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ML evaluation and logging platform for healthcare

Project description

Argos Tracker Getting Started

  • Clone Repo
  • Make sure Anaconda is installed
  • Create conda env with conda env create --name argos-tracker --file=environment.yml
  • To update previously created envs use conda env update --file environment.yml --prune

Jupyter Lab

  • Activate conda env with conda activate argos-tracker
  • Create project specific ipykernel if it has not been created yet:
python -m ipykernel install --user --name argos-tracker --display-name "argos-tracker"
  • Start jupyter lab: jupyter lab
  • Open client using link provided on start
  • Open test_notebook_mimic.ipynb and select the argos-tracker ipykernel

MLflow

  • Open a new terminal window and activate the argos-tracker env
  • Start mlflow: mlflow server --host 127.0.0.1 --port 8787 --app-name mlflow_cors

Argos Dashboard

  • In a third terminal window activate the argos-tracker env
  • Go to the reports_dashboard directory cd reports_dashboard
  • Run npm ci to install dependencies for Vue frontend
  • The following error may occur if using ubuntu with a version older than 24.04:
node: /lib/x86_64-linux-gnu/libstdc++.so.6: version `GLIBCXX_3.4.31' not found (required by /home/user/anaconda3/envs/argos-tracker/bin/../lib/libnode.so.127)
  • Start client with npm run dev

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