We are creating a web app using Flask which uses prompt engineering to generate useful responses to specific user queries.
Gpt-based webapps using prompt engineering have already started to appear and this assignment is meant to help us learn how to write such apps as well as gaining experience using git for a team project. Basically it accepts some text, adds a prompt to the front, sends it to gpt, and returns the response.
The methods used in the GPT class generates text in various formats (summaries, translations, paraphrases, poems, articles, captions, etc.) and perform analysis on text (sentiment analysis).
Many software projects use SQLite to manage their data and this problem set will give you the experience of building such an app. Another important process in software engineering is the design of automated tests. This assignment will ask you to develop a suite of tests for your app. There are other database and testing frameworks, but they are all similar in principle and this assignment will expose you to the core concepts and skills you'll need.
We are recreating the PA03 app as an Express App using Mongodb (through Mongoose) as the database. It has the main transactions list page that essentially shows all of our transactions and allows us to add, delete, edit transactions and to sort by any column and to group by the category column. We can select the "Sort by" button to get desired information simply by adding a query parameter. Then we have "Group By Category". Hitting the "group by category" link sends us to a page with a simple table with two columns: one for the category and the other for the sum of the amounts for transactions in that category.
We have created TextTrove page that is inside our Productivity App which focused on creating a web application using Express, Mongoose, and EJS frameworks, which utilizes prompt engineering to generate useful responses to specific user queries.
The theme of the project is "Text Generation and Analysis," from CA01 and the GPT class's methods will be used to generate text in various formats, such as summaries, translations, paraphrases, poems, articles, captions, etc. Additionally, the app will perform text analysis, such as sentiment analysis. The app should include authentication, so users can log in with a username and password, and store information about their API requests in the database.
