and thats a server we can use

This commit is contained in:
lda
2026-04-30 00:02:23 +07:00 Verified
parent 6cfdb5dcd5
commit 67a3e6a64c
50 changed files with 492 additions and 10 deletions
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from .builder import WorkflowBuilder
from .catalog import NodeCatalog, NodeCatalogEntry
from .conditions import context, exists, expr, input, state
from .mapping import bind_fields, bind_state, merge_maps
from .paths import GraphPath, context_path, graph_path, input_path, state_path
from .spec import (
AsyncRegistryHandler,
NodeReturn,
NodeSpec,
SyncRegistryHandler,
build_async_registry,
build_registry,
node,
)
from .subgraph import subgraph_node
__all__ = [
"NodeCatalog",
"NodeCatalogEntry",
"GraphPath",
"NodeReturn",
"NodeSpec",
"AsyncRegistryHandler",
"SyncRegistryHandler",
"WorkflowBuilder",
"bind_fields",
"build_async_registry",
"build_registry",
"bind_state",
"merge_maps",
"context",
"context_path",
"expr",
"exists",
"graph_path",
"input",
"input_path",
"node",
"state",
"state_path",
"subgraph_node",
]
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from __future__ import annotations
from collections.abc import Mapping
from dataclasses import dataclass, field
from typing import Any, Literal, TypeAlias
from wf_core import (
ConditionNode,
Edge,
ForeachNode,
InterruptNode,
NodeUse,
SchemaRef,
StateSchema,
Workflow,
)
from wf_core.model import Condition as CoreCondition
from .conditions import Expr, compile_condition
from .mapping import PathArg
from .paths import GraphPath
from .spec import NodeSpec
StepRef: TypeAlias = str | NodeUse | ConditionNode | ForeachNode | InterruptNode
MapArg: TypeAlias = Mapping[Any, Any]
def _coerce_path(value: object) -> str:
if isinstance(value, str):
return value
if isinstance(value, GraphPath):
return value.value
raise TypeError(f"unsupported graph path value {value!r}")
def _normalize_mapping(
mapping: MapArg | None,
) -> dict[str, str]:
if mapping is None:
return {}
return {
_coerce_path(source): _coerce_path(destination)
for source, destination in mapping.items()
}
def _step_id(ref: StepRef) -> str:
if isinstance(ref, str):
return ref
return ref.id
@dataclass(slots=True)
class WorkflowBuilder:
name: str
input_schema: SchemaRef
state_schema: StateSchema
output_schema: SchemaRef
start: str
node_specs: dict[str, NodeSpec[Any, Any]] = field(default_factory=dict)
nodes: list[Any] = field(default_factory=list)
edges: list[Edge] = field(default_factory=list)
def use(
self,
spec: NodeSpec[Any, Any],
*,
id: str,
in_map: MapArg | None = None,
out_map: MapArg | None = None,
desc: str | None = None,
) -> NodeUse:
self.node_specs[spec.name] = spec
node = NodeUse(
id=id,
type="node",
node=spec.name,
desc=desc or spec.description,
in_map=_normalize_mapping(in_map),
out_map=_normalize_mapping(out_map),
)
self.nodes.append(node)
return node
def condition(self, *, id: str, check: CoreCondition | Expr) -> ConditionNode:
node = ConditionNode(
id=id,
type="condition",
check=compile_condition(check),
)
self.nodes.append(node)
return node
def foreach(
self,
*,
id: str,
over: PathArg,
as_: str,
mode: Literal["serial", "parallel"] = "serial",
on_item_error: Literal["fail", "collect", "skip"] = "fail",
) -> ForeachNode:
node = ForeachNode.model_validate(
{
"id": id,
"type": "foreach",
"over": _coerce_path(over),
"as": as_,
"mode": mode,
"on_item_error": on_item_error,
}
)
self.nodes.append(node)
return node
def interrupt(
self,
*,
id: str,
kind: str,
request_map: MapArg | None = None,
out_map: MapArg | None = None,
outcomes: list[str] | None = None,
) -> InterruptNode:
node = InterruptNode(
id=id,
type="interrupt",
kind=kind,
request_map=_normalize_mapping(request_map),
out_map=_normalize_mapping(out_map),
outcomes=outcomes or ["submitted"],
)
self.nodes.append(node)
return node
def connect(self, from_: StepRef, outcome: str, to: StepRef) -> None:
self.edges.append(
Edge.model_validate(
{"from": _step_id(from_), "outcome": outcome, "to": _step_id(to)}
)
)
def compile(self) -> Workflow:
node_defs = [spec.to_node_def() for spec in self.node_specs.values()]
return Workflow(
name=self.name,
input_schema=self.input_schema,
state_schema=self.state_schema,
output_schema=self.output_schema,
node_defs=node_defs,
start=self.start,
nodes=self.nodes,
edges=self.edges,
)
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from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from .spec import NodeSpec
@dataclass(slots=True)
class NodeCatalogEntry:
name: str
description: str | None
outcomes: tuple[str, ...]
