Decision.Engine.mp4
This decision engine can generate one final decision based on the user's decision tree. Next, this policy can be stored and executed in the back-end.
For this project to run, make sure these software are installed:
To run locally:
-
Clone this repo
git@github.com:jefersoneiji/decision-engine.git -
Install dependencies in your machine
yarn install
-
Start both the front and back-end
yarn dev
Execute the following command:
yarn testyarn lint- README |
Frontend: Contains front-end logic for the policy editor - README |
Backend: Contains back-end logic for the CRUD operations in policies - README |
PolicyDB: Local database with sqlite and sqlalchemy - README |
ExecutionEngine: Responsible for processing and outputing one decision after executing a policy
Turbo is used to reduce the number of steps required for executing commands such as spin up apps in dev mode.
- For the sake of speed and simplicity. SQLite was choosen as local database engine
- Folders contain file according to their purpose. For instance
routesonly contains API routes. This structure make files predictible - As a way to provent bugs and enforce code styling
pytestwas added to the project
- Because of its reliability and simplicity
Axioswas chosen ashttp-client - Most user feedback comes shows as
Toastnotifications fromreact-toastify - As a way to provent bugs and enforce code styling
eslintwas added to the project - An AI assistant may be helpful in answering user's questions related to docs and help them through problem solving while create policies
Made by Jeferson Eiji ➡️ Get in touch!