def run_graph(import_path: str, deployment_override_options: List[Dict]):
"""Deploys a Serve application to the controller's Ray cluster."""
from ray import serve
from ray.serve.api import build
# Import and build the graph
graph = import_attr(import_path)
app = build(graph)
# Override options for each deployment
for options_dict in deployment_override_options:
name = options_dict["name"]
app.deployments[name].set_options(**options_dict)
# Run the graph locally on the cluster
serve.start(_override_controller_namespace="serve")
serve.run(app)
def run_graph():
"""Deploys a Serve application to the controller's Ray cluster."""
from ray import serve
from ray._private.utils import import_attr
from ray.serve.api import build
# Import and build the graph
graph = import_attr("test_config_files.pizza.serve_dag")
app = build(graph)
# Override options for each deployment
for name in app.deployments:
app.deployments[name].set_options(ray_actor_options={"num_cpus": 0.1})
# Run the graph locally on the cluster
serve.start(detached=True)
serve.run(graph)
def run_graph(import_path: str, graph_env: dict,
deployment_override_options: List[Dict]):
"""Deploys a Serve application to the controller's Ray cluster."""
try:
from ray import serve
from ray.serve.api import build
# Import and build the graph
graph = import_attr(import_path)
app = build(graph)
# Override options for each deployment
for options in deployment_override_options:
name = options["name"]
# Merge graph-level and deployment-level runtime_envs
if "ray_actor_options" in options:
# If specified, get ray_actor_options from config
ray_actor_options = options["ray_actor_options"]
else:
# Otherwise, get options from graph code (and default to {} if code
# sets options to None)
ray_actor_options = app.deployments[
name].ray_actor_options or {}
deployment_env = ray_actor_options.get("runtime_env", {})
merged_env = override_runtime_envs_except_env_vars(
graph_env, deployment_env)
ray_actor_options.update({"runtime_env": merged_env})
options["ray_actor_options"] = ray_actor_options
# Update the deployment's options
app.deployments[name].set_options(**options)
# Run the graph locally on the cluster
serve.start(_override_controller_namespace="serve")
serve.run(app)
except KeyboardInterrupt:
# Error is raised when this task is canceled with ray.cancel(), which
# happens when deploy_app() is called.
logger.debug("Existing config deployment request terminated.")
def check_fruit_deployment_graph_updates():
"""Checks the graph after updating all prices to 0."""
assert requests.post("http://localhost:8000/", json=["MANGO",
1]).json() == 0
assert requests.post("http://localhost:8000/", json=["ORANGE",
1]).json() == 0
assert requests.post("http://localhost:8000/", json=["PEAR",
1]).json() == 0
# Test behavior from this documentation example
serve.start(detached=True)
app = build(deployment_graph)
for deployment in app.deployments.values():
deployment.set_options(ray_actor_options={"num_cpus": 0.1})
serve.run(app)
check_fruit_deployment_graph()
MangoStand.options(name="MangoStand", user_config={"price": 0}).deploy()
OrangeStand.options(user_config={"price": 0}).deploy()
PearStand.options(user_config={"price": 0}).deploy()
check_fruit_deployment_graph_updates()
print("Example ran successfully from the file.")
serve.shutdown()
# Check that deployments have been torn down
try:
requests.post("http://localhost:8000/", json=["MANGO", 1]).json()
raise ValueError("Deployments should have been torn down!")