lift workflow stuff out of the big Tool register

This commit is contained in:
lda
2026-05-12 19:22:32 +07:00 Verified
parent 6b696ff56a
commit 8235794c58
4 changed files with 449 additions and 212 deletions
+16 -212
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@@ -3,46 +3,22 @@ from __future__ import annotations
from typing import Any
from mcp.server.fastmcp import FastMCP
from wf_artifacts import (
AvailableCapability,
AvailableSource,
DependencyDiagnostic,
DiagnosticSeverity,
RequiredCapability,
WorkflowArtifact,
WorkflowDeployment,
create_workflow_artifact_from_plan as build_workflow_artifact_from_plan,
validate_deployment_dependencies,
)
from ..models import RawWorkflowPlan
from ..workflow_surface import WorkflowSurfaceHandlers
from .service import WfMcpService
def register_artifact_tools(server: FastMCP, service: WfMcpService) -> None:
"""Register stable MCP tools for saved workflow artifact inspection."""
handlers = WorkflowSurfaceHandlers(service)
@server.tool()
async def list_workflow_artifacts() -> dict[str, Any]:
if service.artifact_store is None:
return {"nodes": []}
entries = [
service.workflow_artifact_catalog_entry(artifact).model_dump(mode="json")
for artifact in service.artifact_store.list_artifacts()
]
return {"nodes": entries}
return await handlers.list_artifacts()
@server.tool()
async def save_workflow_artifact(artifact: dict[str, Any]) -> dict[str, Any]:
if service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
workflow_artifact = WorkflowArtifact.model_validate(artifact)
service.artifact_store.save_artifact(workflow_artifact)
return {
"artifact_id": workflow_artifact.id,
"version": workflow_artifact.version,
"saved": True,
}
return await handlers.save_artifact(artifact)
@server.tool()
async def create_workflow_artifact_from_plan(
@@ -55,9 +31,7 @@ def register_artifact_tools(server: FastMCP, service: WfMcpService) -> None:
required_capabilities: dict[str, dict[str, Any]] | None = None,
created_from_catalog_version: str | None = None,
) -> dict[str, Any]:
if service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
workflow_artifact = build_workflow_artifact_from_plan(
return await handlers.create_artifact_from_plan(
artifact_id=artifact_id,
version=version,
title=title,
@@ -65,210 +39,40 @@ def register_artifact_tools(server: FastMCP, service: WfMcpService) -> None:
plan=plan,
outcomes=tuple(outcomes),
required_capabilities={
name: RequiredCapability.model_validate(capability)
name: capability
for name, capability in (required_capabilities or {}).items()
},
created_from_catalog_version=created_from_catalog_version,
)
service.artifact_store.save_artifact(workflow_artifact)
return {
"artifact_id": workflow_artifact.id,
"version": workflow_artifact.version,
"saved": True,
}
@server.tool()
async def inspect_workflow_artifact(
artifact_id: str,
version: int,
) -> dict[str, Any]:
if service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
artifact = service.artifact_store.get_artifact(artifact_id, version)
return artifact.model_dump(mode="json")
return await handlers.inspect_artifact(
artifact_id=artifact_id,
version=version,
)
@server.tool()
async def list_workflow_deployments() -> dict[str, Any]:
if service.artifact_store is None:
return {"deployments": []}
return {
"deployments": [
deployment.model_dump(mode="json")
for deployment in service.artifact_store.list_deployments()
]
}
return await handlers.list_deployments()
@server.tool()
async def save_workflow_deployment(deployment: dict[str, Any]) -> dict[str, Any]:
if service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
workflow_deployment = WorkflowDeployment.model_validate(deployment)
service.artifact_store.save_deployment(workflow_deployment)
return {
"deployment_id": workflow_deployment.id,
"artifact_id": workflow_deployment.artifact_id,
"artifact_version": workflow_deployment.artifact_version,
"saved": True,
}
return await handlers.save_deployment(deployment)
