients and employees tables. The fields recommended by our AI helper, such as client ID, client name, contact information, and notes, are added accordingly. For employees, we include fields like email, phone, address, and employee position. Auto-increment fields for unique identifiers ensure smooth data handling.
Next, we move on to the client properties table. As clients may have multiple properties, we set up a connection field to link each property to a client. Additionally, we add fields for property address, size, and notes to provide detailed information.
The jobs table comes next, with connections to clients, properties, services, and assigned employees. We establish a connection field to assign multiple employees to a single job. Fields for scheduled date and time, job status, and service type ensure we capture essential job details. Notes and comments offer additional flexibility.
Lastly, we create the services table, where we store services with names, descriptions, and prices.
Now that our data tables are set up as guided by our AI helper, it's time to visualize their relationships. The support and table connection graph in the app settings help us understand how each table interacts with others, ensuring a clear and organized structure.
Moving forward, we'll use our Tadabase Helper AI GPT to assist us in designing our app's page structure. This will involve determining layouts, pages, and components per page to create a seamless user experience.
In the upcoming episode, we'll delve deeper into building the front-end of our application using the insights from our AI helper.
Thank you for joining us on this exciting journey of building an application with the help of AI. Stay tuned for next week's episode, and we'll continue to Build It With Tim. Take care, and see you next time!