image_management_api/scripts/README.md

Build and Deployment Scripts

This directory contains scripts for building and deploying the Sereact API application.

Prerequisites

• Docker installed and running
• For deployment: access to a container registry (e.g., DockerHub, Google Container Registry)
• For Cloud Run deployment: Google Cloud SDK (gcloud) installed and configured

Scripts

Build Script (build.sh)

Builds the Docker image for the Sereact API.

Usage:

# Basic usage (builds with default settings)
./scripts/build.sh

# Customize the image name
IMAGE_NAME=my-custom-name ./scripts/build.sh

# Customize the image tag
IMAGE_TAG=v1.0.0 ./scripts/build.sh

# Use a custom registry
REGISTRY=gcr.io/my-project ./scripts/build.sh

Environment Variables:

• IMAGE_NAME: Name for the Docker image (default: "sereact-api")
• IMAGE_TAG: Tag for the Docker image (default: "latest")
• REGISTRY: Container registry to use (default: empty, using DockerHub)

Deploy Script (deploy.sh)

Pushes the built Docker image to a container registry and optionally deploys to Google Cloud Run.

Usage:

# Push to registry only
./scripts/deploy.sh

# Push to registry and deploy to Cloud Run
DEPLOY_TO_CLOUD_RUN=true PROJECT_ID=my-project-id ./scripts/deploy.sh

# Customize deployment settings
DEPLOY_TO_CLOUD_RUN=true PROJECT_ID=my-project-id REGION=us-west1 SERVICE_NAME=my-api ./scripts/deploy.sh

Environment Variables: All variables from the build script, plus:

• PROJECT_ID: Google Cloud project ID (required for Cloud Run deployment)
• REGION: Google Cloud region (default: "us-central1")
• SERVICE_NAME: Name for the Cloud Run service (default: "sereact-api")

Cloud Run Deployment Script (deploy-to-cloud-run.sh)

Deploys the application to Google Cloud Run using the service configuration file.

Usage:

# Deploy using existing service.yaml
PROJECT_ID=my-project-id ./scripts/deploy-to-cloud-run.sh

# Build, push, and deploy in one command
PROJECT_ID=my-project-id BUILD=true PUSH=true ./scripts/deploy-to-cloud-run.sh

# Customize the deployment
PROJECT_ID=my-project-id REGION=us-west1 IMAGE_TAG=v1.0.0 ./scripts/deploy-to-cloud-run.sh

Environment Variables:

• PROJECT_ID: Google Cloud project ID (required)
• REGION: Google Cloud region (default: "us-central1")
• SERVICE_CONFIG: Path to the service configuration file (default: "deployment/cloud-run/service.yaml")
• IMAGE_NAME: Name for the Docker image (default: "sereact-api")
• IMAGE_TAG: Tag for the Docker image (default: "latest")
• REGISTRY: Container registry to use (default: "gcr.io")
• BUILD: Set to "true" to build the image before deployment (default: "false")
• PUSH: Set to "true" to push the image before deployment (default: "false")

Frontend Client Script (client.sh)

Manages the SeReact frontend client development, building, and deployment.

Usage:

# Start development server
./scripts/client.sh dev
# or
./scripts/client.sh serve

# Build production files
./scripts/client.sh build

# Deploy to static hosting
DEPLOY_TARGET=netlify ./scripts/client.sh deploy

# Clean build artifacts
./scripts/client.sh clean

# Install dependencies
./scripts/client.sh install

# Check code quality
./scripts/client.sh lint

# Run tests
./scripts/client.sh test

# Show help
./scripts/client.sh help

Environment Variables:

• PORT: Development server port (default: 8080)
• HOST: Development server host (default: localhost)
• DEPLOY_TARGET: Deployment target - netlify, vercel, s3, github, or manual (default: manual)
• S3_BUCKET: S3 bucket name (required for S3 deployment)

Features:

