A: Tables: Lego Sets (with columns for name, number, color ), Lego Pieces (with columns for name, cost, list of pieces ) Q: I want to build an app tracks my Lego sets. A: Tables: Workout (with columns for date, duration, list of exercises, weight, notes ), Gym Exercises (with columns for name, description, weight ). A: Tables: Buildings (with columns for name, phone, address, list of issues ), Issues (with columns for subject, notes, building name, date ) Q: I need an app to track my gym workouts. Q: I want an app that contains information to track issues across different buildings. A: Tables: Staff (with columns for name, title, phone number, e-mail, location ), Office Locations (with columns for name, address, list of people who work there. A: Tables: Customer Information (with columns for name, e-mail address, phone number ), Order Information (with columns for id, cost, list of product ids ), Product (id, cost ) Q: I want an employee directory that contains information about my employees and where they work. Q: I want an app that manages orders for my customers. Slowly, after a couple of examples, we got the hang of it: Prompt As we learned, GPT-3 is essentially like a 3-year-old that’s trained on the entire internet. In particular, we found that making the most complicated parts of the task simple, clear, and straightforward most significantly improved the quality of our results. There are many nuances to prompt engineering (the process of finding the best prompts to give GPT-3)-your prompts "program the model," and poor or unclear examples yield bad results. Over time, though, we found that we could get higher quality results by priming the base, OpenAI models with good, clear examples. So, we gave it a try, starting simple: given a prompt, could GPT-3 output a relevant schema?Īt first, the answer was no. Given its superb text completion abilities, we had an inkling that GPT-3 might helps us solve this problem. Initially, we started very simple - could GPT-3 output just a relevant schema given a prompt? We had an inkling that GPT-3 might be a good candidate for doing this given its superb text completion, so we gave it a try. The challenge, though, is to use that short, plain-English description to generate a relevant data schema and its associated data. And, as they play with the app, they’ll get a better understanding of how to structure their data in ways that unlock some of Glide’s more complex features, like relations. No matter if they have a specific idea or just want to experiment, we can use the short description they provide to generate a relevant data schema, some data for it, and a basic app they can use to start exploring Glide. This project’s goal is to give new Glide users a starting point. However, new users won’t have that knowledge or intuition, and this can trip them up. And, as you work with multiple Glide apps, you’ll build up an intuition for the kinds of schemas that Glide finds meaningful. If you structure your data in a specific way, Glide can produce relatively intelligent default apps. In fact, Glide uses the schema of your data source (its tables and columns) to generate a default app. For example, changing the data in Google Sheets changes the data that shows up in your app, and vice versa. In Glide, we call this a relation, and it’s just one type of computation we can run on an app’s underlying data (others include rollups, template strings, and more).Ī Glide App is intertwined with its data source. For example, a recipes app might have an associated `Recipes` table, and each item in that table might reference multiple rows in the just-mentioned `Ingredients` table (for example, the recipe for a ham and cheese sandwich might reference the `ham`, `cheese`, and `bread` rows of the `Ingredients` table). Glide can derive complex relationships between the tables, columns, and rows that drive an app. This table might have columns like `name`, `cost`, `color`, etc. For example, a grocery-tracking app might use an `Ingredients` table, where each row describes an ingredient. In Glide, apps often use data that lives in a data source like Google Sheets or Glide Tables. How can we make it easier for these new users to pick up some of the concepts they’ll need to be successful with Glide? Basic structure of a Glide Appįor context, it’s first worth describing the basic structure of a Glide App. Ultimately, they may get frustrated trying to make Glide do what they want. Either way, if they’re they're unfamiliar with some of the nuances and mental models associated with Glide, they may not know how to get started (for example, how to structure their data or how to use advanced features like relations, rollup columns, and user profiles). This project started out as a question: how can we make it easier for new users to learn Glide? Sometimes users come to Glide with specific ideas, and other times they just want to experiment.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |