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deploy_functions_prod.yml
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name: Deploy firebase functions to PROD
on:
push:
branches:
- main
paths:
- "backend/**"
- ".github/workflows/deploy_functions_prod.yml"
workflow_dispatch:
jobs:
build_and_deploy:
runs-on: ubuntu-latest
steps:
# Step 1: Checkout the code
- uses: actions/checkout@v3
# Step 1.5: Environment variables
- name: create env file
working-directory: backend
run: |
cd functions
touch .env
echo "${{ secrets.FUNCTIONS_ENV_VARS_PROD }}" >> .env
# Step 2: Set up Python environment
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.10'
# Step 3: Set up Node.js environment
- name: Set up Node
uses: actions/setup-node@v3
with:
node-version: 19.7.0
# Step 3.5: Download the ZIP file from Google Drive
- name: Download Models ZIP
run: |
wget "${{ secrets.LINK_TO_MODEL_FILES_PROD }}" -O models.zip
- name: List Directory Contents
run: ls -lh models.zip
- name: Check File Type
run: file models.zip
# Step 3.5.2: Extract the ZIP file
- name: Extract Models ZIP
run: |
unzip models.zip -d backend/functions/ml_logic
# Step 3.5.3: Clean up
- name: Clean Up
run: rm models.zip
# Step 4: Create Service Account Key and Set Env Variables
- name: Create SA key and set env variables
run: |
echo '${{ secrets.FIREBASE_SERVICE_ACCOUNT_SCHEMESSG_V3_PROD }}' > ${{ runner.temp }}/gcloud.json
echo "GOOGLE_APPLICATION_CREDENTIALS=${{ runner.temp }}/gcloud.json" >> $GITHUB_ENV
# Step 5: Prepare the environment
- name: Prepare the environment
working-directory: backend/functions
run: |
python3.10 -m venv venv
. venv/bin/activate
npx firebase-tools --version
python3.10 -m pip install -r requirements.txt
# Step 6: deploy functions
- name: Deploy functions
working-directory: backend
env:
GOOGLE_APPLICATION_CREDENTIALS: ${{ runner.temp }}/gcloud.json
run: npx firebase-tools deploy --only functions --debug --token "${{ secrets.FIREBASE_TOKEN_SCHEMESSG_V3_PROD }}"