entrpn / matching-engine-demo

Matching Engine Demo

In this demo, we'll create a dog breed search using Kaggle's dog breeds dataset and GCP's Matching Engine.

Setup

1. After cloning this repo, do a pip install -r requirements.txt.

2. We'll need to download the dataset and create the embeddings. If you haven't downloaded your Kaggle API credentials, do it now. Now run.

   python extract_embeddings.py

   This script downloads the Kaggle dog breeds dataset, creates embeddings using a pretrained pytorch Resnet-18 model and uploads them to a GCS bucket. At the end of the script, you'll see a message Bucket gs://{bucket_name} was created. Keep this handy as we'll be using this in another step.

3. Next, we'll need to set up a VPC as it is required by Matching Engine. Run network_setup.sh.

   ./network_setup.sh -n matching-engine-demo -r matching-engine-peering -p <project_id>

4. Now it is time to create the index. Run create_index.py and use the bucket name from one of the steps above as the contents-delta-uri parameter. This operation will take a while as it creates the index and endpoint in Matching Engine.

   python create_index.py --project-id <project_id> --contents-delta-uri gs://<bucket_name> --network matching-engine-demo --project-number <project_number>

   When the script is finished, it will print the grpc ip address which we will need in the next step.

5. To query an index, we'll need to use grpc. This is embedded inside a gradio app in the web_ui folder. cd into the folder and build the image. We'll run this image in Cloud Run.

   cd web_ui
   mkdir images
   find ../data/ -name '*.jpg' -exec cp -t images/ {} +
   docker build . --build-arg port=80 --build-arg grpc_ip=<grpc_ip> -t gcr.io/<project_id>/matching-engine-ui:latest
   docker push gcr.io/<project_id>/matching-engine-ui:latest

   The app won't work in our local environment because the endpoint is only accessible in the same VPC. For this we need to create a VPC connector for the Cloud Run app to have access.

   gcloud services enable vpcaccess.googleapis.com
   gcloud compute networks vpc-access connectors create matching-engine-connector --network matching-engine-demo --region us-central1 --range 10.8.0.0/28
   gcloud compute networks vpc-access connectors describe matching-engine-connector --region us-central1

   Now deploy the app

   gcloud run deploy --port 80 matching-engine-ui --image gcr.io/<project_id>/matching-engine-ui:latest --vpc-connector matching-engine-connector --timeout 3600 --region us-central1 --cpu=4 --memory 4Gi