Merge pull request #18985 from jmchilton/workflow_request

Allow recovering a normalized version of workflow request state from API

.github/workflows/framework_workflows.yaml

@@ -16,6 +16,7 @@ on:
 env:
   GALAXY_TEST_DBURI: 'postgresql://postgres:postgres@localhost:5432/galaxy?client_encoding=utf8'
   GALAXY_TEST_RAISE_EXCEPTION_ON_HISTORYLESS_HDA: '1'
+  GALAXY_TEST_WORKFLOW_AFTER_RERUN: '1'
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: true

client/src/api/schema/schema.ts

@@ -2645,6 +2645,23 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/api/invocations/{invocation_id}/request": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /** Get a description modeling an API request to invoke this workflow - this is recreated and will be more specific in some ways than the initial creation request. */
+        get: operations["invocation_as_request_api_invocations__invocation_id__request_get"];
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/api/invocations/{invocation_id}/step_jobs_summary": {
         parameters: {
             query?: never;
@@ -12391,8 +12408,9 @@ export interface components {
              */
             batch: boolean | null;
             /**
-             * Dataset Map
-             * @description TODO
+             * Legacy Dataset Map
+             * @deprecated
+             * @description An older alternative to specifying inputs using database IDs, do not use this and use inputs instead
              * @default {}
              */
             ds_map: {
@@ -12415,12 +12433,12 @@ export interface components {
             history_id?: string | null;
             /**
              * Inputs
-             * @description TODO
+             * @description Specify values for formal inputs to the workflow
              */
             inputs?: Record<string, never> | null;
             /**
              * Inputs By
-             * @description How inputs maps to inputs (datasets/collections) to workflows steps.
+             * @description How the 'inputs' field maps its inputs (datasets/collections/step parameters) to workflows steps.
              */
             inputs_by?: string | null;
             /**
@@ -12447,35 +12465,35 @@ export interface components {
              */
             no_add_to_history: boolean | null;
             /**
-             * Parameters
-             * @description The raw parameters for the workflow invocation.
+             * Legacy Step Parameters
+             * @description Parameters specified per-step for the workflow invocation, this is legacy and you should generally use inputs and only specify the formal parameters of a workflow instead.
              * @default {}
              */
             parameters: Record<string, never> | null;
             /**
-             * Parameters Normalized
-             * @description Indicates if parameters are already normalized for workflow invocation.
+             * Legacy Step Parameters Normalized
+             * @description Indicates if legacy parameters are already normalized to be indexed by the order_index and are specified as a dictionary per step. Legacy-style parameters could previously be specified as one parameter per step or by tool ID.
              * @default false
              */
             parameters_normalized: boolean | null;
             /**
              * Preferred Intermediate Object Store ID
-             * @description The ID of the ? object store that should be used to store ? datasets in this history.
+             * @description The ID of the object store that should be used to store the intermediate datasets of this workflow -  - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences
              */
             preferred_intermediate_object_store_id?: string | null;
             /**
              * Preferred Object Store ID
-             * @description The ID of the object store that should be used to store new datasets in this history.
+             * @description The ID of the object store that should be used to store all datasets (can instead specify object store IDs for intermediate and outputs datasts separately) -  - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences
              */
             preferred_object_store_id?: string | null;
             /**
              * Preferred Outputs Object Store ID
-             * @description The ID of the object store that should be used to store ? datasets in this history.
+             * @description The ID of the object store that should be used to store the marked output datasets of this workflow - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences.
              */
             preferred_outputs_object_store_id?: string | null;
             /**
              * Replacement Parameters
-             * @description TODO
+             * @description Class of parameters mostly used for string replacement in PJAs. In best practice workflows, these should be replaced with input parameters
              * @default {}
              */
             replacement_params: Record<string, never> | null;
@@ -12487,7 +12505,7 @@ export interface components {
             require_exact_tool_versions: boolean | null;
             /**
              * Resource Parameters
-             * @description TODO
+             * @description If a workflow_resource_params_file file is defined and the target workflow is configured to consumer resource parameters, they can be specified with this parameter. See https://github.com/galaxyproject/galaxy/pull/4830 for more information.
              * @default {}
              */
             resource_params: Record<string, never> | null;
@@ -12496,11 +12514,6 @@ export interface components {
              * @description Scheduler to use for workflow invocation.
              */
             scheduler?: string | null;
-            /**
-             * Step Parameters
-             * @description TODO
-             */
-            step_parameters?: Record<string, never> | null;
             /**
              * Use cached job
              * @description Indicated whether to use a cached job for workflow invocation.
@@ -18194,6 +18207,86 @@ export interface components {
              */
             workflow_id: string;
         };
+        /**
+         * WorkflowInvocationRequestModel
+         * @description Model a workflow invocation request (InvokeWorkflowPayload) for an existing invocation.
+         */
+        WorkflowInvocationRequestModel: {
+            /**
+             * History ID
+             * @description The encoded history id the workflow was run in.
+             */
+            history_id: string;
+            /**
+             * Inputs
+             * @description Values for inputs
+             */
+            inputs: Record<string, never>;
+            /**
+             * Inputs by
+             * @description How the 'inputs' field maps its inputs (datasets/collections/step parameters) to workflows steps.
+             */
+            inputs_by: string;
+            /**
+             * Is instance
+             * @description This API yields a particular workflow instance, newer workflows belonging to the same storedworkflow may have different state.
+             * @default true
+             * @constant
+             * @enum {boolean}
+             */
+            instance: true;
+            /**
+             * Legacy Step Parameters
+             * @description Parameters specified per-step for the workflow invocation, this is legacy and you should generally use inputs and only specify the formal parameters of a workflow instead. If these are set, the workflow was not executed in a best-practice fashion and we the resulting invocation request may not fully reflect the executed workflow state.
+             */
+            parameters?: Record<string, never> | null;
+            /**
+             * Legacy Step Parameters Normalized
+             * @description Indicates if legacy parameters are already normalized to be indexed by the order_index and are specified as a dictionary per step. Legacy-style parameters could previously be specified as one parameter per step or by tool ID.
+             * @default true
+             * @constant
+             * @enum {boolean}
+             */
+            parameters_normalized: true;
+            /**
+             * Preferred Intermediate Object Store ID
+             * @description The ID of the object store that should be used to store the intermediate datasets of this workflow -  - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences
+             */
+            preferred_intermediate_object_store_id?: string | null;
+            /**
+             * Preferred Object Store ID
+             * @description The ID of the object store that should be used to store all datasets (can instead specify object store IDs for intermediate and outputs datasts separately) -  - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences
+             */
+            preferred_object_store_id?: string | null;
+            /**
+             * Preferred Outputs Object Store ID
+             * @description The ID of the object store that should be used to store the marked output datasets of this workflow - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences.
+             */
+            preferred_outputs_object_store_id?: string | null;
+            /**
+             * Replacement Parameters
+             * @description Class of parameters mostly used for string replacement in PJAs. In best practice workflows, these should be replaced with input parameters
+             * @default {}
+             */
+            replacement_params: Record<string, never> | null;
+            /**
+             * Resource Parameters
+             * @description If a workflow_resource_params_file file is defined and the target workflow is configured to consumer resource parameters, they can be specified with this parameter. See https://github.com/galaxyproject/galaxy/pull/4830 for more information.
+             * @default {}
+             */
+            resource_params: Record<string, never> | null;
+            /**
+             * Use cached job
+             * @description Indicated whether to use a cached job for workflow invocation.
+             * @default false
+             */
+            use_cached_job: boolean;
+            /**
+             * Workflow ID
+             * @description The encoded Workflow ID associated with the invocation.
+             */
+            workflow_id: string;
+        };
         /** WorkflowInvocationResponse */
         WorkflowInvocationResponse:
             | components["schemas"]["WorkflowInvocationElementView"]
@@ -27062,6 +27155,50 @@ export interface operations {
             };
         };
     };
+    invocation_as_request_api_invocations__invocation_id__request_get: {
+        parameters: {
+            query?: never;
+            header?: {
+                /** @description The user ID that will be used to effectively make this API call. Only admins and designated users can make API calls on behalf of other users. */
+                "run-as"?: string | null;
+            };
+            path: {
+                /** @description The encoded database identifier of the Invocation. */
+                invocation_id: string;
+            };
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Successful Response */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["WorkflowInvocationRequestModel"];
+                };
+            };
+            /** @description Request Error */
+            "4XX": {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["MessageExceptionModel"];
+                };
+            };
+            /** @description Server Error */
+            "5XX": {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["MessageExceptionModel"];
+                };
+            };
+        };
+    };
     invocation_step_jobs_summary_api_invocations__invocation_id__step_jobs_summary_get: {
         parameters: {
             query?: never;

