Docker

Prerequisites

1. Credentials for Google Ads API access which are stored in google-ads.yaml. See details here.
2. A Google Cloud project with billing account attached.
3. Vertex AI API enabled.
4. Environment variables specified:
   • GEMINI_API_KEY to access Google Gemini.

5. Service account created and service account key downloaded in order to write data to BigQuery.

   Note

   If authenticating via service account is not possible you can authenticate with the following command:

   gcloud auth application-default login
   

   You can grab application_default_credentials.json file from $HOME/.config/gcloud folder.

Run

Map local files, provide environment variables and run

docker run \
  -v /path/to/google-ads.yaml:/app/google-ads.yaml \
  -v /path/to/application_default_credentials.json:/app/service_account.json \
  -e GEMINI_API_KEY=$GEMINI_API_KEY \
  -e GOOGLE_CLOUD_PROJECT=$GOOGLE_CLOUD_PROJECT \
  ghcr.io/google-marketing-solutions/arba:latest \
  -a <GOOGLE_ADS_ACCOUNT> -c /app/google-ads.yaml

where:

• -a - Google Ads account(s) or MCC(s)
• -c - Path to google-ads.yaml

Customize

You can provide the following Environment variables to customize arba execution.

• START_DATE - First date of performance; can be either date (i.e. '2026-01-01') or lookback (:YYYYMMDD-N, where N - number of lookback days).
• END_DATE - Last date of performance in the same format as START_DATE.
• MIN_COST_SHARE - Share of text ads needs to be processed by Gemini. From 0 to 100.
• GEMINI_API_KEY - Gemini API key.