Adapt flytekit ray plugin to kuberay 1.1.0

plugins/flytekit-ray/flytekitplugins/ray/models.py

@@ -191,12 +191,14 @@ class RayJob(_common.FlyteIdlEntity):
     def __init__(
         self,
         ray_cluster: RayCluster,
-        runtime_env: typing.Optional[str],
+        runtime_env: typing.Optional[str] = None,
+        runtime_env_yaml: typing.Optional[str] = None,
         ttl_seconds_after_finished: typing.Optional[int] = None,
         shutdown_after_job_finishes: bool = False,
     ):
         self._ray_cluster = ray_cluster
         self._runtime_env = runtime_env
+        self._runtime_env_yaml = runtime_env_yaml
         self._ttl_seconds_after_finished = ttl_seconds_after_finished
         self._shutdown_after_job_finishes = shutdown_after_job_finishes
 
@@ -208,6 +210,10 @@ def ray_cluster(self) -> RayCluster:
     def runtime_env(self) -> typing.Optional[str]:
         return self._runtime_env
 
+    @property
+    def runtime_env_yaml(self) -> typing.Optional[str]:
+        return self._runtime_env_yaml
+
     @property
     def ttl_seconds_after_finished(self) -> typing.Optional[int]:
         # ttl_seconds_after_finished specifies the number of seconds after which the RayCluster will be deleted after the RayJob finishes.
@@ -222,6 +228,7 @@ def to_flyte_idl(self) -> _ray_pb2.RayJob:
         return _ray_pb2.RayJob(
             ray_cluster=self.ray_cluster.to_flyte_idl(),
             runtime_env=self.runtime_env,
+            runtime_env_yaml=self.runtime_env_yaml,
             ttl_seconds_after_finished=self.ttl_seconds_after_finished,
             shutdown_after_job_finishes=self.shutdown_after_job_finishes,
         )
@@ -231,6 +238,7 @@ def from_flyte_idl(cls, proto: _ray_pb2.RayJob):
         return cls(
             ray_cluster=RayCluster.from_flyte_idl(proto.ray_cluster) if proto.ray_cluster else None,
             runtime_env=proto.runtime_env,
+            runtime_env_yaml=proto.runtime_env_yaml,
             ttl_seconds_after_finished=proto.ttl_seconds_after_finished,
             shutdown_after_job_finishes=proto.shutdown_after_job_finishes,
         )

plugins/flytekit-ray/flytekitplugins/ray/task.py

@@ -4,6 +4,7 @@
 from dataclasses import dataclass
 from typing import Any, Callable, Dict, Optional
 
+import yaml
 from flytekitplugins.ray.models import HeadGroupSpec, RayCluster, RayJob, WorkerGroupSpec
 from google.protobuf.json_format import MessageToDict
 
@@ -63,6 +64,11 @@ def post_execute(self, user_params: ExecutionParameters, rval: Any) -> Any:
     def get_custom(self, settings: SerializationSettings) -> Optional[Dict[str, Any]]:
         cfg = self._task_config
 
+        # Deprecated: runtime_env is removed KubeRay >= 1.1.0. It is replaced by runtime_env_yaml
+        runtime_env = base64.b64encode(json.dumps(cfg.runtime_env).encode()).decode() if cfg.runtime_env else None
+
+        runtime_env_yaml = yaml.dump(cfg.runtime_env) if cfg.runtime_env else None
+
         ray_job = RayJob(
             ray_cluster=RayCluster(
                 head_group_spec=HeadGroupSpec(cfg.head_node_config.ray_start_params) if cfg.head_node_config else None,
@@ -72,8 +78,8 @@ def get_custom(self, settings: SerializationSettings) -> Optional[Dict[str, Any]
                 ],
                 enable_autoscaling=cfg.enable_autoscaling if cfg.enable_autoscaling else False,
             ),
-            # Use base64 to encode runtime_env dict and convert it to byte string
-            runtime_env=base64.b64encode(json.dumps(cfg.runtime_env).encode()).decode(),
+            runtime_env=runtime_env,
+            runtime_env_yaml=runtime_env_yaml,
             ttl_seconds_after_finished=cfg.ttl_seconds_after_finished,
             shutdown_after_job_finishes=cfg.shutdown_after_job_finishes,
         )

plugins/flytekit-ray/tests/test_ray.py

@@ -2,6 +2,7 @@
 import json
 
 import ray
+import yaml
 from flytekitplugins.ray.models import RayCluster, RayJob, WorkerGroupSpec
 from flytekitplugins.ray.task import RayJobConfig, WorkerNodeConfig
 from google.protobuf.json_format import MessageToDict
@@ -42,6 +43,7 @@ def t1(a: int) -> str:
     ray_job_pb = RayJob(
         ray_cluster=RayCluster(worker_group_spec=[WorkerGroupSpec("test_group", 3, 0, 10)], enable_autoscaling=True),
         runtime_env=base64.b64encode(json.dumps({"pip": ["numpy"]}).encode()).decode(),
+        runtime_env_yaml=yaml.dump({"pip": ["numpy"]}),
         shutdown_after_job_finishes=True,
         ttl_seconds_after_finished=20,
     ).to_flyte_idl()