lib/galaxy/model/__init__.py

@@ -7749,6 +7749,16 @@ class StoredWorkflow(Base, HasTags, Dictifiable, RepresentById, UsesCreateAndUpd
             raise galaxy.exceptions.RequestParameterInvalidException("Version does not exist")
         return list(reversed(self.workflows))[version]
 
+    def get_internal_version_by_id(self, workflow_instance_id: int):
+        sa_session = object_session(self)
+        assert sa_session
+        workflow = sa_session.get(Workflow, workflow_instance_id)
+        if not workflow:
+            raise galaxy.exceptions.ObjectNotFound()
+        elif workflow.stored_workflow != self:
+            raise galaxy.exceptions.RequestParameterInvalidException()
+        return workflow
+
     def version_of(self, workflow):
         for version, workflow_instance in enumerate(reversed(self.workflows)):
             if workflow_instance.id == workflow.id:
@@ -8015,7 +8025,7 @@ class WorkflowStep(Base, RepresentById, UsesCreateAndUpdateTime):
     type: Mapped[Optional[str]] = mapped_column(String(64))
     tool_id: Mapped[Optional[str]] = mapped_column(TEXT)
     tool_version: Mapped[Optional[str]] = mapped_column(TEXT)
-    tool_inputs: Mapped[Optional[bytes]] = mapped_column(JSONType)
+    tool_inputs: Mapped[Optional[Dict[str, Any]]] = mapped_column(JSONType)
     tool_errors: Mapped[Optional[bytes]] = mapped_column(JSONType)
     position: Mapped[Optional[bytes]] = mapped_column(MutableJSONType)
     config: Mapped[Optional[bytes]] = mapped_column(JSONType)
@@ -8085,11 +8095,13 @@ class WorkflowStep(Base, RepresentById, UsesCreateAndUpdateTime):
     def tool_uuid(self):
         return self.dynamic_tool and self.dynamic_tool.uuid
 
+    @property
+    def is_input_type(self) -> bool:
+        return bool(self.type and self.type in self.STEP_TYPE_TO_INPUT_TYPE)
+
     @property
     def input_type(self):
-        assert (
-            self.type and self.type in self.STEP_TYPE_TO_INPUT_TYPE
-        ), "step.input_type can only be called on input step types"
+        assert self.is_input_type, "step.input_type can only be called on input step types"
         return self.STEP_TYPE_TO_INPUT_TYPE[self.type]
 
     @property
@@ -8310,6 +8322,17 @@ class WorkflowStep(Base, RepresentById, UsesCreateAndUpdateTime):
             f"WorkflowStep[index={self.order_index},type={self.type},label={self.label},uuid={self.uuid},id={self.id}]"
         )
 
+    @property
+    def effective_label(self) -> Optional[str]:
+        label = self.label
+        if label is not None:
+            return label
+        elif self.is_input_type:
+            tool_inputs = self.tool_inputs
+            if tool_inputs is not None:
+                return cast(Optional[str], tool_inputs.get("name"))
+        return None
+
     def clear_module_extras(self):
         # the module code adds random dynamic state to the step, this
         # attempts to clear that.
@@ -9112,6 +9135,50 @@ class WorkflowInvocation(Base, UsesCreateAndUpdateTime, Dictifiable, Serializabl
             attach_step(request_to_content)
             self.input_step_parameters.append(request_to_content)
 