@server.tool()
async def validate_workflow_deployment(deployment_id: str) -> dict[str, Any]:
if service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
deployment = service.artifact_store.get_deployment(deployment_id)
artifact = service.artifact_store.get_artifact(
deployment.artifact_id,
deployment.artifact_version,
)
diagnostics = validate_deployment_dependencies(
artifact=artifact,
deployment=deployment,
sources=_available_sources(service),
)
return {
"deployment_id": deployment.id,
"artifact_id": artifact.id,
"artifact_version": artifact.version,
"status": "unrunnable" if diagnostics else "runnable",
"diagnostics": [
diagnostic.model_dump(mode="json") for diagnostic in diagnostics
],
}
return await handlers.validate_deployment(deployment_id=deployment_id)
@server.tool()
async def run_workflow_deployment(
deployment_id: str,
workflow_input: dict[str, Any],
) -> dict[str, Any]:
if service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
deployment = service.artifact_store.get_deployment(deployment_id)
artifact = service.artifact_store.get_artifact(
deployment.artifact_id,
deployment.artifact_version,
return await handlers.run_deployment(
deployment_id=deployment_id,
workflow_input=workflow_input,
)
diagnostics = validate_deployment_dependencies(
artifact=artifact,
deployment=deployment,
sources=_available_sources(service),
)
if diagnostics:
return _run_payload(
deployment=deployment,
artifact=artifact,
status="unrunnable",
diagnostics=diagnostics,
)
unsupported = _unsupported_interrupt_diagnostic(artifact)
if unsupported is not None:
return _run_payload(
deployment=deployment,
artifact=artifact,
status="unsupported",
diagnostics=[unsupported],
)
plan = _raw_plan_from_artifact(artifact)
run = await service.run_workflow_from_plan(plan, workflow_input)
return _run_payload(
deployment=deployment,
artifact=artifact,
status=run.status.value,
output=run.output,
trace_count=len(run.trace),
)
def _available_sources(service: WfMcpService) -> list[AvailableSource]:
"""Convert broker capability sources into artifact validation snapshots."""
sources: list[AvailableSource] = []
for source in service.capability_sources.values():
capabilities = {
spec.name.rsplit(".", maxsplit=1)[-1]: AvailableCapability(
name=spec.name.rsplit(".", maxsplit=1)[-1],
kind="node_spec",
input_schema_hash=None,
output_schema_hash=None,
)
for spec in source.capabilities.node_specs.values()
}
sources.append(
AvailableSource(
id=source.id,
enabled=source.enabled,
capabilities=capabilities,
)
)
return sources
def _raw_plan_from_artifact(artifact: WorkflowArtifact) -> RawWorkflowPlan:
"""Validate the stored plan shape expected by the broker workflow runner."""
return RawWorkflowPlan(
name=_plan_field(artifact, "name"),
input_schema=_plan_field(artifact, "input_schema"),
state_schema=_plan_field(artifact, "state_schema"),
output_schema=_plan_field(artifact, "output_schema"),
start=_plan_field(artifact, "start"),
nodes=_plan_field(artifact, "nodes"),
edges=_plan_field(artifact, "edges"),
)
def _plan_field(artifact: WorkflowArtifact, field_name: str) -> Any:
try:
return artifact.plan[field_name]
except KeyError as exc:
raise ValueError(
f"workflow artifact {artifact.id}@{artifact.version} "
f"is missing plan field {field_name!r}"
) from exc
def _unsupported_interrupt_diagnostic(
artifact: WorkflowArtifact,
) -> DependencyDiagnostic | None:
if not any(node.get("type") == "interrupt" for node in _plan_nodes(artifact)):
return None
return DependencyDiagnostic(
severity=DiagnosticSeverity.ERROR,
code="interrupting_artifact_unsupported",
logical_ref=f"workflow.{artifact.id}.v{artifact.version}",
message=(
"Running saved workflow artifacts with interrupt nodes is unsupported "
"until nested run-state resume is implemented."
),
repair_hint=(
"Run this workflow as a top-level core workflow or remove interrupt "
"nodes before saving it as a runnable deployment."
