image_management_api/deployment/cloud-function/README.md

Cloud Function for Image Processing

This directory contains the source code for the Cloud Function that processes image embeddings.

Deployment

Note: This Cloud Function is now deployed via Terraform, not the previous bash script.

The Cloud Function is automatically deployed when you run:

cd deployment/terraform
terraform apply

What the Cloud Function Does

1. Triggered by Pub/Sub: Listens to the image-processing-topic for new image processing tasks
2. Downloads Images: Retrieves images from Google Cloud Storage
3. Generates Embeddings: Uses Google Cloud Vision API to create image embeddings
4. Stores Vectors: Saves embeddings to the Qdrant vector database
5. Updates Status: Updates Firestore with processing status and embedding metadata

Environment Variables

The following environment variables are automatically configured by Terraform:

• QDRANT_HOST: IP address of the vector database VM
• QDRANT_PORT: Port for Qdrant (default: 6333)
• QDRANT_API_KEY: API key for Qdrant authentication
• QDRANT_COLLECTION: Collection name for storing vectors (default: image_vectors)

Function Configuration

• Runtime: Python 3.11
• Memory: 512MB
• Timeout: 540 seconds (9 minutes)
• Max Instances: 10
• Min Instances: 0 (scales to zero when not in use)
• Retry Policy: Automatic retries on failure

Dependencies

See requirements.txt for the complete list of Python dependencies.

Monitoring

The function automatically logs to Google Cloud Logging. You can monitor:

• Function executions
• Error rates
• Processing times
• Pub/Sub message handling

Manual Testing

To manually trigger the function, publish a message to the Pub/Sub topic:

{
  "image_id": "test-image-123",
  "storage_path": "your-bucket/path/to/image.jpg",
  "team_id": "team-456",
  "retry_count": 0
}