feat(cli): add version info to ado get operators

orchestrator/cli/resources/operator/get.py

@@ -43,6 +43,9 @@ def get_operator(parameters: AdoGetCommandParameters) -> None:
         for function_name in collection.function_operations:
             entry = {
                 "OPERATOR": function_name,
+                "VERSION": collection.function_operation_versions.get(
+                    function_name, ""
+                ),
                 "TYPE": collection.type.value,
             }
             if parameters.show_details:

orchestrator/modules/operators/randomwalk.py

@@ -8,6 +8,7 @@
 import uuid
 from builtins import anext
 from collections.abc import AsyncGenerator
+from importlib.metadata import version
 from queue import Empty, Queue
 from typing import Annotated, Literal
 
@@ -986,6 +987,7 @@ def operationType(cls) -> DiscoveryOperationEnum:
     description=RandomWalk.description(),
     configuration_model=RandomWalkParameters,
     configuration_model_default=RandomWalkParameters(),
+    version=version("ado-core"),
 )
 def random_walk(
     discoverySpace: DiscoverySpace,

plugins/operators/no-priors-characterization/src/no_priors_characterization/operator.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: MIT
 
 import logging
+from importlib.metadata import version
 
 from no_priors_characterization.no_priors_pydantic import NoPriorsParameters
 from orchestrator.core.discoveryspace.space import DiscoverySpace
@@ -22,6 +23,7 @@
                 model knowledge or feature importance. This operator is useful for initial
                 exploration of discovery spaces when no training data exists yet.
                 """,
+    version=version("ado-no-priors-characterization"),
 )
 def no_priors_characterization(
     discoverySpace: DiscoverySpace = None,  # type: ignore[name-defined]

plugins/operators/profile_space/profile_space/operator.py

@@ -1,6 +1,6 @@
 # Copyright IBM Corporation 2025, 2026
 # SPDX-License-Identifier: MIT
-
+from importlib.metadata import version
 
 import pandas as pd
 
@@ -17,6 +17,7 @@
     configuration_model=None,  # You can use this field to define the option of your operator if any - see https://ibm.github.io/ado/operators/creating-operators/#describing-your-operation-input-parameters
     configuration_model_default=None,  # Use this field to provide default/example values for your operator
     description="Returns a ydata_profiling ProfileReport for the space",
+    version=version("ado-core"),
 )
 # operator function can have any name but have similar parameters - see https://ibm.github.io/ado/operators/creating-operators/#operator-function-parameters
 def profile(

plugins/operators/ray_tune/ado_ray_tune/operator.py

@@ -1002,7 +1002,7 @@ def operationIdentifier(self) -> str:
     def operatorIdentifier(cls) -> str:
         from importlib.metadata import version
 
-        version = version("ado-core")
+        version = version("ado-ray-tune")
 
         return f"raytune-{version}"
 

plugins/operators/ray_tune/ado_ray_tune/operator_function.py

@@ -1,6 +1,6 @@
 # Copyright IBM Corporation 2025, 2026
 # SPDX-License-Identifier: MIT
-
+from importlib.metadata import version
 
 import orchestrator.core
 import orchestrator.modules.module
@@ -21,6 +21,7 @@
     description=RayTune.description(),
     configuration_model=RayTuneConfiguration,
     configuration_model_default=RayTune.defaultOperationParameters(),
+    version=version("ado-ray-tune"),
 )
 def ray_tune(
     discoverySpace: DiscoverySpace,

plugins/operators/ray_tune/ado_ray_tune/rifferla.py

@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: MIT
 
 import typing
+from importlib.metadata import version
 from typing import Annotated
 
 import pydantic
@@ -93,6 +94,7 @@ def defaultOperationParameters(cls) -> "RifferlaParameters":
     "It does this by identifying which entity space dimensions should be fixed to set values, which explored, and setting range limits for those dimensions. "
     "The method leverages Mutual Information to identify dimensions correlated with the desired observed property.",
     configuration_model_default=RifferlaParameters.defaultOperationParameters(),
+    version=version("ado-ray-tune"),
 )
 def rifferla(
     discoverySpace: DiscoverySpace,

plugins/operators/trim/src/trim/operator.py

@@ -3,6 +3,7 @@
 
 
 import logging
+from importlib.metadata import version
 
 from no_priors_characterization.utils import get_source_and_target
 
@@ -31,6 +32,7 @@
                 Retrieves all measured entities from the entity source and samples the others following a certain order.
                 If the number of measured entity is too small, Trim instantiates a no-priors characterization operation.
                 """,
+    version=version("ado-trim"),
 )
 def trim(
     discoverySpace: DiscoverySpace = None,  # type: ignore[name-defined]