I wanted to use AI to help me make more deeply-informed investment and trading decisions, so I thought I'd build a personal investment assistant and open source the entire process. The goal of open sourcing this is to showcase my thoughts on how I'm incorporating AI into something useful and value add for my personal life. Doing this from the very beginning also means that it's going to go through a lot of changes and iterations, and I'll be documenting the process on my blog, I'd love it if you followed along there.
The project will start off pretty simple and generalized with foundaitonal API calls needed to pull relevant information about companies I decide to dig into, but since this is a personal project that I plan to use regularly, it will take shape to serve my specific needs from a financial management perspective. That being said, feel free to use any of this code as a reference for how to build your own AI-powered personal assistant if you'd like, none of what I'm building I plan to "close source" unless some random act of the universe forces me to do so.
Feel free to reach out to me if you have any questions or suggestions. I will not accepting code contributions for the forseeable future, but we'll see if that changes, for now this is for informational purposes only.
Thanks
- Ruby on Rails (Main application framework)
- Bulma (Styling)
- PostgreSQL (Bread and butter relational database)
- Redis (Bread and butter key-value store for background jobs and caching)
- Sidekiq (Background job processing framework)
- RSpec (Testing framework)
- Hotwire (Turbo + Stimulus for frontend interactivity)
- FinancialModelingPrep API (Financial data needs, pretty comprehensive and good free tier, wll upgrade to paid tier eventually)
- Assorted Generative AI Models used for summarization, analysis, vectorization, and more