),
)
def _plan_nodes(artifact: WorkflowArtifact) -> list[dict[str, Any]]:
nodes = artifact.plan.get("nodes", [])
return [node for node in nodes if isinstance(node, dict)]
def _run_payload(
*,
deployment: WorkflowDeployment,
artifact: WorkflowArtifact,
status: str,
diagnostics: list[DependencyDiagnostic] | None = None,
output: dict[str, Any] | None = None,
trace_count: int = 0,
) -> dict[str, Any]:
return {
"deployment_id": deployment.id,
"artifact_id": artifact.id,
"artifact_version": artifact.version,
"status": status,
"output": output,
"diagnostics": [
diagnostic.model_dump(mode="json") for diagnostic in diagnostics or []
],
"trace_count": trace_count,
}
+3
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@@ -0,0 +1,3 @@
from .handlers import WorkflowSurfaceHandlers
__all__ = ["WorkflowSurfaceHandlers"]
+271
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@@ -0,0 +1,271 @@
from __future__ import annotations
from collections.abc import Sequence
from typing import TYPE_CHECKING, Any
from wf_artifacts import (
AvailableCapability,
AvailableSource,
DependencyDiagnostic,
DiagnosticSeverity,
RequiredCapability,
WorkflowArtifact,
WorkflowDeployment,
create_workflow_artifact_from_plan as build_workflow_artifact_from_plan,
validate_deployment_dependencies,
)
from ..models import RawWorkflowPlan
if TYPE_CHECKING:
from ..broker.service import WfMcpService
class WorkflowSurfaceHandlers:
"""Reusable implementation behind MCP workflow artifact tools."""
def __init__(self, service: WfMcpService) -> None:
self.service = service
async def list_artifacts(self) -> dict[str, Any]:
if self.service.artifact_store is None:
return {"nodes": []}
entries = [
self.service.workflow_artifact_catalog_entry(artifact).model_dump(
mode="json"
)
for artifact in self.service.artifact_store.list_artifacts()
]
return {"nodes": entries}
async def save_artifact(self, artifact: dict[str, Any]) -> dict[str, Any]:
if self.service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
workflow_artifact = WorkflowArtifact.model_validate(artifact)
self.service.artifact_store.save_artifact(workflow_artifact)
return {
"artifact_id": workflow_artifact.id,
"version": workflow_artifact.version,
"saved": True,
}
async def create_artifact_from_plan(
self,
*,
artifact_id: str,
version: int,
title: str,
plan: dict[str, Any],
outcomes: Sequence[str],
description: str | None = None,
required_capabilities: dict[str, dict[str, Any]] | None = None,
created_from_catalog_version: str | None = None,
) -> dict[str, Any]:
if self.service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
workflow_artifact = build_workflow_artifact_from_plan(
artifact_id=artifact_id,
version=version,
title=title,
description=description,
plan=plan,
outcomes=tuple(outcomes),
required_capabilities={
name: RequiredCapability.model_validate(capability)
for name, capability in (required_capabilities or {}).items()
},
created_from_catalog_version=created_from_catalog_version,
)
self.service.artifact_store.save_artifact(workflow_artifact)
return {
"artifact_id": workflow_artifact.id,
"version": workflow_artifact.version,
"saved": True,
}
async def inspect_artifact(
self, *, artifact_id: str, version: int
) -> dict[str, Any]:
if self.service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
artifact = self.service.artifact_store.get_artifact(artifact_id, version)
return artifact.model_dump(mode="json")
async def list_deployments(self) -> dict[str, Any]:
if self.service.artifact_store is None:
return {"deployments": []}
return {
"deployments": [
deployment.model_dump(mode="json")
for deployment in self.service.artifact_store.list_deployments()
]
}
async def save_deployment(self, deployment: dict[str, Any]) -> dict[str, Any]:
if self.service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
workflow_deployment = WorkflowDeployment.model_validate(deployment)
self.service.artifact_store.save_deployment(workflow_deployment)
return {
"deployment_id": workflow_deployment.id,
"artifact_id": workflow_deployment.artifact_id,
"artifact_version": workflow_deployment.artifact_version,
"saved": True,
}
async def validate_deployment(self, *, deployment_id: str) -> dict[str, Any]:
deployment, artifact, diagnostics = self._deployment_validation(deployment_id)
