add files for the App Engine set up

mlflow/Dockerfile

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+FROM python:3.8-slim
+
+# displays logs imidietly to the stream, they wont be part of the buffer
+ENV PYTHONUNBUFFERED True
+ENV GCP_PROJECT="783282864357"
+
+WORKDIR /app
+
+COPY ./requirements.txt ./requirements.txt
+
+RUN pip install -r requirements.txt
+
+COPY get_secret.py /app/get_secret.py
+COPY entry-point.sh /app/entry-point.sh
+COPY mlflow_auth.py /app/mlflow_auth.py
+
+ENTRYPOINT ["/usr/bin/env", "bash", "/app/entry-point.sh"]
+
+EXPOSE 8080
+EXPOSE 8000/tcp
+CMD [ "--backend-store-uri", "/tmp"]

mlflow/app.yaml

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+service: mlflow
+runtime: custom
+env: flex
+automatic_scaling:
+  min_num_instances: 1
+  max_num_instances: 2
+beta_settings:
+  cloud_sql_instances: broad-ml4cvd:us-central1:broad-ml4cvd-staging-db 

mlflow/entry-point.sh

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+#!/usr/bin/env bash
+
+set -e
+
+# Verify that all required variables are set
+if [[ -z "${GCP_PROJECT}" ]]; then
+    echo "Error: GCP_PROJECT not set"
+    exit 1
+fi
+
+# Fetch secrets from Secret Manager in CGP
+export MLFLOW_TRACKING_USERNAME="$(python3 /app/get_secret.py --project="${GCP_PROJECT}" --secret=mlflow_tracking_username)"
+export MLFLOW_TRACKING_PASSWORD="$(python3 /app/get_secret.py --project="${GCP_PROJECT}" --secret=mlflow_tracking_password)"
+export ARTIFACT_URL="$(python3 /app/get_secret.py --project="${GCP_PROJECT}" --secret=mlflow_artifact_url)"
+if [[ -z "${DATABASE_URL}" ]]; then # Allow overriding for local deployment
+    export DATABASE_URL="$(python3 /app/get_secret.py --project="${GCP_PROJECT}" --secret=mlflow_database_url)"
+fi
+
+# Verify that all required variables are set
+if [[ -z "${MLFLOW_TRACKING_USERNAME}" ]]; then
+    echo "Error: MLFLOW_TRACKING_USERNAME not set"
+    exit 1
+fi
+
+if [[ -z "${MLFLOW_TRACKING_PASSWORD}" ]]; then
+    echo "Error: MLFLOW_TRACKING_PASSWORD not set"
+    exit 1
+fi
+
+if [[ -z "${ARTIFACT_URL}" ]]; then
+    echo "Error: ARTIFACT_URL not set"
+    exit 1
+fi
+
+if [[ -z "${DATABASE_URL}" ]]; then
+    echo "Error: DATABASE_URL not set"
+    exit 1
+fi
+
+if [[ -z "${PORT}" ]]; then
+    export PORT=8080
+fi
+
+export WSGI_AUTH_CREDENTIALS="${MLFLOW_TRACKING_USERNAME}:${MLFLOW_TRACKING_PASSWORD}"
+export _MLFLOW_SERVER_ARTIFACT_ROOT="${ARTIFACT_URL}"
+export _MLFLOW_SERVER_FILE_STORE="${DATABASE_URL}"
+
+echo "hello its me im the problem its me"
+echo ${_MLFLOW_SERVER_FILE_STORE}
+echo "or me"
+echo ${_MLFLOW_SERVER_ARTIFACT_ROOT}
+
+# Start MLflow and ngingx using supervisor
+exec gunicorn -b "${HOST}:${PORT}" -w 4 --log-level debug --access-logfile=- --error-logfile=- --log-level=debug mlflow_auth:app

mlflow/mlflow_auth.py

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+from mlflow.server import app as mlflow_app
+from wsgi_basic_auth import BasicAuth
+
+app = BasicAuth(mlflow_app)