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This blog entry discusses and showcases the final presentation for our project, campAIgn, to the Computer Science educational board at SCSU as well as to fellow classmates, students, and faculty within the Computer Science department. I also hint at next steps, goals, and some exciting news on the horizon for the project.
This blog entry discusses the next hurdle within the UI Optimization process: the implementation of tooltips. Tooltips will provide users who may be less experienced or knowledgeable with tech, especially AI, the opportunity to understand the process and use for each feature provided within the application.
This blog entry discusses the first of many issues regarding UI optimization: asynchronous form rendering. This simple implementation using vanilla JavaScript would allow for our application's user experience to improve vastly, and this post will highlight the process I underwent to apply this level of functionality to the application.
This blog entry discusses the 'next steps' of the application, and marks the shift from a back-end focus to prioritizing the front-end, more importantly the user experience. We layout a plan to gather user feedback, and internalize it to directly affect the final UI and layout of the application.
This blog entry discusses the issues faced and solutions implemented to resolve the asynchronous render of AI-generated tokens not interacting as intended with Applications deployed on Google App Engine.
This blog entry discusses the steps taken to deploy the application to Google Cloud Protocol (GCP), through the use of storage buckets, Google App Engine, Google Error Log Tracking, and a coinciding Google SQL Database.
This blog entry tackles the issues brought about by OpenAI generated images: a mere 2hr object time window. We discuss alternatives, workarounds, and the solution we eventually implemented to subvert the 2hr time window and allow for our AI-generated images to be stored permanently.
This blog entry discusses the implementation of the OpenAI API, used as the primary backbone of the application to allow for image and text generation, the primary feature of our application. We will walk through the process of acquiring an API key, building functions that utilize various OpenAI models, and the steps taken to implement the models into our application.
CampAIgn is an AI-enhanced advertisement campaign generator developed for my senior capstone project, utilizing various APIs such as OpenAI's GPT and Dall-E Models, as well as the Imgur API, Gmail API, Facebook API, and Google App Engine to allow users to create Campaigns using AI, manage them in a cloud-hosted database using Portfolios, and directly export them to their favorite social media app, all through a published, live web-app. Here, we will discuss the project synopsis and goals, outlining a course of action to bring this application idea to reality.