input_schema: dict[str, Any]
output_schema: dict[str, Any]
@classmethod
def from_spec(cls, spec: NodeSpec[Any, Any]) -> "NodeCatalogEntry":
return cls(
name=spec.name,
description=spec.description,
outcomes=spec.outcomes,
input_schema=spec.input_model.model_json_schema(),
output_schema=spec.output_model.model_json_schema(),
)
@dataclass(slots=True)
class NodeCatalog:
specs: dict[str, NodeSpec[Any, Any]]
@classmethod
def from_specs(cls, *specs: NodeSpec[Any, Any]) -> "NodeCatalog":
return cls(specs={spec.name: spec for spec in specs})
def entries(self) -> list[NodeCatalogEntry]:
return [NodeCatalogEntry.from_spec(spec) for spec in self.specs.values()]
def as_mcp_payload(self) -> dict[str, Any]:
return {
"nodes": [
{
"name": entry.name,
"description": entry.description,
"outcomes": list(entry.outcomes),
"input_schema": entry.input_schema,
"output_schema": entry.output_schema,
}
for entry in self.entries()
]
}
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from __future__ import annotations
from dataclasses import dataclass
from typing import Literal
from wf_core.model import (
BinaryCondition,
Condition,
ExistsCondition,
LiteralOperand,
NotCondition,
PathOperand,
VariadicCondition,
)
from .paths import GraphPath, context_path, input_path, state_path
def _operand(value: object) -> PathOperand | LiteralOperand:
if isinstance(value, PathExpr):
return PathOperand(path=value.path)
if isinstance(value, GraphPath):
return PathOperand(path=value.value)
return LiteralOperand(value=value)
def _path_str(value: PathExpr | GraphPath) -> str:
if isinstance(value, PathExpr):
return value.path
return value.value
@dataclass(frozen=True, slots=True)
class Expr:
condition: Condition
def __and__(self, other: object) -> Expr:
if not isinstance(other, Expr):
return NotImplemented
return Expr(VariadicCondition(op="and", args=[self.condition, other.condition]))
def __or__(self, other: object) -> Expr:
if not isinstance(other, Expr):
return NotImplemented
return Expr(VariadicCondition(op="or", args=[self.condition, other.condition]))
def __invert__(self) -> Expr:
return Expr(NotCondition(op="not", arg=self.condition))
def to_condition(self) -> Condition:
return self.condition
@dataclass(frozen=True, slots=True)
class PathExpr:
path: str
def _binary(self, op: Literal["eq", "ne", "gt", "lt"], other: object) -> Expr:
return Expr(
BinaryCondition(
op=op,
left=PathOperand(path=self.path),
right=_operand(other),
)
)
def eq(self, other: object) -> Expr:
return self._binary("eq", other)
def ne(self, other: object) -> Expr:
return self._binary("ne", other)
def gt(self, other: object) -> Expr:
return self._binary("gt", other)
def lt(self, other: object) -> Expr:
return self._binary("lt", other)
def __eq__(self, other: object) -> Expr: # type: ignore[override] # ty: ignore[invalid-method-override]
return self._binary("eq", other)
def __ne__(self, other: object) -> Expr: # type: ignore[override] # ty: ignore[invalid-method-override]
return self._binary("ne", other)
def __gt__(self, other: object) -> Expr:
return self.gt(other)
def __lt__(self, other: object) -> Expr:
return self.lt(other)
def expr(value: PathExpr | GraphPath) -> PathExpr:
if isinstance(value, PathExpr):
return value
return PathExpr(path=value.value)
def state(field: str) -> PathExpr:
return expr(state_path(field))
def input(field: str) -> PathExpr:
return expr(input_path(field))
def context(field: str) -> PathExpr:
return expr(context_path(field))
def exists(value: PathExpr | GraphPath) -> Expr:
return Expr(ExistsCondition(op="exists", path=_path_str(value)))
def compile_condition(value: Condition | Expr) -> Condition:
if isinstance(value, Expr):
return value.to_condition()
return value
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from __future__ import annotations
from collections.abc import Mapping
from typing import TypeAlias
from .paths import GraphPath
PathArg: TypeAlias = str | GraphPath
def normalize_path(path: PathArg) -> str:
if isinstance(path, GraphPath):
return path.value
return path
def bind_fields(**mapping: PathArg) -> dict[str, str]:
return {
normalize_path(source): destination for destination, source in mapping.items()
}
def bind_state(**mapping: PathArg) -> dict[str, str]:
return {
destination: normalize_path(target) for destination, target in mapping.items()
}
