In this episode, we explore the practical use of Campfire Bots for webhook applications. We'll start by setting up an AI Image Generator bot that interacts with our Ruby on Rails application, and then connect it to a self-hosted Large Language Model (LLM). Our initial goal is to get the system working. After that, we'll focus on refactoring the code to improve its safety and maintainability.
We can create a small python service that uses a Large Language Model (LLM) to detect if a message is spam or not. Using this service, we can tie it into our Rails application so that any comment created will be evaluated for being spam or not. We explore a few different routes on handling any messages flagged as spam.
In a previous episode, we had created a custom ActionCable channel to assist in broadcasting updates from a background job. With the introduction of Turbo, we can simplify this process as we look at a few different approaches in displaying a progress bar with real time updates from background jobs.
In this episode, we look at creating an audio transcription service which allows files uploaded from Active Storage to be transcribed with Artificial Intelligence. However, there are a lot of considerations around the approach from both a performance and thread safety perspectives.