This is a generic boilerplate for basic ML/DL projects. It has the basic functionality for doing one-off predictions based on simple inputs (i.e. not on images for example, or large numbers of inputs).

It contains nothing more than all the configuraton files for the project. No actual code.

• Streamlit for the front end
• FastAPI serving the back end
• Model storage on GCS / MLFlow (python functions to be written)
• Everything to deploy with Docker

⚠️ Back-end and front-end should go in separate repositories ⚠️

All commands needed have been included in the Makefiles:

• make run_api to run the API locally
• make docker_##### to run Docker stuff:
  • Commands to build and run (nteractively) a local Docker image
  • Commands to build and run (interactively) a Docker image ready for GCP (i.e. using linux/amd64 infra)
  • Commands to push and deploy to GCP

Just type make <tab> on the command line to see all possibilities

• make streamlit: defaults to make streamlit_local
• make streamlit_local: run streamlit locally and connect to local API (running through uvicorn on port 8000)
• make streamlit_local_docker: run streamlit locally and connect to local Docker container (running on port 8080)
• make streamlit_cloud: run streamlit locally and connect to cloud API

Just type make <tab> on the command line to see all possibilities

URIs for local and cloud APIs are included in the .streamlit/secrets.toml file (or in the Secrets setting on Streamlit Cloud)

Copy .env.sample and .env.yaml.sample to new files .env and .env.yaml and update all variables with your project identifiers.

Requirements.txt:

• requirements.txt: for production excluding all packages that are redundant in prod = requirements_dev.txt: adding packages for local usage including ipython, debugging, matplotlib, etc.
• Update requirements.txt if you use TensorFlow (uncomment the respective lines).

Complete the following files (if needed):

• requirements.txt
• .streamlit/config.toml: mainly for layout purposes
• .streamlit/secrets.toml: base it on the sample file; reflect the contents also in the Secrets settings on Streamlit Cloud

⚠️ Back-end and front-end should go in separate repositories ⚠️

• packagename/: your package (rename this, and adapt the configuration files - tip: Ctrl-Shift-F or Cmd-Shift-F in VS Code)
  • data/: only small static data (no large files), or temporary files (not tracked by git)
• api/: this is where your API code goes
• models/: your saved models (not tracked by git, should be stored elsewhere: GCS, MLFlow, ...)
• raw_data/: your data (not tracked by git, should be stored elsewhere for cloud: GCS, MLFLow, ...)
• notebooks/: your notebooks, tracked by git, but avoid working with different people on one notebook (include your name in the filename)

• app.py: main streamlit page
• pages/: put a .py file per page here if you use multiple pages
• media/: store visual elements for your pages here
• .streamlit/: configuration files for streamlit