+    def recover_inputs(self) -> Tuple[Dict[str, Any], str]:
+        inputs = {}
+        inputs_by = "name"
+
+        have_referenced_steps_by_order_index = False
+
+        def best_step_reference(workflow_step: "WorkflowStep") -> str:
+            label = workflow_step.effective_label
+            if label is not None:
+                return label
+            nonlocal have_referenced_steps_by_order_index
+            have_referenced_steps_by_order_index = True
+            return str(workflow_step.order_index)
+
+        def ensure_step(step: Optional["WorkflowStep"]) -> "WorkflowStep":
+            if step is None:
+                raise galaxy.exceptions.InconsistentDatabase(
+                    "workflow input found without step definition, this should not happen"
+                )
+            assert step
+            return step
+
+        for input_dataset_assoc in self.input_datasets:
+            workflow_step = ensure_step(input_dataset_assoc.workflow_step)
+            input_dataset = input_dataset_assoc.dataset
+            input_index = best_step_reference(workflow_step)
+            inputs[input_index] = input_dataset
+
+        for input_dataset_collection_assoc in self.input_dataset_collections:
+            workflow_step = ensure_step(input_dataset_collection_assoc.workflow_step)
+            input_dataset_collection = input_dataset_collection_assoc.dataset_collection
+            input_index = best_step_reference(workflow_step)
+            inputs[input_index] = input_dataset_collection
+
+        for input_step_parameter_assoc in self.input_step_parameters:
+            workflow_step = ensure_step(input_step_parameter_assoc.workflow_step)
+            value = input_step_parameter_assoc.parameter_value
+            input_index = best_step_reference(workflow_step)
+            inputs[input_index] = value
+
+        if have_referenced_steps_by_order_index:
+            inputs_by = "name|step_index"
+        return inputs, inputs_by
+
     def add_message(self, message: "InvocationMessageUnion"):
         self.messages.append(
             WorkflowInvocationMessage(  # type:ignore[abstract]

lib/galaxy/schema/invocation.py

@@ -47,6 +47,19 @@ from galaxy.schema.schema import (
     UpdateTimeField,
     WithModelClass,
 )
+from .workflows import (
+    INPUTS_BY_DESCRIPTION,
+    PreferredIntermediateObjectStoreIdField,
+    PreferredObjectStoreIdField,
+    PreferredOutputsObjectStoreIdField,
+    ReplacementParametersField,
+    ResourceParametersField,
+    STEP_PARAMETERS_DESCRIPTION,
+    STEP_PARAMETERS_NORMALIZED_DESCRIPTION,
+    STEP_PARAMETERS_NORMALIZED_TITLE,
+    STEP_PARAMETERS_TITLE,
+    UseCachedJobField,
+)
 
 INVOCATION_STEP_OUTPUT_SRC = Literal["hda"]
 INVOCATION_STEP_COLLECTION_OUTPUT_SRC = Literal["hdca"]
@@ -531,13 +544,16 @@ class InvocationOutputCollection(InvocationIOBase):
     )
 
 
+InvocationWorkflowIdField = Field(
+    title="Workflow ID", description="The encoded Workflow ID associated with the invocation."
+)
+
+
 class WorkflowInvocationCollectionView(Model, WithModelClass):
     id: EncodedDatabaseIdField = InvocationIdField
     create_time: datetime = CreateTimeField
     update_time: datetime = UpdateTimeField
-    workflow_id: EncodedDatabaseIdField = Field(
-        title="Workflow ID", description="The encoded Workflow ID associated with the invocation."
-    )
+    workflow_id: EncodedDatabaseIdField = InvocationWorkflowIdField
     history_id: EncodedDatabaseIdField = Field(
         default=...,
         title="History ID",
@@ -583,6 +599,48 @@ class WorkflowInvocationResponse(RootModel):
     ]
 
 
+class WorkflowInvocationRequestModel(Model):
+    """Model a workflow invocation request (InvokeWorkflowPayload) for an existing invocation."""
+
+    history_id: str = Field(
+        ...,
+        title="History ID",
+        description="The encoded history id the workflow was run in.",
+    )
+    workflow_id: str = Field(title="Workflow ID", description="The encoded Workflow ID associated with the invocation.")
+    inputs: Dict[str, Any] = Field(
+        ...,
+        title="Inputs",
+        description="Values for inputs",
+    )
+    inputs_by: str = Field(
+        ...,
+        title="Inputs by",
+        description=INPUTS_BY_DESCRIPTION,
+    )
+    replacement_params: Optional[Dict[str, Any]] = ReplacementParametersField
+    resource_params: Optional[Dict[str, Any]] = ResourceParametersField
+    use_cached_job: bool = UseCachedJobField
+    preferred_object_store_id: Optional[str] = PreferredObjectStoreIdField
+    preferred_intermediate_object_store_id: Optional[str] = PreferredIntermediateObjectStoreIdField
+    preferred_outputs_object_store_id: Optional[str] = PreferredOutputsObjectStoreIdField
+    parameters_normalized: Literal[True] = Field(
+        True,
+        title=STEP_PARAMETERS_NORMALIZED_TITLE,
+        description=STEP_PARAMETERS_NORMALIZED_DESCRIPTION,
+    )
+    parameters: Optional[Dict[str, Any]] = Field(
+        None,
+        title=STEP_PARAMETERS_TITLE,
+        description=f"{STEP_PARAMETERS_DESCRIPTION} If these are set, the workflow was not executed in a best-practice fashion and we the resulting invocation request may not fully reflect the executed workflow state.",
+    )
+    instance: Literal[True] = Field(
+        True,
+        title="Is instance",
+        description="This API yields a particular workflow instance, newer workflows belonging to the same storedworkflow may have different state.",
+    )
+
+
 class InvocationJobsSummaryBaseModel(Model):
     id: EncodedDatabaseIdField = InvocationIdField
     states: Dict[JobState, int] = Field(

lib/galaxy/schema/workflows.py

@@ -1,6 +1,7 @@
 import json
 from typing import (
     Any,
+    cast,
     Dict,
     List,
     Optional,
@@ -8,6 +9,7 @@ from typing import (
 )
 
 from pydantic import (
+    AfterValidator,
     Field,
     field_validator,
 )
@@ -22,13 +24,73 @@ from galaxy.schema.schema import (
     Organization,
     PauseStep,
     Person,
-    PreferredObjectStoreIdField,
     StoredWorkflowSummary,
     SubworkflowStep,
     ToolStep,
     WorkflowInput,
 )
 
