389 lines
11 KiB
Python
389 lines
11 KiB
Python
from __future__ import annotations
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from typing import Any
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from pydantic import BaseModel
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from wf_artifacts import (
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FileDraftWorkspaceStore,
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FileRunStore,
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FileWorkflowArtifactStore,
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RequiredCapability,
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WorkflowArtifact,
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)
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from wf_authoring import node, reducer
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from wf_mcp.broker import WfMcpService
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from wf_mcp.capabilities import DiscoveredTool
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from wf_mcp.sdk import ToolCallResult
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from wf_mcp.storage import FileStore
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from wf_mcp.workflow_surface import WorkflowSurfaceHandlers
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from ..test_support import input_binding, output_binding
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class AmountInput(BaseModel):
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amount: int
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class AmountOutput(BaseModel):
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amount: int
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class ChangedEchoInput(BaseModel):
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message: str
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class ChangedEchoOutput(BaseModel):
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echoed: str
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@node()
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async def amount_tool(payload: AmountInput) -> AmountOutput:
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return AmountOutput(amount=payload.amount)
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@node(name="echo_tool")
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def changed_echo_tool(payload: ChangedEchoInput) -> ChangedEchoOutput:
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return ChangedEchoOutput(echoed=payload.message)
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@node(name="mcp_echo_tool", outcomes=("ok", "error"))
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def mcp_echo_tool(payload: ChangedEchoInput) -> ChangedEchoOutput:
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"""Test fixture that mirrors naive MCP wrappers with ok/error outcomes."""
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return ChangedEchoOutput(echoed=payload.message)
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@node(name="failing_tool")
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def failing_tool(payload: ChangedEchoInput) -> ChangedEchoOutput:
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raise RuntimeError("upstream exploded")
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class ContentOnlyOutputAdapter:
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"""MCP-like adapter whose tool exposes raw content blocks as output schema."""
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async def list_tools(
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self,
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connection,
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auth,
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) -> list[DiscoveredTool]:
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return [
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DiscoveredTool(
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name="echo",
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title="Echo",
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description="Echo a message as an MCP text content block.",
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input_schema={
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"type": "object",
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"properties": {"message": {"type": "string"}},
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"required": ["message"],
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},
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output_schema={
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"type": "object",
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"properties": {"content": {"type": "array"}},
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"required": ["content"],
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},
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)
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]
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async def list_resources(
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self,
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connection,
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auth,
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) -> list[Any]:
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return []
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async def list_prompts(
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self,
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connection,
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auth,
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) -> list[Any]:
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return []
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async def get_connection_metadata(
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self,
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connection,
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auth,
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) -> dict[str, Any]:
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return {
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"server": getattr(
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connection, "provider", getattr(connection, "server", None)
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)
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}
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async def call_tool(
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self,
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connection,
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auth,
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tool_name: str,
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payload: dict[str, Any],
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) -> ToolCallResult:
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message = payload.get("message", "")
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return ToolCallResult(
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outcome="ok",
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output={"content": [{"type": "text", "text": f"Echo: {message}"}]},
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)
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async def read_resource(
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self,
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connection,
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auth,
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uri: str,
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) -> dict[str, Any]:
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raise KeyError(uri)
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async def get_prompt(
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self,
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connection,
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auth,
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prompt_name: str,
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arguments: dict[str, str] | None = None,
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) -> dict[str, Any]:
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raise KeyError(prompt_name)
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async def invoke_method(
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self,
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connection,
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auth,
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method: str,
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params: dict[str, Any] | None = None,
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) -> dict[str, Any]:
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raise KeyError(method)
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async def send_notification(
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self,
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connection,
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auth,
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method: str,
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params: dict[str, Any] | None = None,
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) -> None:
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raise KeyError(method)
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@reducer(name="custom.default.multiply")
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def multiply(current: int | None, incoming: int) -> int:
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return (current or 1) * incoming
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def handlers(artifact_store: FileWorkflowArtifactStore) -> WorkflowSurfaceHandlers:
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mcp_root = artifact_store.root / "surface_mcp" / str(id(artifact_store))
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service = WfMcpService(
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store=FileStore(mcp_root),
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artifact_store=artifact_store,
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draft_workspace_store=FileDraftWorkspaceStore(mcp_root),
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run_store=FileRunStore(mcp_root),
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)
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return WorkflowSurfaceHandlers(service)
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def artifact() -> WorkflowArtifact:
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return WorkflowArtifact(
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id="summarize_docs",
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version=1,
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title="Summarize Docs",
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description="Summarize retrieved documentation.",
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input_schema={"type": "object", "properties": {}},
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output_schema={"type": "object", "properties": {}},
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outcomes=("done",),
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plan={"name": "summarize_docs", "nodes": [], "edges": []},
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required_capabilities={
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"context7.query-docs": RequiredCapability(
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ref="context7.query-docs",
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kind="tool",
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input_schema_hash="sha256:input",
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output_schema_hash="sha256:output",
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)
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},
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)
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def echo_artifact() -> WorkflowArtifact:
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plan: dict[str, Any] = {
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"name": "echo",
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"input_schema": {
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"type": "object",
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"properties": {"text": {"type": "string"}},
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"required": ["text"],
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},
