move to wf_api: Runtime dependencies
This commit is contained in:
@@ -23,6 +23,8 @@ from .wrapper_hints import (
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wrapper_hints_for_capability,
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)
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from .runtime_dependencies import RuntimeDependencies, resolve_runtime_dependencies
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__all__ = [
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"DEFAULT_CALL_STEP_ID",
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"DEFAULT_ERROR_OUTCOME",
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@@ -36,6 +38,7 @@ __all__ = [
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"OutcomeCandidate",
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"OutcomeCandidateKind",
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"RUNTIME_ERROR_CAPABILITY",
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"RuntimeDependencies",
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"TraceRange",
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"WorkflowApi",
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"WorkflowApiBackend",
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@@ -46,4 +49,5 @@ __all__ = [
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"parse_workflow_surface_capability_id",
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"workflow_output_schema_for_authoring",
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"wrapper_hints_for_capability",
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"resolve_runtime_dependencies",
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]
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@@ -0,0 +1,153 @@
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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from wf_artifacts import RequiredCapability, WorkflowArtifact, WorkflowDeployment
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from wf_authoring import AsyncRegistryHandler, NodeSpec, build_async_registry
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from wf_core.runtime.ops.merges import ReducerDefinition
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from wf_platform import CapabilityRef, CapabilitySource
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@dataclass(frozen=True, slots=True)
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class RuntimeDependencies:
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"""Executable dependencies resolved for one workflow run."""
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node_specs: dict[str, NodeSpec[Any, Any]]
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node_name_bindings: dict[str, str]
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node_registry: dict[str, AsyncRegistryHandler]
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reducers: dict[str, ReducerDefinition]
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def resolve_runtime_dependencies(
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*,
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artifact: WorkflowArtifact,
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deployment: WorkflowDeployment | None,
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sources: dict[str, CapabilitySource],
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plan_node_names: list[str],
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) -> RuntimeDependencies:
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"""Resolve source-owned specs and reducers into runtime callables.
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Node names in stored plans are still concrete today, so node specs resolve
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by exact plan names. Reducers are already logical artifact dependencies, so
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they resolve through deployment bindings and are registered under the
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logical reducer name used by the workflow state schema.
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"""
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node_specs: dict[str, NodeSpec[Any, Any]] = {}
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node_name_bindings: dict[str, str] = {}
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for node_name in dict.fromkeys(plan_node_names):
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concrete_name, spec = _resolve_node_spec(
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node_name=node_name,
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deployment=deployment,
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sources=sources,
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)
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node_name_bindings[node_name] = concrete_name
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node_specs[concrete_name] = spec
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reducers = _resolve_reducers(
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required_capabilities=artifact.required_capability_map(),
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deployment=deployment,
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sources=sources,
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)
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return RuntimeDependencies(
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node_specs=node_specs,
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node_name_bindings=node_name_bindings,
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node_registry=build_async_registry(*node_specs.values()),
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reducers=reducers,
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)
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def _resolve_node_spec(
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*,
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node_name: str,
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deployment: WorkflowDeployment | None,
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sources: dict[str, CapabilitySource],
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) -> tuple[str, NodeSpec[Any, Any]]:
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concrete = _find_node_spec(node_name, sources)
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if concrete is not None:
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return node_name, concrete
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if deployment is not None:
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for bound_name in _bound_node_names(node_name, deployment.binding_map()):
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concrete = _find_node_spec(bound_name, sources)
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if concrete is not None:
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return bound_name, concrete
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raise KeyError(f"unknown node spec {node_name!r}")
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def _bound_node_names(
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node_name: str,
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bindings: dict[str, str],
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) -> tuple[str, ...]:
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"""Return concrete names made by replacing known logical source prefixes.
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CapabilityRef parses by splitting on the last dot, which is correct for
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simple tool names but wrong for local names that also contain dots
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(`demo.foo.bar` with logical source `demo`). Runtime binding is source-aware:
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deployment bindings define the allowed source prefixes, and everything after
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the matched prefix remains the local capability name.
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"""
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candidates: list[str] = []
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for logical_source, concrete_source in sorted(
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bindings.items(),
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key=lambda item: len(item[0]),
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reverse=True,
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):
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prefix = f"{logical_source}."
