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runtime service

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lda
2026-06-02 16:39:47 +07:00 Verified
parent 62f880bc5b
commit 19f6fa3e40
8 changed files with 1285 additions and 141 deletions
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src/wf_mcp/broker/service/core.py
+23 -136
View File
@@ -15,14 +15,10 @@ from wf_artifacts import (
)
from wf_authoring import NodeSpec
from wf_core import (
NodeUse,
RunState,
Workflow,
execute_workflow_result_async,
resume_workflow_result_async,
)
from wf_api.models import RawWorkflowPlan
from wf_api.runtime_dependencies import resolve_runtime_dependencies
from wf_platform import (
CapabilitySource,
)
@@ -42,17 +38,14 @@ from ...runtime import ToolExecutor
from ...shared.errors import error_payload
from ...shared.names import RESERVED_CONNECTION_IDS
from ...storage import Store
from wf_api.saved_subgraphs import (
SavedSubgraphTree,
prepare_saved_subgraphs,
resolve_saved_subgraph_tree,
)
from wf_api.saved_subgraphs import SavedSubgraphTree
from ..admin_capabilities import admin_source
from ..catalog import CombinedCatalog, snapshot_from_specs
from ..discovery import discover_connection_capabilities, specs_from_discovered_tools
from .adapters import require_adapter
from .builtins import builtin_sources
from .source_catalog import SourceCatalogService
from .workflow_runtime import WorkflowRuntimeService
@dataclass(slots=True)
@@ -68,6 +61,7 @@ class WfMcpService:
run_store: RunStore | None = None
tool_executor: ToolExecutor | None = None
source_catalog: SourceCatalogService = field(init=False)
workflow_runtime: WorkflowRuntimeService = field(init=False)
def __post_init__(self) -> None:
"""Install broker-local system specs when enabled.
@@ -90,6 +84,11 @@ class WfMcpService:
for source in builtin_sources().values():
self.register_capability_source(source)
self.register_capability_source(admin_source())
self.workflow_runtime = WorkflowRuntimeService(
source_catalog=self.source_catalog,
artifact_store=self.artifact_store,
emit_event=self._record_event,
)
@property
def capability_sources(self) -> dict[str, CapabilitySource]:
@@ -486,35 +485,7 @@ class WfMcpService:
plan: RawWorkflowPlan,
node_name_bindings: dict[str, str] | None = None,
) -> Workflow:
node_defs: dict[str, Any] = {}
bindings = node_name_bindings or {}
for step in plan.nodes:
if not isinstance(step, NodeUse):
continue
qualified_name = bindings.get(step.node, step.node)
spec = self._get_qualified_spec(qualified_name)
node_defs[qualified_name] = spec.to_node_def()
nodes = []
for node in plan.nodes:
payload = node.model_dump(by_alias=True)
if isinstance(node, NodeUse):
payload["node"] = bindings.get(node.node, node.node)
nodes.append(payload)
payload = {
"name": plan.name,
"input_schema": plan.input_schema,
"state_schema": plan.state_schema,
"output_schema": plan.output_schema,
"output": [binding.model_dump(mode="json") for binding in plan.output],
"outcomes": plan.outcomes,
"start": plan.start,
"node_defs": [node.model_dump() for node in node_defs.values()],
"nodes": nodes,
"edges": [edge.model_dump(by_alias=True) for edge in plan.edges],
}
return Workflow.model_validate(payload)
return self.workflow_runtime.compile_plan(plan, node_name_bindings)
def _prepare_workflow_runtime(
self,
@@ -524,56 +495,11 @@ class WfMcpService:
artifact: WorkflowArtifact | None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> tuple[Workflow, dict[str, Any], dict[str, Any], dict[str, Any]]:
"""Resolve bindings once into the executable pieces core expects.
Saved-run resume must rebuild prepared dependencies from the current
in-memory service state. Durable resume will need a stricter snapshot,
but this keeps the current platform boundary explicit.