+TargetHistoryIdField = Field(
+    None,
+    title="History ID",
+    # description="The history to import the workflow into.",
+    description="The encoded history id into which to import.",
+)
+INPUTS_BY_DESCRIPTION = (
+    "How the 'inputs' field maps its inputs (datasets/collections/step parameters) to workflows steps."
+)
+STEP_PARAMETERS_NORMALIZED_TITLE = "Legacy Step Parameters Normalized"
+STEP_PARAMETERS_NORMALIZED_DESCRIPTION = "Indicates if legacy parameters are already normalized to be indexed by the order_index and are specified as a dictionary per step. Legacy-style parameters could previously be specified as one parameter per step or by tool ID."
+STEP_PARAMETERS_TITLE = "Legacy Step Parameters"
+STEP_PARAMETERS_DESCRIPTION = "Parameters specified per-step for the workflow invocation, this is legacy and you should generally use inputs and only specify the formal parameters of a workflow instead."
+ReplacementParametersField = Field(
+    {},
+    title="Replacement Parameters",
+    description="Class of parameters mostly used for string replacement in PJAs. In best practice workflows, these should be replaced with input parameters",
+)
+UseCachedJobField = Field(
+    False,
+    title="Use cached job",
+    description="Indicated whether to use a cached job for workflow invocation.",
+)
+PreferredObjectStoreIdField = Field(
+    default=None,
+    title="Preferred Object Store ID",
+    description="The ID of the object store that should be used to store all datasets (can instead specify object store IDs for intermediate and outputs datasts separately) -  - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences",
+)
+PreferredIntermediateObjectStoreIdField = Field(
+    None,
+    title="Preferred Intermediate Object Store ID",
+    description="The ID of the object store that should be used to store the intermediate datasets of this workflow -  - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences",
+)
+PreferredOutputsObjectStoreIdField = Field(
+    None,
+    title="Preferred Outputs Object Store ID",
+    description="The ID of the object store that should be used to store the marked output datasets of this workflow - Galaxy's job configuration may override this in some cases but this workflow preference will override tool and user preferences.",
+)
+ResourceParametersField = Field(
+    {},
+    title="Resource Parameters",
+    description="If a workflow_resource_params_file file is defined and the target workflow is configured to consumer resource parameters, they can be specified with this parameter. See https://github.com/galaxyproject/galaxy/pull/4830 for more information.",
+)
+
+VALID_INPUTS_BY_ITEMS = ["step_id", "step_index", "step_uuid", "name"]
+
+
+def validateInputsBy(inputsBy: Optional[str]) -> Optional[str]:
+    if inputsBy is not None:
+        if not isinstance(inputsBy, str):
+            raise ValueError(f"Invalid type for inputsBy {inputsBy}")
+        inputsByStr = cast(str, inputsBy)
+        inputsByArray: List[str] = inputsByStr.split("|")
+        for inputsByItem in inputsByArray:
+            if inputsByItem not in VALID_INPUTS_BY_ITEMS:
+                raise ValueError(f"Invalid inputsBy delineation {inputsByItem}")
+    return inputsBy
+
+
+InputsByValidator = AfterValidator(validateInputsBy)
+
 
 class GetTargetHistoryPayload(Model):
     # TODO - Are the descriptions correct?
@@ -38,12 +100,7 @@ class GetTargetHistoryPayload(Model):
         # description="The encoded history id - passed exactly like this 'hist_id=...' -  to import the workflow into. Or the name of the new history to import the workflow into.",
         description="The encoded history id - passed exactly like this 'hist_id=...' -  into which to import. Or the name of the new history into which to import.",
     )
-    history_id: Optional[str] = Field(
-        None,
-        title="History ID",
-        # description="The history to import the workflow into.",
-        description="The encoded history id into which to import.",
-    )
+    history_id: Optional[str] = TargetHistoryIdField
     new_history_name: Optional[str] = Field(
         None,
         title="New History Name",
@@ -85,15 +142,11 @@ class InvokeWorkflowPayload(GetTargetHistoryPayload):
         title="Allow tool state corrections",
         description="Indicates if tool state corrections are allowed for workflow invocation.",
     )
-    use_cached_job: Optional[bool] = Field(
-        False,
-        title="Use cached job",
-        description="Indicated whether to use a cached job for workflow invocation.",
-    )
+    use_cached_job: Optional[bool] = UseCachedJobField
     parameters_normalized: Optional[bool] = Field(
         False,
-        title="Parameters Normalized",
-        description="Indicates if parameters are already normalized for workflow invocation.",
+        title=STEP_PARAMETERS_NORMALIZED_TITLE,
+        description=STEP_PARAMETERS_NORMALIZED_DESCRIPTION,
     )
 
     @field_validator(
@@ -102,7 +155,6 @@ class InvokeWorkflowPayload(GetTargetHistoryPayload):
         "ds_map",
         "resource_params",
         "replacement_params",
-        "step_parameters",
         mode="before",
         check_fields=False,
     )
@@ -114,34 +166,22 @@ class InvokeWorkflowPayload(GetTargetHistoryPayload):
 
     parameters: Optional[Dict[str, Any]] = Field(
         {},
-        title="Parameters",
-        description="The raw parameters for the workflow invocation.",
+        title=STEP_PARAMETERS_TITLE,
+        description=STEP_PARAMETERS_DESCRIPTION,
     )
     inputs: Optional[Dict[str, Any]] = Field(
         None,
         title="Inputs",
-        description="TODO",
+        description="Specify values for formal inputs to the workflow",
     )
     ds_map: Optional[Dict[str, Dict[str, Any]]] = Field(
         {},
-        title="Dataset Map",
-        description="TODO",
-    )
-    resource_params: Optional[Dict[str, Any]] = Field(
-        {},
-        title="Resource Parameters",
-        description="TODO",
-    )
-    replacement_params: Optional[Dict[str, Any]] = Field(
-        {},
-        title="Replacement Parameters",
-        description="TODO",
-    )
-    step_parameters: Optional[Dict[str, Any]] = Field(
-        None,
-        title="Step Parameters",
-        description="TODO",
+        title="Legacy Dataset Map",
+        description="An older alternative to specifying inputs using database IDs, do not use this and use inputs instead",
+        deprecated=True,
     )
+    resource_params: Optional[Dict[str, Any]] = ResourceParametersField
+    replacement_params: Optional[Dict[str, Any]] = ReplacementParametersField
     no_add_to_history: Optional[bool] = Field(
         False,
         title="No Add to History",
@@ -152,11 +192,11 @@ class InvokeWorkflowPayload(GetTargetHistoryPayload):
         title="Legacy",
         description="Indicating if to use legacy workflow invocation.",
     )
-    inputs_by: Optional[str] = Field(
+    inputs_by: Annotated[Optional[str], InputsByValidator] = Field(
         None,
         title="Inputs By",
         # lib/galaxy/workflow/run_request.py - see line 60
-        description="How inputs maps to inputs (datasets/collections) to workflows steps.",
+        description=INPUTS_BY_DESCRIPTION,
     )
     effective_outputs: Optional[Any] = Field(
         None,
@@ -164,17 +204,9 @@ class InvokeWorkflowPayload(GetTargetHistoryPayload):
         # lib/galaxy/workflow/run_request.py - see line 455
         description="TODO",
     )
-    preferred_intermediate_object_store_id: Optional[str] = Field(
-        None,
-        title="Preferred Intermediate Object Store ID",
-        description="The ID of the ? object store that should be used to store ? datasets in this history.",
-    )
-    preferred_outputs_object_store_id: Optional[str] = Field(
-        None,
-        title="Preferred Outputs Object Store ID",
-        description="The ID of the object store that should be used to store ? datasets in this history.",
-    )
     preferred_object_store_id: Optional[str] = PreferredObjectStoreIdField
+    preferred_intermediate_object_store_id: Optional[str] = PreferredIntermediateObjectStoreIdField
+    preferred_outputs_object_store_id: Optional[str] = PreferredOutputsObjectStoreIdField
 