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if node_name.startswith(prefix):
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candidates.append(f"{concrete_source}.{node_name[len(prefix) :]}")
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return tuple(candidates)
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def _find_node_spec(
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node_name: str,
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sources: dict[str, CapabilitySource],
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) -> NodeSpec[Any, Any] | None:
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for source in sources.values():
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spec = source.capabilities.node_specs.get(node_name)
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if spec is not None:
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return spec
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return None
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def _resolve_reducers(
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*,
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required_capabilities: dict[str, RequiredCapability],
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deployment: WorkflowDeployment | None,
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sources: dict[str, CapabilitySource],
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) -> dict[str, ReducerDefinition]:
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reducers: dict[str, ReducerDefinition] = {}
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if deployment is None:
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return reducers
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for logical_ref, required in required_capabilities.items():
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if required.kind != "reducer":
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continue
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bound_source_id = deployment.binding_map().get(required.logical_source)
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if bound_source_id is None:
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continue
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source = sources.get(bound_source_id)
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if source is None:
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continue
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definition = _find_reducer_definition(
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source=source,
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capability_name=required.capability_name,
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)
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if definition is not None:
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reducers[logical_ref] = definition
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return reducers
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def _find_reducer_definition(
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*,
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source: CapabilitySource,
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capability_name: str,
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) -> ReducerDefinition | None:
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for reducer_name, definition in source.capabilities.reducer_definitions.items():
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try:
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reducer_ref = CapabilityRef.parse(reducer_name)
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except ValueError:
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continue
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if reducer_ref.name == capability_name:
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return definition
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return None
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@@ -55,7 +55,7 @@ from ...shared.errors import error_payload
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from ...shared.names import RESERVED_CONNECTION_IDS
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from ...storage import Store
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from ...workflow.wrappers import _model_from_schema
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from ...workflow_surface.runtime_dependencies import resolve_runtime_dependencies
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from wf_api.runtime_dependencies import resolve_runtime_dependencies
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from ...workflow_surface.saved_subgraphs import (
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SavedSubgraphTree,
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prepare_saved_subgraphs,
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@@ -1,153 +1,17 @@
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"""Compatibility shim for workflow runtime dependency resolution.
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New code should import from `wf_api.runtime_dependencies`. This module stays so
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older MCP workflow-surface imports keep working during extraction.
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Any
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from wf_artifacts import RequiredCapability, WorkflowArtifact, WorkflowDeployment
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from wf_authoring import AsyncRegistryHandler, NodeSpec, build_async_registry
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from wf_core.runtime.ops.merges import ReducerDefinition
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from wf_platform import CapabilityRef, CapabilitySource
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@dataclass(frozen=True, slots=True)
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class RuntimeDependencies:
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"""Executable dependencies resolved for one workflow run."""
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node_specs: dict[str, NodeSpec[Any, Any]]
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node_name_bindings: dict[str, str]
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node_registry: dict[str, AsyncRegistryHandler]
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reducers: dict[str, ReducerDefinition]
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def resolve_runtime_dependencies(
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*,
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artifact: WorkflowArtifact,
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deployment: WorkflowDeployment | None,
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sources: dict[str, CapabilitySource],
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plan_node_names: list[str],
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) -> RuntimeDependencies:
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"""Resolve source-owned specs and reducers into runtime callables.
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Node names in stored plans are still concrete today, so node specs resolve
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by exact plan names. Reducers are already logical artifact dependencies, so
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they resolve through deployment bindings and are registered under the
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logical reducer name used by the workflow state schema.
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"""
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node_specs: dict[str, NodeSpec[Any, Any]] = {}
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node_name_bindings: dict[str, str] = {}
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for node_name in dict.fromkeys(plan_node_names):
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concrete_name, spec = _resolve_node_spec(
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node_name=node_name,
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deployment=deployment,
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sources=sources,
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)
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node_name_bindings[node_name] = concrete_name
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node_specs[concrete_name] = spec
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reducers = _resolve_reducers(
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required_capabilities=artifact.required_capability_map(),
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deployment=deployment,
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sources=sources,
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)
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return RuntimeDependencies(
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node_specs=node_specs,
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node_name_bindings=node_name_bindings,
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node_registry=build_async_registry(*node_specs.values()),
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reducers=reducers,
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from wf_api.runtime_dependencies import ( # noqa: F401
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RuntimeDependencies,
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resolve_runtime_dependencies,
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)
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def _resolve_node_spec(
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*,
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node_name: str,
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deployment: WorkflowDeployment | None,
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sources: dict[str, CapabilitySource],
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) -> tuple[str, NodeSpec[Any, Any]]:
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concrete = _find_node_spec(node_name, sources)
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if concrete is not None:
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return node_name, concrete
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if deployment is not None:
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for bound_name in _bound_node_names(node_name, deployment.binding_map()):
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concrete = _find_node_spec(bound_name, sources)
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if concrete is not None:
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return bound_name, concrete
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raise KeyError(f"unknown node spec {node_name!r}")
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def _bound_node_names(
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node_name: str,
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bindings: dict[str, str],
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) -> tuple[str, ...]:
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"""Return concrete names made by replacing known logical source prefixes.