def merge_maps(*maps: Mapping[str, str]) -> dict[str, str]:
merged: dict[str, str] = {}
for mapping in maps:
merged.update(mapping)
return merged
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from __future__ import annotations
from dataclasses import dataclass
@dataclass(frozen=True, slots=True)
class GraphPath:
value: str
def __str__(self) -> str:
return self.value
def graph_path(value: str) -> GraphPath:
return GraphPath(value)
def input_path(field: str) -> GraphPath:
return GraphPath(f"input.{field}")
def state_path(field: str) -> GraphPath:
return GraphPath(f"state.{field}")
def context_path(field: str) -> GraphPath:
return GraphPath(f"context.{field}")
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from __future__ import annotations
from inspect import Parameter, iscoroutinefunction, signature
from collections.abc import Awaitable, Callable
from dataclasses import dataclass
from typing import (
Any,
Generic,
Literal,
TypeVar,
cast,
get_args,
get_origin,
get_type_hints,
overload,
)
from pydantic import BaseModel
from wf_core import NodeDef, RuntimeContext, SchemaRef
InputT = TypeVar("InputT", bound=BaseModel)
OutputT = TypeVar("OutputT", bound=BaseModel)
NodeCallable = Callable[[InputT, RuntimeContext], "NodeReturn[OutputT] | OutputT"]
AsyncNodeCallable = Callable[
[InputT, RuntimeContext], Awaitable["NodeReturn[OutputT] | OutputT"]
]
SyncRegistryHandler = Callable[[dict[str, Any], RuntimeContext], dict[str, Any]]
AsyncRegistryHandler = Callable[
[dict[str, Any], RuntimeContext], Awaitable[dict[str, Any]]
]
def _schema_ref_for(model_type: type[BaseModel]) -> SchemaRef:
return SchemaRef.model_validate(model_type.model_json_schema())
@dataclass(slots=True)
class NodeReturn(Generic[OutputT]):
outcome: str
output: OutputT
def _default_outcome(spec: "NodeSpec[Any, Any]") -> str:
return spec.outcomes[0]
def _coerce_registry_result(
*,
node_name: str,
output_model: type[BaseModel],
default_outcome: str,
raw: NodeReturn[BaseModel] | BaseModel,
) -> dict[str, Any]:
if isinstance(raw, NodeReturn):
if not isinstance(raw.output, output_model):
raise TypeError(
f"node {node_name!r} returned NodeReturn with unsupported output "
f"{type(raw.output)!r}"
)
return {
"outcome": raw.outcome,
"output": raw.output.model_dump(),
}
if isinstance(raw, output_model):
return {"outcome": default_outcome, "output": raw.model_dump()}
raise TypeError(f"node {node_name!r} returned unsupported value {type(raw)!r}")
def _is_basemodel_subclass(value: object) -> bool:
return isinstance(value, type) and issubclass(value, BaseModel)
def _infer_models(
fn: Callable[..., object],
) -> tuple[type[BaseModel], type[BaseModel]]:
hints = get_type_hints(fn, include_extras=True)
params = list(signature(fn).parameters.values())
if len(params) < 2:
raise TypeError("node function must accept at least (payload, ctx) parameters")
payload_param = params[0]
ctx_param = params[1]
if payload_param.kind not in (
Parameter.POSITIONAL_ONLY,
Parameter.POSITIONAL_OR_KEYWORD,
):
raise TypeError("node payload parameter must be positional")
if ctx_param.kind not in (
Parameter.POSITIONAL_ONLY,
Parameter.POSITIONAL_OR_KEYWORD,
):
raise TypeError("node context parameter must be positional")
input_model = hints.get(payload_param.name)
if not _is_basemodel_subclass(input_model):
raise TypeError("node payload annotation must be a pydantic BaseModel subclass")
ctx_type = hints.get(ctx_param.name)
if ctx_type is not RuntimeContext:
raise TypeError("node context annotation must be wf_core.RuntimeContext")
return_type = hints.get("return")
if return_type is None:
raise TypeError("node function must declare a return annotation")
if _is_basemodel_subclass(return_type):
return cast(type[BaseModel], input_model), cast(type[BaseModel], return_type)
origin = get_origin(return_type)
if origin is NodeReturn:
args = get_args(return_type)
if len(args) != 1 or not _is_basemodel_subclass(args[0]):
raise TypeError(
"NodeReturn return annotation must wrap a BaseModel subclass"
)
return cast(type[BaseModel], input_model), cast(type[BaseModel], args[0])
raise TypeError(
"node return annotation must be a BaseModel subclass or NodeReturn[BaseModel]"
)
@dataclass(slots=True)
class NodeSpec(Generic[InputT, OutputT]):
name: str
input_model: type[InputT]
output_model: type[OutputT]
outcomes: tuple[str, ...]
