Episode
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.
00:00 - Introduction
03:48 - Creating the Python Service
04:59 - Creating the Python web service
07:06 - Creating the Python Spam detector
11:54 - Testing the Python service
12:19 - Using Docker for the Python service
15:00 - Overview of the Rails application
17:28 - Adding migrations for the Spam detector
18:45 - Determining when to check for spam
21:35 - Creating the background job
24:54 - Testing the background service
26:50 - Adding CSS Classes to Spam messages
27:57 - Handling spam in different ways
28:41 - Filtering to exclude spam messages
29:08 - Final thoughts
► Full Episode - https://www.driftingruby.com/episodes...
This episode is sponsored by Honeybadger (https://www.honeybadger.io/)
► Visit the Merchandise Store - https://www.railsstore.com/
► Ruby on Rails Templates - https://www.rubidium.io
► Subscribe to Drifting Ruby at https://www.driftingruby.com/subscrip...
#ruby #rubyonrails #programming #code #hotwire #ai #machine-learning #development