"""
plan_node_names = [
node.node for node in plan.nodes if isinstance(node, NodeUse)
]
runtime_artifact = artifact or WorkflowArtifact(
id=plan.name,
version=1,
title=plan.name,
input_schema=plan.input_schema,
output_schema=plan.output_schema,
outcomes=("completed",),
plan=plan.model_dump(mode="json", by_alias=True),
)
dependencies = resolve_runtime_dependencies(
artifact=runtime_artifact,
return self.workflow_runtime.prepare_workflow_runtime(
plan,
deployment=deployment,
sources=self.capability_sources,
plan_node_names=plan_node_names,
)
prepared_subgraphs = {}
if saved_subgraph_tree is not None:
tree = saved_subgraph_tree
prepared_subgraphs = prepare_saved_subgraphs(
tree=tree,
deployment=deployment,
sources=self.capability_sources,
compile_plan=self.compile_plan,
)
elif artifact is not None and self.artifact_store is not None:
tree = resolve_saved_subgraph_tree(
root_artifact=artifact,
artifact_store=self.artifact_store,
)
prepared_subgraphs = prepare_saved_subgraphs(
tree=tree,
deployment=deployment,
sources=self.capability_sources,
compile_plan=self.compile_plan,
)
workflow = self.compile_plan(plan, dependencies.node_name_bindings)
return (
workflow,
dependencies.node_registry,
dependencies.reducers,
prepared_subgraphs,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
async def run_workflow_from_plan(
@@ -584,36 +510,13 @@ class WfMcpService:
artifact: WorkflowArtifact | None = None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
):
self._record_event(
make_event(
"workflow_run_started",
workflow_name=plan.name,
payload={"input_keys": sorted(workflow_input.keys())},
)
)
workflow, registry, reducers, prepared_subgraphs = (
self._prepare_workflow_runtime(
plan,
deployment=deployment,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
)
run = await execute_workflow_result_async(
workflow,
return await self.workflow_runtime.run_workflow_from_plan(
plan,
workflow_input,
registry,
reducers=reducers,
subgraphs=prepared_subgraphs,
deployment=deployment,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
self._record_event(
make_event(
"workflow_run_completed",
workflow_name=plan.name,
payload={"status": run.status.value},
)
)
return run
async def resume_workflow_from_plan(
self,
@@ -627,31 +530,15 @@ class WfMcpService:
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> RunState:
"""Resume one stopped run using its prepared runtime dependency boundary."""
workflow, registry, reducers, prepared_subgraphs = (
self._prepare_workflow_runtime(
plan,
deployment=deployment,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
)
resumed = await resume_workflow_result_async(
workflow,
return await self.workflow_runtime.resume_workflow_from_plan(
plan,
run,
registry,
resume_payload=resume_payload,
resume_outcome=resume_outcome,
reducers=reducers,
subgraphs=prepared_subgraphs,
deployment=deployment,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
self._record_event(
make_event(
"workflow_run_resumed",
workflow_name=plan.name,
payload={"status": resumed.status.value},
)
)
return resumed
def list_events(self) -> list[McpEvent]:
return self.event_bus.list_events()
src/wf_mcp/broker/service/workflow_operation_context.py
+6 -5
View File
@@ -18,6 +18,7 @@ from wf_mcp.events import make_event
from .core import WfMcpService
from .workflow_live_checks import live_source_diagnostics
from .workflow_runtime import WorkflowRuntimeService
@dataclass(frozen=True, slots=True)
@@ -67,9 +68,9 @@ class WfMcpWorkflowArtifactCataloger(WorkflowArtifactCataloger):
@dataclass(frozen=True, slots=True)
class WfMcpWorkflowRuntimeRunner(WorkflowRuntimeRunner):
"""Adapter-owned runtime runner backed by WfMcpService."""
"""Adapter-owned runtime runner backed by WorkflowRuntimeService."""
service: WfMcpService
runtime: WorkflowRuntimeService
async def run_workflow_from_plan(
self,
@@ -79,7 +80,7 @@ class WfMcpWorkflowRuntimeRunner(WorkflowRuntimeRunner):
artifact=None,
saved_subgraph_tree=None,
):
return await self.service.run_workflow_from_plan(
return await self.runtime.run_workflow_from_plan(
plan,
workflow_input,
deployment=deployment,
@@ -98,7 +99,7 @@ class WfMcpWorkflowRuntimeRunner(WorkflowRuntimeRunner):
artifact=None,
saved_subgraph_tree=None,
):
return await self.service.resume_workflow_from_plan(
return await self.runtime.resume_workflow_from_plan(
plan,
run,
resume_payload=resume_payload,
@@ -139,7 +140,7 @@ def context_from_service(service: WfMcpService) -> WorkflowOperationContext:
events=WfMcpWorkflowEventRecorder(service),
specs=specs,
artifacts=WfMcpWorkflowArtifactCataloger(service),
runtime=WfMcpWorkflowRuntimeRunner(service),
runtime=WfMcpWorkflowRuntimeRunner(service.workflow_runtime),
live_sources=WfMcpWorkflowLiveSourceChecker(service),
)
src/wf_mcp/broker/service/workflow_runtime.py
+216
View File
@@ -0,0 +1,216 @@
from __future__ import annotations
from collections.abc import Callable
from dataclasses import dataclass
from typing import Any
from wf_artifacts import WorkflowArtifact, WorkflowArtifactStore, WorkflowDeployment
from wf_authoring import NodeSpec
from wf_core import (
NodeUse,
RunState,
Workflow,
execute_workflow_result_async,
resume_workflow_result_async,
)
from wf_api.models import RawWorkflowPlan
from wf_api.runtime_dependencies import resolve_runtime_dependencies
from wf_api.saved_subgraphs import (
SavedSubgraphTree,
prepare_saved_subgraphs,
resolve_saved_subgraph_tree,
)
from ...events import McpEvent, make_event
from .source_catalog import SourceCatalogService
EventEmitter = Callable[[McpEvent], None]
@dataclass(slots=True)
class WorkflowRuntimeService:
"""Compile and execute workflow plans against broker-owned runtime deps.
This service is still an MCP broker implementation detail. It receives
source/catalog state from `SourceCatalogService`, but it does not own
connections, adapters, auth, or upstream discovery.
