README

ML Project template used to bootstrap ML projects requiring compute-intensive jobs.

Features:

• Batching of ML jobs to run asynchronously using Redis.
• FastAPI used as the application server.
• Nginx used as a reverse proxy.
• Python ML workers receive jobs from Redis.

Services

• Web server: Nginx
• Application server: FastAPI
• ML Workers: Python workers
• Message Queue: Redis
• Clientside: Sapper
• Docker-compose for the deployment of services.

How do I get set up?

Run Project

cd MLtiplier
docker-compose build
docker-compose up

Build your ML worker

• Add your ML workload to run here backend_services/ml_worker/ml_worker/main.py
• ML job payload is added to Redis from the backend_services/app_server/app_server/main.py

Update your clientside

• Update ui/ directory to match the clientside required for Mltiplier

Contribution guidelines

• Writing tests
• Code review
• Other guidelines

Who do I talk to?

• https://github.com/KshitijKarthick