return {
"deployment_id": deployment.id,
"artifact_id": artifact.id,
"artifact_version": artifact.version,
"status": "unrunnable" if diagnostics else "runnable",
"diagnostics": [
diagnostic.model_dump(mode="json") for diagnostic in diagnostics
],
}
async def run_deployment(
self,
*,
deployment_id: str,
workflow_input: dict[str, Any],
) -> dict[str, Any]:
deployment, artifact, diagnostics = self._deployment_validation(deployment_id)
if diagnostics:
return _run_payload(
deployment=deployment,
artifact=artifact,
status="unrunnable",
diagnostics=diagnostics,
)
unsupported = _unsupported_interrupt_diagnostic(artifact)
if unsupported is not None:
return _run_payload(
deployment=deployment,
artifact=artifact,
status="unsupported",
diagnostics=[unsupported],
)
plan = _raw_plan_from_artifact(artifact)
run = await self.service.run_workflow_from_plan(plan, workflow_input)
return _run_payload(
deployment=deployment,
artifact=artifact,
status=run.status.value,
output=run.output,
trace_count=len(run.trace),
)
def _deployment_validation(
self,
deployment_id: str,
) -> tuple[WorkflowDeployment, WorkflowArtifact, list[DependencyDiagnostic]]:
if self.service.artifact_store is None:
raise KeyError("workflow artifact store is not configured")
deployment = self.service.artifact_store.get_deployment(deployment_id)
artifact = self.service.artifact_store.get_artifact(
deployment.artifact_id,
deployment.artifact_version,
)
diagnostics = validate_deployment_dependencies(
artifact=artifact,
deployment=deployment,
sources=_available_sources(self.service),
)
return deployment, artifact, diagnostics
def _available_sources(service: WfMcpService) -> list[AvailableSource]:
"""Convert broker capability sources into artifact validation snapshots."""
sources: list[AvailableSource] = []
for source in service.capability_sources.values():
capabilities = {
spec.name.rsplit(".", maxsplit=1)[-1]: AvailableCapability(
name=spec.name.rsplit(".", maxsplit=1)[-1],
kind="node_spec",
input_schema_hash=None,
output_schema_hash=None,
)
for spec in source.capabilities.node_specs.values()
}
sources.append(
AvailableSource(
id=source.id,
enabled=source.enabled,
capabilities=capabilities,
)
)
return sources
def _raw_plan_from_artifact(artifact: WorkflowArtifact) -> RawWorkflowPlan:
"""Validate the stored plan shape expected by the broker workflow runner."""
return RawWorkflowPlan(
name=_plan_field(artifact, "name"),
input_schema=_plan_field(artifact, "input_schema"),
state_schema=_plan_field(artifact, "state_schema"),
output_schema=_plan_field(artifact, "output_schema"),
start=_plan_field(artifact, "start"),
nodes=_plan_field(artifact, "nodes"),
edges=_plan_field(artifact, "edges"),
)
def _plan_field(artifact: WorkflowArtifact, field_name: str) -> Any:
try:
return artifact.plan[field_name]
except KeyError as exc:
raise ValueError(
f"workflow artifact {artifact.id}@{artifact.version} "
f"is missing plan field {field_name!r}"
) from exc
def _unsupported_interrupt_diagnostic(
artifact: WorkflowArtifact,
) -> DependencyDiagnostic | None:
if not any(node.get("type") == "interrupt" for node in _plan_nodes(artifact)):
return None
return DependencyDiagnostic(
severity=DiagnosticSeverity.ERROR,
code="interrupting_artifact_unsupported",
logical_ref=f"workflow.{artifact.id}.v{artifact.version}",
message=(
"Running saved workflow artifacts with interrupt nodes is unsupported "
"until nested run-state resume is implemented."
),
repair_hint=(
"Run this workflow as a top-level core workflow or remove interrupt "
"nodes before saving it as a runnable deployment."
),
)
def _plan_nodes(artifact: WorkflowArtifact) -> list[dict[str, Any]]:
nodes = artifact.plan.get("nodes", [])
return [node for node in nodes if isinstance(node, dict)]
def _run_payload(
*,
deployment: WorkflowDeployment,
artifact: WorkflowArtifact,
status: str,
diagnostics: list[DependencyDiagnostic] | None = None,
output: dict[str, Any] | None = None,
trace_count: int = 0,
) -> dict[str, Any]:
return {
"deployment_id": deployment.id,
"artifact_id": artifact.id,
"artifact_version": artifact.version,
"status": status,
"output": output,
"diagnostics": [
diagnostic.model_dump(mode="json") for diagnostic in diagnostics or []
],
"trace_count": trace_count,
}