image_management_api/scripts/README.md

# Build and Deployment Scripts

This directory contains scripts for building and deploying the Contoso 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 Contoso API.

**Usage:**
```bash
# 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: "contoso-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:**
```bash
# 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: "contoso-api")

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

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

**Usage:**
```bash
# 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: "contoso-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 Contoso frontend client development, building, and deployment.

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

### Frontend Development Workflow:
```bash
# 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 CONTOSO application.

## Database Seeding Scripts

### `seed_firestore.py`

This script initializes and seeds a Google Cloud Firestore database with initial data for the CONTOSO 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:
   ```bash
   gcloud auth login
   gcloud config set project YOUR_PROJECT_ID
   ```

2. If not using application default credentials, create a service account key file:
   ```bash
   gcloud iam service-accounts create contoso-app
   gcloud projects add-iam-policy-binding YOUR_PROJECT_ID --member="serviceAccount:contoso-app@YOUR_PROJECT_ID.iam.gserviceaccount.com" --role="roles/datastore.user"
   gcloud iam service-accounts keys create credentials.json --iam-account=contoso-app@YOUR_PROJECT_ID.iam.gserviceaccount.com
   ```

3. Set environment variables:
   ```bash
   # 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:

```bash
# 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**:
   - Contoso Development
   - Marketing Team
   - Customer Support

2. **Users**:
   - Admin User (team: Contoso Development)
   - Developer User (team: Contoso 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.