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CapabilityRef parses by splitting on the last dot, which is correct for
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simple tool names but wrong for local names that also contain dots
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(`demo.foo.bar` with logical source `demo`). Runtime binding is source-aware:
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deployment bindings define the allowed source prefixes, and everything after
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the matched prefix remains the local capability name.
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"""
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candidates: list[str] = []
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for logical_source, concrete_source in sorted(
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bindings.items(),
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key=lambda item: len(item[0]),
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reverse=True,
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):
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prefix = f"{logical_source}."
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if node_name.startswith(prefix):
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candidates.append(f"{concrete_source}.{node_name[len(prefix) :]}")
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return tuple(candidates)
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def _find_node_spec(
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node_name: str,
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sources: dict[str, CapabilitySource],
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) -> NodeSpec[Any, Any] | None:
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for source in sources.values():
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spec = source.capabilities.node_specs.get(node_name)
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if spec is not None:
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return spec
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return None
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def _resolve_reducers(
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*,
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required_capabilities: dict[str, RequiredCapability],
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deployment: WorkflowDeployment | None,
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sources: dict[str, CapabilitySource],
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) -> dict[str, ReducerDefinition]:
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reducers: dict[str, ReducerDefinition] = {}
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if deployment is None:
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return reducers
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for logical_ref, required in required_capabilities.items():
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if required.kind != "reducer":
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continue
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bound_source_id = deployment.binding_map().get(required.logical_source)
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if bound_source_id is None:
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continue
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source = sources.get(bound_source_id)
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if source is None:
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continue
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definition = _find_reducer_definition(
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source=source,
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capability_name=required.capability_name,
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)
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if definition is not None:
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reducers[logical_ref] = definition
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return reducers
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def _find_reducer_definition(
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*,
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source: CapabilitySource,
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capability_name: str,
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) -> ReducerDefinition | None:
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for reducer_name, definition in source.capabilities.reducer_definitions.items():
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try:
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reducer_ref = CapabilityRef.parse(reducer_name)
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except ValueError:
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continue
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if reducer_ref.name == capability_name:
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return definition
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return None
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__all__ = [
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"RuntimeDependencies",
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"resolve_runtime_dependencies",
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]
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@@ -27,7 +27,7 @@ from wf_core.models.workflow_refs import WorkflowRef
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from wf_platform import CapabilitySource
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from ..models import RawWorkflowPlan
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from .runtime_dependencies import resolve_runtime_dependencies
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from wf_api.runtime_dependencies import resolve_runtime_dependencies
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_STEPS_ADAPTER = TypeAdapter(list[Step])
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@@ -0,0 +1,37 @@
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"""Tests for runtime_dependencies extraction: canonical location in wf_api, shim in wf_mcp."""
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from __future__ import annotations
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def test_canonical_import_from_wf_api() -> None:
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from wf_api.runtime_dependencies import (
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RuntimeDependencies,
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resolve_runtime_dependencies,
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)
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assert RuntimeDependencies.__name__ == "RuntimeDependencies"
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assert callable(resolve_runtime_dependencies)
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def test_compat_shim_import_from_wf_mcp() -> None:
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from wf_mcp.workflow_surface.runtime_dependencies import (
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RuntimeDependencies,
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resolve_runtime_dependencies,
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)
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assert RuntimeDependencies.__name__ == "RuntimeDependencies"
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assert callable(resolve_runtime_dependencies)
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def test_shim_symbols_are_identical_to_canonical() -> None:
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from wf_api.runtime_dependencies import (
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RuntimeDependencies as CanonicalRuntimeDependencies,
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resolve_runtime_dependencies as canonical_resolve,
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)
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from wf_mcp.workflow_surface.runtime_dependencies import (
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RuntimeDependencies as ShimRuntimeDependencies,
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resolve_runtime_dependencies as shim_resolve,
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)
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assert CanonicalRuntimeDependencies is ShimRuntimeDependencies
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assert canonical_resolve is shim_resolve
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Reference in New Issue
Block a user