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"state_schema": {"fields": {"echoed": {"type": "string"}}},
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"output_schema": {
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"type": "object",
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"properties": {"echoed": {"type": "string"}},
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"required": ["echoed"],
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},
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"start": "echo",
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"nodes": [
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{
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"id": "echo",
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"type": "node",
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"node": "demo.personal.echo_tool",
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"input": [input_binding("input.text", "text")],
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"output": [output_binding("echoed", "state.echoed")],
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}
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],
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"edges": [{"from": "echo", "outcome": "ok", "to": "__end__"}],
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}
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return WorkflowArtifact(
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id="echo",
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version=1,
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title="Echo",
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input_schema=plan["input_schema"],
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output_schema=plan["output_schema"],
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outcomes=("completed",),
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plan=plan,
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required_capabilities={
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"demo.echo_tool": RequiredCapability(
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ref="demo.echo_tool",
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kind="node_spec",
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)
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},
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)
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def echo_draft() -> dict[str, Any]:
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return {
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"name": "echo",
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"input_schema": {
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"type": "object",
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"properties": {"text": {"type": "string"}},
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"required": ["text"],
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},
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"state_schema": {"fields": {"echoed": {"type": "string"}}},
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"output_schema": {
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"type": "object",
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"properties": {"echoed": {"type": "string"}},
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"required": ["echoed"],
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},
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"start": "echo",
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"steps": {
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"echo": {
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"use": "demo.personal.echo_tool",
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"input": [
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{
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"target": {"root": "local", "parts": ["text"]},
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"path": {"root": "input", "parts": ["text"]},
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}
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],
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"output": [
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{
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"source": {"root": "local", "parts": ["echoed"]},
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"target": {"root": "state", "parts": ["echoed"]},
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}
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],
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}
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},
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"routes": {"echo": {"ok": "__end__"}},
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}
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def logical_echo_artifact() -> WorkflowArtifact:
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a = echo_artifact()
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plan = dict(a.plan)
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nodes = [dict(node) for node in plan["nodes"]]
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nodes[0]["node"] = "demo.echo_tool"
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plan["nodes"] = nodes
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return a.model_copy(
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update={
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"id": "logical_echo",
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"plan": plan,
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}
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)
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def failing_artifact() -> WorkflowArtifact:
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plan: dict[str, Any] = {
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"name": "fail",
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"input_schema": {
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"type": "object",
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"properties": {"message": {"type": "string"}},
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"required": ["message"],
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},
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"state_schema": {"fields": {"echoed": {"type": "string"}}},
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"output_schema": {
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"type": "object",
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"properties": {"echoed": {"type": "string"}},
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},
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"start": "fail",
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"nodes": [
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{
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"id": "fail",
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"type": "node",
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"node": "demo.personal.failing_tool",
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"input": [input_binding("input.message", "message")],
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"output": [output_binding("echoed", "state.echoed")],
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}
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],
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"edges": [{"from": "fail", "outcome": "ok", "to": "__end__"}],
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}
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return WorkflowArtifact(
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id="fail",
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version=1,
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title="Fail",
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input_schema=plan["input_schema"],
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output_schema=plan["output_schema"],
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outcomes=("completed",),
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plan=plan,
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required_capabilities={
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"demo.failing_tool": RequiredCapability(
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ref="demo.failing_tool",
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kind="node_spec",
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)
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},
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)
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def custom_reducer_artifact() -> WorkflowArtifact:
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plan: dict[str, Any] = {
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"name": "multiply",
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"input_schema": {
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"type": "object",
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"properties": {
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"total": {"type": "integer"},
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"amount": {"type": "integer"},
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},
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"required": ["total", "amount"],
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},
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"state_schema": {
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"type": "object",
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"properties": {
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"total": {
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"type": "integer",
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"reducer": "custom.multiply",
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}
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},
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},
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"output_schema": {
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"type": "object",
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"properties": {"total": {"type": "integer"}},
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"required": ["total"],
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},
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"start": "amount",
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"nodes": [
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{
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"id": "amount",
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"type": "node",
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"node": "demo.personal.amount_tool",
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"input": [input_binding("input.amount", "amount")],
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"output": [output_binding("amount", "state.total")],
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}
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],
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"edges": [{"from": "amount", "outcome": "ok", "to": "__end__"}],
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}
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return WorkflowArtifact(
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id="multiply",
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version=1,
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title="Multiply",
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input_schema=plan["input_schema"],
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output_schema=plan["output_schema"],
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outcomes=("completed",),
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plan=plan,
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required_capabilities={
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"demo.amount_tool": RequiredCapability(
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ref="demo.amount_tool",
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kind="node_spec",
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),
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"custom.multiply": RequiredCapability(
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ref="custom.multiply",
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kind="reducer",
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),
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},
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)
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