 
 class StoredWorkflowDetailed(StoredWorkflowSummary):

lib/galaxy/webapps/galaxy/api/workflows.py

@@ -64,6 +64,7 @@ from galaxy.schema.invocation import (
     InvocationStepJobsResponseJobModel,
     InvocationStepJobsResponseStepModel,
     InvocationUpdatePayload,
+    WorkflowInvocationRequestModel,
     WorkflowInvocationResponse,
 )
 from galaxy.schema.schema import (
@@ -1464,6 +1465,17 @@ class FastAPIInvocations:
         )
         return self.invocations_service.show(trans, invocation_id, serialization_params, eager=True)
 
+    @router.get(
+        "/api/invocations/{invocation_id}/request",
+        summary="Get a description modeling an API request to invoke this workflow - this is recreated and will be more specific in some ways than the initial creation request.",
+    )
+    def invocation_as_request(
+        self,
+        invocation_id: InvocationIDPathParam,
+        trans: ProvidesUserContext = DependsOnTrans,
+    ) -> WorkflowInvocationRequestModel:
+        return self.invocations_service.as_request(trans, invocation_id)
+
     @router.get(
         "/api/workflows/{workflow_id}/invocations/{invocation_id}",
         summary="Get detailed description of a workflow invocation.",

lib/galaxy/webapps/galaxy/services/invocations.py

@@ -1,3 +1,4 @@
+import json
 import logging
 from typing import (
     Any,
@@ -14,9 +15,13 @@ from galaxy.celery.tasks import (
 )
 from galaxy.exceptions import (
     AdminRequiredException,
+    InconsistentDatabase,
     ObjectNotFound,
 )
-from galaxy.managers.context import ProvidesHistoryContext
+from galaxy.managers.context import (
+    ProvidesHistoryContext,
+    ProvidesUserContext,
+)
 from galaxy.managers.histories import HistoryManager
 from galaxy.managers.jobs import (
     fetch_job_states,
@@ -24,8 +29,11 @@ from galaxy.managers.jobs import (
 )
 from galaxy.managers.workflows import WorkflowsManager
 from galaxy.model import (
+    HistoryDatasetAssociation,
+    HistoryDatasetCollectionAssociation,
     WorkflowInvocation,
     WorkflowInvocationStep,
+    WorkflowRequestInputParameter,
 )
 from galaxy.schema.fields import DecodedDatabaseIdField
 from galaxy.schema.invocation import (
@@ -33,6 +41,7 @@ from galaxy.schema.invocation import (
     InvocationSerializationParams,
     InvocationSerializationView,
     InvocationStep,
+    WorkflowInvocationRequestModel,
     WorkflowInvocationResponse,
 )
 from galaxy.schema.schema import (
@@ -133,6 +142,12 @@ class InvocationsService(ServiceBase, ConsumesModelStores):
         )
         return self.serialize_workflow_invocation(wfi, serialization_params)
 
+    def as_request(self, trans: ProvidesUserContext, invocation_id) -> WorkflowInvocationRequestModel:
+        wfi = self._workflows_manager.get_invocation(
+            trans, invocation_id, True, check_ownership=True, check_accessible=True
+        )
+        return self.serialize_workflow_invocation_to_request(trans, wfi)
+
     def cancel(self, trans, invocation_id, serialization_params):
         wfi = self._workflows_manager.request_invocation_cancellation(trans, invocation_id)
         return self.serialize_workflow_invocation(wfi, serialization_params)
@@ -252,3 +267,71 @@ class InvocationsService(ServiceBase, ConsumesModelStores):
             history=history,
         )
         return self.serialize_workflow_invocations(object_tracker.invocations_by_key.values(), serialization_params)
+
+    def serialize_workflow_invocation_to_request(
+        self, trans: ProvidesUserContext, invocation: WorkflowInvocation
+    ) -> WorkflowInvocationRequestModel:
+        history_id = trans.security.encode_id(invocation.history.id)
+        workflow_id = trans.security.encode_id(invocation.workflow.id)
+        inputs, inputs_by = invocation.recover_inputs()
+        export_inputs = {}
+        for key, value in inputs.items():
+            if isinstance(value, HistoryDatasetAssociation):
+                export_inputs[key] = {"src": "hda", "id": trans.security.encode_id(value.id)}
+            elif isinstance(value, HistoryDatasetCollectionAssociation):
+                export_inputs[key] = {"src": "hdca", "id": trans.security.encode_id(value.id)}
+            else:
+                export_inputs[key] = value
+
+        param_types = WorkflowRequestInputParameter.types
+        steps_by_id = invocation.workflow.steps_by_id
+
+        replacement_dict = {}
+        resource_params = {}
+        use_cached_job = False
+        preferred_object_store_id = None
+        preferred_intermediate_object_store_id = None
+        preferred_outputs_object_store_id = None
+        step_param_map: Dict[str, Dict] = {}
+        for parameter in invocation.input_parameters:
+            parameter_type = parameter.type
+
+            if parameter_type == param_types.REPLACEMENT_PARAMETERS:
+                replacement_dict[parameter.name] = parameter.value
+            elif parameter_type == param_types.META_PARAMETERS:
+                # copy_inputs_to_history is being skipped here sort of intentionally,
+                # we wouldn't want to include this on re-run.
+                if parameter.name == "use_cached_job":
+                    use_cached_job = parameter.value == "true"
+                if parameter.name == "preferred_object_store_id":
+                    preferred_object_store_id = parameter.value
+                if parameter.name == "preferred_intermediate_object_store_id":
+                    preferred_intermediate_object_store_id = parameter.value
+                if parameter.name == "preferred_outputs_object_store_id":
+                    preferred_outputs_object_store_id = parameter.value
+            elif parameter_type == param_types.RESOURCE_PARAMETERS:
+                resource_params[parameter.name] = parameter.value
+            elif parameter_type == param_types.STEP_PARAMETERS:
+                # TODO: test subworkflows and ensure this works
+                step_id: int
+                try:
+                    step_id = int(parameter.name)
+                except TypeError:
+                    raise InconsistentDatabase("saved workflow step parameters not in the format expected")
+                step_param_map[str(steps_by_id[step_id].order_index)] = json.loads(parameter.value)
+
+        return WorkflowInvocationRequestModel(
+            history_id=history_id,
+            workflow_id=workflow_id,
+            instance=True,  # this is a workflow ID and not a stored workflow ID
+            inputs=export_inputs,
+            inputs_by=inputs_by,
+            replacement_params=None if not replacement_dict else replacement_dict,
+            resource_params=None if not resource_params else resource_params,
+            use_cached_job=use_cached_job,
+            preferred_object_store_id=preferred_object_store_id,
+            preferred_intermediate_object_store_id=preferred_intermediate_object_store_id,
+            preferred_outputs_object_store_id=preferred_outputs_object_store_id,
+            parameters_normalized=True,
+            parameters=None if not step_param_map else step_param_map,
+        )

