Local Test

Local Test — Inference Services

Build, run, and test a model server locally.

Steps

1. Ensure a .env file exists in the repo root with PATH_TO_<MODEL>_MODEL=/local/path/to/model.
2. Build the image: docker compose build <service>.
3. Start the service: docker compose up <service>.
4. Once it's running, send a test request. The endpoint is POST /v1/models/<model-name>:predict where <model-name> is the MODEL_NAME env var set for that service in docker-compose.yml. Check src/models/<service>/model_server/model.py for the expected input schema. Example for revert-risk language agnostic model: curl localhost:8080/v1/models/revertrisk-language-agnostic:predict -X POST -d '{"lang":"en","rev_id":12345}' -H "Content-type: application/json".
5. To stop: Ctrl+C or docker compose down.

Notes

• ARM Macs: If the service doesn't start, add platform: linux/amd64 to the service in docker-compose.yml.
• The service listens on localhost:8080 by default. Check docker-compose.yml if the port is mapped differently. If :8080 is already in use, stop the other service or remap the port.
• Model files must be downloaded separately from https://analytics.wikimedia.org/published/wmf-ml-models/ and placed at the path referenced in .env.
• To run detached: docker compose up -d <service>. Logs: docker compose logs <service>.

Input

$ARGUMENTS — the docker-compose service name (e.g., revertrisk-language-agnostic, articlequality, reference-need).