carlososuna11/demo-ray-serve-multiple-models

contains the basic structure that a model serving application should have. This implementation is based on the Ray Serve framework.

Ray Demo Model Serving

This repository contains the basic structure that a model serving application should have. This implementation is based on the Ray Serve framework. It not only provides a simple way to deploy a model, but also provides a way to scale the model to multiple instances.

How to run

1. Install ray serve on your machine

pip install ray[serve]

2. Create the head node

 ray start --head --block --dashboard-host 0.0.0.0
Usage stats collection is enabled. To disable this, add `--disable-usage-stats` to the command that starts the cluster, or run the following command: `ray disable-usage-stats` before starting the cluster. See https://docs.ray.io/en/master/cluster/usage-stats.html for more details.

Local node IP: XX.XX.XX.XX

--------------------
Ray runtime started.
--------------------

Next steps
  To connect to this Ray runtime from another node, run
    ray start --address='XX.XX.XX.XX:6379'

  Alternatively, use the following Python code:
    import ray
    ray.init(address='auto')

  To connect to this Ray runtime from outside of the cluster, for example to
  connect to a remote cluster from your laptop directly, use the following
  Python code:
    import ray
    ray.init(address='ray://<head_node_ip_address>:10001')

  If connection fails, check your firewall settings and network configuration.

  To terminate the Ray runtime, run
    ray stop

--block
  This command will now block forever until terminated by a signal.
  Running subprocesses are monitored and a message will be printed if any of them terminate unexpectedly. Subprocesses exit with SIGTERM will be treated as graceful, thus NOT reported.

3. Install the dependencies

pip install -r requirements.txt

4. Run the application

python3 backend/main.py

How to test

1. Run the test

python3 -m pytest tests

Links of interest

• routes of the application: http://localhost:8000/-/routes
• dashboard: http://localhost:8265
• documentation: https://docs.ray.io/en/master/serve/index.html

Environment variables

Name	Default Value	Overwrite required	Description	Reference
SETTINGS_MODULE_ENVIRONMENT_VARIABLE	config.settings	Yes	The path to the settings module of your project	Backend Base
DEBUG	True	No	If the application is running in debug mode	Backend Base
PROJECT_NAME	DEMO MULTIPLE MODEL SERVING	No	The name of the project
PROJECT_DESCRIPTION	This is a demo of how to serve multiple models with Ray Serve	No	The description of the project
PROJECT_VERSION	0.0.1	No	The version of the project
RAY_ADDRESS	auto	No	The address of the ray cluster	Ray Serve