lib/galaxy/webapps/galaxy/services/workflows.py

@@ -131,7 +131,10 @@ class WorkflowsService(ServiceBase):
         by_stored_id = not payload.instance
         stored_workflow = self._workflows_manager.get_stored_accessible_workflow(trans, workflow_id, by_stored_id)
         version = payload.version
-        workflow = stored_workflow.get_internal_version(version)
+        if version is None and payload.instance:
+            workflow = stored_workflow.get_internal_version_by_id(workflow_id)
+        else:
+            workflow = stored_workflow.get_internal_version(version)
         run_configs = build_workflow_run_configs(trans, workflow, payload.model_dump(exclude_unset=True))
         is_batch = payload.batch
         if not is_batch and len(run_configs) != 1:

lib/galaxy/workflow/extract.py

@@ -116,7 +116,7 @@ def extract_steps(
         if name not in step_labels:
             step.label = name
             step_labels.add(name)
-        step.tool_inputs = dict(name=name)  # type:ignore[assignment]
+        step.tool_inputs = dict(name=name)
         hid_to_output_pair[hid] = (step, "output")
         steps.append(step)
     for i, hid in enumerate(dataset_collection_ids):
@@ -132,7 +132,7 @@ def extract_steps(
         if name not in step_labels:
             step.label = name
             step_labels.add(name)
-        step.tool_inputs = dict(name=name, collection_type=collection_type)  # type:ignore[assignment]
+        step.tool_inputs = dict(name=name, collection_type=collection_type)
         hid_to_output_pair[hid] = (step, "output")
         steps.append(step)
     # Tool steps

lib/galaxy/workflow/run_request.py

@@ -121,7 +121,9 @@ def _normalize_inputs(
             elif inputs_by_el == "step_uuid":
                 possible_input_keys.append(str(step.uuid))
             elif inputs_by_el == "name":
-                possible_input_keys.append(step.label or step.tool_inputs.get("name"))  # type:ignore[union-attr]
+                label = step.effective_label
+                if label:
+                    possible_input_keys.append(label)
             else:
                 raise exceptions.MessageException(
                     "Workflow cannot be run because unexpected inputs_by value specified."
@@ -317,7 +319,7 @@ def build_workflow_run_configs(
     add_to_history = "no_add_to_history" not in payload
     legacy = payload.get("legacy", False)
     already_normalized = payload.get("parameters_normalized", False)
-    raw_parameters = payload.get("parameters", {})
+    raw_parameters = payload.get("parameters") or {}
     requires_materialization: bool = False
     run_configs = []
     unexpanded_param_map = _normalize_step_parameters(

lib/galaxy_test/api/test_workflows.py

@@ -3460,6 +3460,31 @@ input_c:
         invocation_id = run_workflow_response.json()["id"]
         self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
 
+    def test_workflow_request_recover(self):
+        workflow = self.workflow_populator.load_workflow(name="test_for_queue")
+        workflow_request, history_id, workflow_id = self._setup_workflow_run(workflow)
+        run_workflow_response = self.workflow_populator.invoke_workflow_raw(
+            workflow_id, workflow_request, assert_ok=True
+        )
+        invocation_id = run_workflow_response.json()["id"]
+        self.workflow_populator.wait_for_invocation_and_jobs(history_id, workflow_id, invocation_id)
+        request = self.workflow_populator.invocation_to_request(invocation_id)
+        assert request["history_id"] == history_id
+        assert request["replacement_params"] is None
+        assert request["use_cached_job"] is False
+        assert request["preferred_object_store_id"] is None
+        assert request["preferred_intermediate_object_store_id"] is None
+        assert request["preferred_outputs_object_store_id"] is None
+        assert request["parameters_normalized"] is True
+        assert request["parameters"] is None
+
+        assert request["inputs"]["WorkflowInput1"]["src"] == "hda"
+        encoded_id = request["inputs"]["WorkflowInput1"]["id"]
+        assert self.dataset_populator.get_history_dataset_content(history_id, dataset_id=encoded_id).strip() == "1 2 3"
+        assert request["inputs"]["WorkflowInput2"]["src"] == "hda"
+        encoded_id = request["inputs"]["WorkflowInput2"]["id"]
+        assert self.dataset_populator.get_history_dataset_content(history_id, dataset_id=encoded_id).strip() == "4 5 6"
+
     def test_workflow_new_autocreated_history(self):
         workflow = self.workflow_populator.load_workflow(name="test_for_new_autocreated_history")
         workflow_request, history_id, workflow_id = self._setup_workflow_run(workflow)
@@ -4898,7 +4923,7 @@ test_data:
 
     def test_run_with_optional_collection_specified(self):
         with self.dataset_populator.test_history() as history_id:
-            self._run_jobs(
+            result = self._run_workflow(
                 WORKFLOW_OPTIONAL_TRUE_INPUT_COLLECTION,
                 test_data="""
 input1:
@@ -4919,6 +4944,12 @@ input1:
             content = self.dataset_populator.get_history_dataset_content(history_id)
             assert "GAATTGATCAGGACATAGGACAACTGTAGGCACCAT" in content
 