"""
source_catalog: SourceCatalogService
artifact_store: WorkflowArtifactStore | None
emit_event: EventEmitter
def compile_plan(
self,
plan: RawWorkflowPlan,
node_name_bindings: dict[str, str] | None = None,
) -> Workflow:
node_defs: dict[str, Any] = {}
bindings = node_name_bindings or {}
for step in plan.nodes:
if not isinstance(step, NodeUse):
continue
qualified_name = bindings.get(step.node, step.node)
spec: NodeSpec[Any, Any] = self.source_catalog.get_qualified_spec(
qualified_name
)
node_defs[qualified_name] = spec.to_node_def().model_copy(
update={"name": qualified_name}
)
nodes = []
for node in plan.nodes:
payload = node.model_dump(by_alias=True)
if isinstance(node, NodeUse):
payload["node"] = bindings.get(node.node, node.node)
nodes.append(payload)
payload = {
"name": plan.name,
"input_schema": plan.input_schema,
"state_schema": plan.state_schema,
"output_schema": plan.output_schema,
"output": [binding.model_dump(mode="json") for binding in plan.output],
"outcomes": plan.outcomes,
"start": plan.start,
"node_defs": [node.model_dump() for node in node_defs.values()],
"nodes": nodes,
"edges": [edge.model_dump(by_alias=True) for edge in plan.edges],
}
return Workflow.model_validate(payload)
def prepare_workflow_runtime(
self,
plan: RawWorkflowPlan,
*,
deployment: WorkflowDeployment | None,
artifact: WorkflowArtifact | None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> tuple[Workflow, dict[str, Any], dict[str, Any], dict[str, Any]]:
"""Resolve bindings once into the executable pieces core expects.
Saved-run resume still rebuilds prepared dependencies from the current
in-memory broker state. Durable resume will need a stricter snapshot,
but this keeps the current platform boundary explicit.
"""
plan_node_names = [
node.node for node in plan.nodes if isinstance(node, NodeUse)
]
runtime_artifact = artifact or WorkflowArtifact(
id=plan.name,
version=1,
title=plan.name,
input_schema=plan.input_schema,
output_schema=plan.output_schema,
outcomes=("completed",),
plan=plan.model_dump(mode="json", by_alias=True),
)
dependencies = resolve_runtime_dependencies(
artifact=runtime_artifact,
deployment=deployment,
sources=self.source_catalog.capability_sources,
plan_node_names=plan_node_names,
)
prepared_subgraphs = {}
if saved_subgraph_tree is not None:
prepared_subgraphs = prepare_saved_subgraphs(
tree=saved_subgraph_tree,
deployment=deployment,
sources=self.source_catalog.capability_sources,
compile_plan=self.compile_plan,
)
elif artifact is not None and self.artifact_store is not None:
tree = resolve_saved_subgraph_tree(
root_artifact=artifact,
artifact_store=self.artifact_store,
)
prepared_subgraphs = prepare_saved_subgraphs(
tree=tree,
deployment=deployment,
sources=self.source_catalog.capability_sources,
compile_plan=self.compile_plan,
)
workflow = self.compile_plan(plan, dependencies.node_name_bindings)
return (
workflow,
dependencies.node_registry,
dependencies.reducers,
prepared_subgraphs,
)
async def run_workflow_from_plan(
self,
plan: RawWorkflowPlan,
workflow_input: dict[str, Any],
deployment: WorkflowDeployment | None = None,
artifact: WorkflowArtifact | None = None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> RunState:
self.emit_event(
make_event(
"workflow_run_started",
workflow_name=plan.name,
payload={"input_keys": sorted(workflow_input.keys())},
)
)
workflow, registry, reducers, prepared_subgraphs = (
self.prepare_workflow_runtime(
plan,
deployment=deployment,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
)
run = await execute_workflow_result_async(
workflow,
workflow_input,
registry,
reducers=reducers,
subgraphs=prepared_subgraphs,
)
self.emit_event(
make_event(
"workflow_run_completed",
workflow_name=plan.name,
payload={"status": run.status.value},
)
)
return run
async def resume_workflow_from_plan(
self,
plan: RawWorkflowPlan,
run: RunState,
*,
resume_payload: dict[str, Any],
resume_outcome: str = "submitted",
deployment: WorkflowDeployment | None = None,
artifact: WorkflowArtifact | None = None,
saved_subgraph_tree: SavedSubgraphTree | None = None,
) -> RunState:
"""Resume one stopped run using its prepared runtime dependency boundary."""
workflow, registry, reducers, prepared_subgraphs = (
self.prepare_workflow_runtime(
plan,
deployment=deployment,
artifact=artifact,
saved_subgraph_tree=saved_subgraph_tree,
)
)
resumed = await resume_workflow_result_async(
workflow,
run,
registry,
resume_payload=resume_payload,
resume_outcome=resume_outcome,
reducers=reducers,
subgraphs=prepared_subgraphs,
)
self.emit_event(
make_event(
"workflow_run_resumed",
workflow_name=plan.name,
payload={"status": resumed.status.value},
)
)
return resumed