This code snippet is part of a larger system designed to process and interpret user input for a responsive application. In this specific section, I implemented logic to identify key phrases within user responses, such as “yes," "no," or requests for "more information.” The system uses case-insensitive matching and simulates a short delay to create a more natural interaction experience. This functionality ensures that user input is accurately categorized, enabling the application to provide appropriate feedback or actions based on predefined criteria.

This code snippet is part of a larger system designed to process and interpret user input dynamically. In this section, I implemented a system to match user responses against a dictionary of keyword arrays. If a keyword is detected, the application updates its current stage and provides an initial prompt for that stage. The logic includes case-insensitive matching, efficient loop-breaking to optimize performance, and fallback handling for unmatched responses. This functionality enables the application to adapt to user input in real-time, delivering a more context-aware and responsive experience.

This code updates the AI’s text response in an interactive dialogue system. It handles different types of responses based on the player’s input, cycling through pre-defined answers or providing additional information. When the input is the initial prompt, it sets up the first response and acceptable answers for the current stage. If the player’s input matches an acceptable answer, the code either cycles through multiple responses or provides more information. If the response is invalid, the AI prompts the player to try again. The response is then added to the chat box, ensuring a dynamic and engaging conversation flow. This approach helps create an interactive and responsive dialogue system where the AI adapts based on user input.

This function adds a new text bubble to the chat UI, either for the player or the AI, based on the provided text prefab and text content. It instantiates a new text bubble from the prefab and assigns the passed-in text to the bubble’s TMP_Text component. The function then updates the UI layout by forcing a rebuild of the bubble’s RectTransform. If the message is from the player, it plays a sound indicating a message was sent; if it’s from the AI, it plays a message received sound. Additionally, if the AI’s message contains a link (identified by “https”), a functioning Link component is added to the bubble to handle interactions. This ensures that the UI dynamically updates to display messages while also managing player and AI message behaviors appropriately.

For this project, we utilized ayellowpaper's serialized dictionary package for Unity (link), a powerful tool that greatly enhanced our ability to manage complex dictionaries. This package allowed us to customize and visualize our dictionaries directly within the Unity editor, streamlining our workflow. Given the extensive size and depth of the dictionaries we were working with, this package proved invaluable in helping us organize, navigate, and efficiently understand the data structure, ultimately improving both our development process and project management.

The Layout Element component was key to this project’s visual success, as it allowed me to control the size and flexibility of individual UI elements, like message bubbles, within the overall messaging layout. By setting preferred widths, heights, and flexibility values, I was able to ensure that the message bubbles resized properly based on the content and adapted to different screen sizes. This helped achieve the desired phone messaging aesthetic, where each message fits neatly in the conversation flow while maintaining an organized and user-friendly layout. The experience greatly expanded my knowledge of Unity’s UI system, enabling me to create polished, responsive designs for interactive applications.