+            invocation_id = result.invocation_id
+            request = self.workflow_populator.invocation_to_request(invocation_id)
+            assert request["history_id"] == history_id
+            assert request["inputs"]["input1"]["src"] == "hdca"
+            assert request["inputs"]["input1"]["id"]
+
     def test_run_with_optional_collection_unspecified(self):
         with self.dataset_populator.test_history() as history_id:
             self._run_jobs(
@@ -5008,9 +5039,14 @@ int_input:
             # self.dataset_populator.wait_for_history(history_id, assert_ok=True)
             content = self.dataset_populator.get_history_dataset_content(history_id)
             assert len(content.splitlines()) == 1, content
-            invocation = self.workflow_populator.get_invocation(run_response.invocation_id)
+            invocation_id = run_response.invocation_id
+            invocation = self.workflow_populator.get_invocation(invocation_id)
             assert invocation["input_step_parameters"]["int_input"]["parameter_value"] == 1
 
+            request = self.workflow_populator.invocation_to_request(invocation_id)
+            assert request["history_id"] == history_id
+            assert request["inputs"]["int_input"] == 1
+
             run_response = self._run_workflow(
                 WORKFLOW_PARAMETER_INPUT_INTEGER_OPTIONAL,
                 test_data="""
@@ -5359,6 +5395,10 @@ steps:
                 workflow_id, new_workflow_request, assert_ok=True
             ).json()
             invocation_id = new_workflow_response["id"]
+
+            request = self.workflow_populator.invocation_to_request(invocation_id)
+            assert request["use_cached_job"] is True
+
             self.workflow_populator.wait_for_invocation_and_jobs(history_id_two, workflow_id, invocation_id)
 
             # get_history_dataset_details defaults to last item in history, so since we've done
@@ -5558,6 +5598,9 @@ outer_input:
         content = self.dataset_populator.get_history_dataset_details(history_id, wait=True, assert_ok=True)
         assert content["name"] == "foo was replaced"
 
+        request = self.workflow_populator.invocation_to_request(invocation_id)
+        assert request["replacement_params"]["replaceme"] == "was replaced"
+
     @skip_without_tool("hidden_param")
     def test_hidden_param_in_workflow(self):
         with self.dataset_populator.test_history() as history_id:
@@ -7060,7 +7103,7 @@ outputs:
     @skip_without_tool("random_lines1")
     def test_run_replace_params_over_default(self):
         with self.dataset_populator.test_history() as history_id:
-            self._run_jobs(
+            wf_run = self._run_workflow(
                 WORKFLOW_ONE_STEP_DEFAULT,
                 test_data="""
 step_parameters:
@@ -7078,6 +7121,13 @@ input:
             result = self.dataset_populator.get_history_dataset_content(history_id)
             assert result.count("\n") == 4
 
+            request = self.workflow_populator.invocation_to_request(wf_run.invocation_id)
+            assert request["parameters"]["1"]["num_lines"] == 4
+
+            self.workflow_populator.rerun(wf_run)
+            result = self.dataset_populator.get_history_dataset_content(history_id)
+            assert result.count("\n") == 4
+
     @skip_without_tool("random_lines1")
     def test_defaults_editor(self):
         workflow_id = self._upload_yaml_workflow(WORKFLOW_ONE_STEP_DEFAULT, publish=True)

lib/galaxy_test/base/populators.py

@@ -1996,7 +1996,7 @@ class BaseWorkflowPopulator(BasePopulator):
         url = f"workflows/{workflow_id}/invocations"
         invocation_response = self._post(url, data=request, json=True)
         if assert_ok:
-            invocation_response.raise_for_status()
+            api_asserts.assert_status_code_is_ok(invocation_response)
         return invocation_response
 
     def invoke_workflow(
@@ -2085,6 +2085,11 @@ class BaseWorkflowPopulator(BasePopulator):
         else:
             return ordered_load(response.text)
 
+    def invocation_to_request(self, invocation_id: str):
+        request_response = self._get(f"invocations/{invocation_id}/request")
+        api_asserts.assert_status_code_is_ok(request_response)
+        return request_response.json()
+
     def set_tags(self, workflow_id: str, tags: List[str]) -> None:
         update_payload = {"tags": tags}
         response = self.update_workflow(workflow_id, update_payload)
@@ -2183,7 +2188,51 @@ class BaseWorkflowPopulator(BasePopulator):
             workflow_request.update(extra_invocation_kwds)
         if has_uploads:
             self.dataset_populator.wait_for_history(history_id, assert_ok=True)
+
+        return self._request_to_summary(
+            history_id,
+            workflow_id,
+            workflow_request,
+            inputs=inputs,
+            wait=wait,
+            assert_ok=assert_ok,
+            invocations=invocations,
+            expected_response=expected_response,
+        )
+
+    def rerun(self, run_jobs_summary: "RunJobsSummary", wait: bool = True, assert_ok: bool = True) -> "RunJobsSummary":
+        history_id = run_jobs_summary.history_id
+        invocation_id = run_jobs_summary.invocation_id
+        inputs = run_jobs_summary.inputs
+        workflow_request = self.invocation_to_request(invocation_id)
+        workflow_id = workflow_request["workflow_id"]
+        assert workflow_request["history_id"] == history_id
+        assert workflow_request["instance"] is True
+        return self._request_to_summary(
+            history_id,
+            workflow_id,
+            workflow_request,
+            inputs=inputs,
+            wait=wait,
+            assert_ok=assert_ok,
+            invocations=1,
+            expected_response=200,
+        )
+
+    def _request_to_summary(
+        self,
+        history_id: str,
+        workflow_id: str,
+        workflow_request: Dict[str, Any],
+        inputs,
+        wait: bool,
+        assert_ok: bool,
+        invocations: int,
+        expected_response: int,
+    ):
+        workflow_populator = self
         assert invocations > 0
+
         jobs = []
         for _ in range(invocations):
             invocation_response = workflow_populator.invoke_workflow_raw(workflow_id, workflow_request)
@@ -2199,6 +2248,7 @@ class BaseWorkflowPopulator(BasePopulator):
                 if wait:
                     workflow_populator.wait_for_workflow(workflow_id, invocation_id, history_id, assert_ok=assert_ok)
                 jobs.extend(self.dataset_populator.invocation_jobs(invocation_id))
+
         return RunJobsSummary(
             history_id=history_id,
             workflow_id=workflow_id,