• Development Server: Starts a local HTTP server with CORS headers for frontend development
• Production Build: Creates optimized production files in dist/ directory
• Multiple Deployment Options: Supports Netlify, Vercel, AWS S3, GitHub Pages, and manual deployment
• Code Quality: Integrates with ESLint, Stylelint, and HTML Tidy (if installed)
• Dependency Management: Handles Python virtual environment setup
• Clean Build: Removes build artifacts and cache files

Deployment Targets:

• netlify: Deploy using Netlify CLI
• vercel: Deploy using Vercel CLI
• s3: Deploy to AWS S3 bucket (requires AWS CLI and S3_BUCKET env var)
• github: Shows instructions for GitHub Pages deployment
• manual: Shows manual deployment instructions

Example Workflows

Basic workflow:

# Build and tag with version
IMAGE_TAG=v1.0.0 ./scripts/build.sh

# Deploy to Cloud Run
DEPLOY_TO_CLOUD_RUN=true PROJECT_ID=my-project-id IMAGE_TAG=v1.0.0 ./scripts/deploy.sh

Using the Cloud Run config file:

# Build and deploy in one step
PROJECT_ID=my-project-id BUILD=true PUSH=true ./scripts/deploy-to-cloud-run.sh

Frontend Development Workflow:

# Install dependencies
./scripts/client.sh install

# Start development server
./scripts/client.sh dev

# Build for production
./scripts/client.sh build

# Deploy to Netlify
DEPLOY_TARGET=netlify ./scripts/client.sh deploy

Scripts Documentation

This directory contains utility scripts for the SEREACT application.

Database Seeding Scripts

seed_firestore.py

This script initializes and seeds a Google Cloud Firestore database with initial data for the SEREACT application. It creates teams, users, API keys, and sample image metadata.

Requirements

• Google Cloud project with Firestore enabled
• Google Cloud credentials configured on your machine
• Python 3.8+
• Required Python packages (listed in requirements.txt)

Setup

1. Make sure you have the Google Cloud SDK installed and configured with access to your project:

   gcloud auth login
   gcloud config set project YOUR_PROJECT_ID
   

2. If not using application default credentials, create a service account key file:

   gcloud iam service-accounts create sereact-app
   gcloud projects add-iam-policy-binding YOUR_PROJECT_ID --member="serviceAccount:sereact-app@YOUR_PROJECT_ID.iam.gserviceaccount.com" --role="roles/datastore.user"
   gcloud iam service-accounts keys create credentials.json --iam-account=sereact-app@YOUR_PROJECT_ID.iam.gserviceaccount.com
   

3. Set environment variables:

   # Windows (CMD)
   set DATABASE_TYPE=firestore
   set GCS_CREDENTIALS_FILE=path/to/credentials.json
   
   # Windows (PowerShell)
   $env:DATABASE_TYPE="firestore"
   $env:GCS_CREDENTIALS_FILE="path/to/credentials.json"
   
   # Linux/macOS
   export DATABASE_TYPE=firestore
   export GCS_CREDENTIALS_FILE=path/to/credentials.json
   

Usage

Run the seeding script from the project root directory:

# Activate the Python virtual environment
source venv/bin/activate  # Linux/macOS
venv\Scripts\activate     # Windows

# Run the script
python scripts/seed_firestore.py

Generated Data

The script will create the following data:

1. Teams:

   • Sereact Development
   • Marketing Team
   • Customer Support

2. Users:

   • Admin User (team: Sereact Development)
   • Developer User (team: Sereact Development)
   • Marketing User (team: Marketing Team)
   • Support User (team: Customer Support)

3. API Keys:

   • One API key per user (the keys will be output to the console, save them securely)

4. Images:

   • Sample image metadata (3 images, one for each team)

Notes

• The script logs the generated API keys to the console. Save these keys somewhere secure as they won't be displayed again.
• If you need to re-run the script with existing data, use the --force flag to overwrite existing data.
• This script only creates metadata entries for images - it does not upload actual files to Google Cloud Storage.