lib/galaxy_test/workflow/test_framework_workflows.py

@@ -21,6 +21,7 @@ from galaxy.tool_util.verify.interactor import (
     get_metadata_to_test,
     verify_collection,
 )
+from galaxy.util import asbool
 from galaxy_test.api._framework import ApiTestCase
 from galaxy_test.base.populators import (
     DatasetCollectionPopulator,
@@ -30,6 +31,7 @@ from galaxy_test.base.populators import (
 )
 
 SCRIPT_DIRECTORY = os.path.abspath(os.path.dirname(__file__))
+TEST_WORKFLOW_AFTER_RERUN = asbool(os.environ.get("GALAXY_TEST_WORKFLOW_AFTER_RERUN", "0"))
 
 
 def find_workflows():
@@ -67,6 +69,8 @@ class TestWorkflow(ApiTestCase):
                 test_data=test_job["job"],
                 history_id=history_id,
             )
+            if TEST_WORKFLOW_AFTER_RERUN:
+                run_summary = self.workflow_populator.rerun(run_summary)
             self._verify(run_summary, test_job["outputs"])
 
     def _verify(self, run_summary: RunJobsSummary, output_definitions: OutputsDict):

test/integration/objectstore/test_selection_with_user_preferred_object_store.py

@@ -244,17 +244,22 @@ class TestObjectStoreSelectionWithPreferredObjectStoresIntegration(BaseObjectSto
 
     def test_workflow_objectstore_selection(self):
         with self.dataset_populator.test_history() as history_id:
-            output_dict, intermediate_dict = self._run_workflow_get_output_storage_info_dicts(history_id)
+            output_dict, intermediate_dict, _ = self._run_workflow_get_output_storage_info_dicts(history_id)
             assert_storage_name_is(output_dict, "Default Store")
             assert_storage_name_is(intermediate_dict, "Default Store")
 
-            output_dict, intermediate_dict = self._run_workflow_get_output_storage_info_dicts(
+            output_dict, intermediate_dict, wf_run = self._run_workflow_get_output_storage_info_dicts(
                 history_id, {"preferred_object_store_id": "static"}
             )
             assert_storage_name_is(output_dict, "Static Storage")
             assert_storage_name_is(intermediate_dict, "Static Storage")
 
-            output_dict, intermediate_dict = self._run_workflow_get_output_storage_info_dicts(
+            request = self.workflow_populator.invocation_to_request(wf_run.invocation_id)
+            assert request["preferred_object_store_id"] == "static"
+            assert request["preferred_outputs_object_store_id"] is None
+            assert request["preferred_intermediate_object_store_id"] is None
+
+            output_dict, intermediate_dict, wf_run = self._run_workflow_get_output_storage_info_dicts(
                 history_id,
                 {
                     "preferred_outputs_object_store_id": "static",
@@ -264,6 +269,11 @@ class TestObjectStoreSelectionWithPreferredObjectStoresIntegration(BaseObjectSto
             assert_storage_name_is(output_dict, "Static Storage")
             assert_storage_name_is(intermediate_dict, "Dynamic EBS")
 
+            request = self.workflow_populator.invocation_to_request(wf_run.invocation_id)
+            assert request["preferred_object_store_id"] is None
+            assert request["preferred_outputs_object_store_id"] == "static"
+            assert request["preferred_intermediate_object_store_id"] == "dynamic_ebs"
+
     def test_simple_subworkflow_objectstore_selection(self):
         with self.dataset_populator.test_history() as history_id:
             output_dict, intermediate_dict = self._run_simple_nested_workflow_get_output_storage_info_dicts(
@@ -428,7 +438,6 @@ class TestObjectStoreSelectionWithPreferredObjectStoresIntegration(BaseObjectSto
             extra_invocation_kwds=extra_invocation_kwds,
         )
         jobs = wf_run.jobs_for_tool("cat1")
-        print(jobs)
         assert len(jobs) == 2
 
         intermediate_info = self._storage_info_for_job_id(jobs[1]["id"])
@@ -448,11 +457,10 @@ class TestObjectStoreSelectionWithPreferredObjectStoresIntegration(BaseObjectSto
             extra_invocation_kwds=extra_invocation_kwds,
         )
         jobs = wf_run.jobs_for_tool("cat")
-        print(jobs)
         assert len(jobs) == 2
         output_info = self._storage_info_for_job_id(jobs[0]["id"])
         intermediate_info = self._storage_info_for_job_id(jobs[1]["id"])
-        return output_info, intermediate_info
+        return output_info, intermediate_info, wf_run
 
     def _storage_info_for_job_id(self, job_id: str) -> Dict[str, Any]:
         job_dict = self.dataset_populator.get_job_details(job_id, full=True).json()

test/unit/data/model/test_model_store.py

@@ -1066,7 +1066,7 @@ def _setup_collection_invocation(app):
     workflow_step_1 = model.WorkflowStep()
     workflow_step_1.order_index = 0
     workflow_step_1.type = "data_collection_input"
-    workflow_step_1.tool_inputs = {}  # type:ignore[assignment]
+    workflow_step_1.tool_inputs = {}
     sa_session.add(workflow_step_1)
     workflow_1 = _workflow_from_steps(u, [workflow_step_1])
     workflow_1.license = "MIT"
@@ -1092,7 +1092,7 @@ def _setup_simple_invocation(app):
     workflow_step_1 = model.WorkflowStep()
     workflow_step_1.order_index = 0
     workflow_step_1.type = "data_input"
-    workflow_step_1.tool_inputs = {}  # type:ignore[assignment]
+    workflow_step_1.tool_inputs = {}
     sa_session.add(workflow_step_1)
     workflow = _workflow_from_steps(u, [workflow_step_1])
     workflow.license = "MIT"