fn: NodeCallable[InputT, OutputT] | AsyncNodeCallable[InputT, OutputT]
description: str | None = None
is_async: bool = False
def __call__(
self,
payload: InputT,
ctx: RuntimeContext,
) -> NodeReturn[OutputT] | OutputT | Awaitable[NodeReturn[OutputT] | OutputT]:
return self.fn(payload, ctx)
def to_node_def(self) -> NodeDef:
return NodeDef(
name=self.name,
input_schema=_schema_ref_for(self.input_model),
output_schema=_schema_ref_for(self.output_model),
outcomes=list(self.outcomes),
)
def to_registry_handler(self) -> SyncRegistryHandler:
if self.is_async:
raise TypeError(
f"node {self.name!r} is async and cannot be exported to the sync registry"
)
def handler(payload: dict[str, Any], ctx: RuntimeContext) -> dict[str, Any]:
parsed = self.input_model.model_validate(payload)
raw = self.fn(parsed, ctx)
return _coerce_registry_result(
node_name=self.name,
output_model=self.output_model,
default_outcome=_default_outcome(self),
raw=cast(NodeReturn[BaseModel] | BaseModel, raw),
)
return handler
def to_async_registry_handler(self) -> AsyncRegistryHandler:
async def handler(
payload: dict[str, Any],
ctx: RuntimeContext,
) -> dict[str, Any]:
parsed = self.input_model.model_validate(payload)
raw_result = self.fn(parsed, ctx)
if self.is_async:
raw = await cast(
Awaitable[NodeReturn[OutputT] | OutputT],
raw_result,
)
else:
raw = cast(NodeReturn[OutputT] | OutputT, raw_result)
return _coerce_registry_result(
node_name=self.name,
output_model=self.output_model,
default_outcome=_default_outcome(self),
raw=cast(NodeReturn[BaseModel] | BaseModel, raw),
)
return handler
@overload
def node(
fn: NodeCallable[InputT, OutputT] | AsyncNodeCallable[InputT, OutputT],
/,
) -> NodeSpec[InputT, OutputT]: ...
@overload
def node(
fn: None = None,
/,
) -> Callable[
[NodeCallable[InputT, OutputT] | AsyncNodeCallable[InputT, OutputT]],
NodeSpec[InputT, OutputT],
]: ...
@overload
def node(
fn: None = None,
/,
*,
name: str | None = None,
input_model: type[InputT] | None = None,
output_model: type[OutputT] | None = None,
outcomes: tuple[str, ...] = ("ok",),
description: str | None = None,
is_async: bool | None = None,
) -> Callable[
[NodeCallable[InputT, OutputT] | AsyncNodeCallable[InputT, OutputT]],
NodeSpec[InputT, OutputT],
]: ...
def node(
fn: NodeCallable[InputT, OutputT]
| AsyncNodeCallable[InputT, OutputT]
| None = None,
*,
name: str | None = None,
input_model: type[InputT] | None = None,
output_model: type[OutputT] | None = None,
outcomes: tuple[str, ...] = ("ok",),
description: str | None = None,
is_async: bool | None = None,
) -> Any:
def decorator(
fn: NodeCallable[InputT, OutputT] | AsyncNodeCallable[InputT, OutputT],
) -> NodeSpec[InputT, OutputT]:
inferred_input_model: type[BaseModel] | None = input_model
inferred_output_model: type[BaseModel] | None = output_model
if inferred_input_model is None or inferred_output_model is None:
inferred_input_model, inferred_output_model = _infer_models(fn)
resolved_name = name or getattr(fn, "__name__", "node")
resolved_is_async = iscoroutinefunction(fn) if is_async is None else is_async
return cast(
NodeSpec[InputT, OutputT],
NodeSpec(
name=resolved_name,
input_model=inferred_input_model,
output_model=inferred_output_model,
outcomes=outcomes,
fn=cast(Any, fn),
description=description or fn.__doc__,
is_async=resolved_is_async,
),
)
if fn is not None:
return decorator(fn)
return decorator
def build_registry(
*specs: NodeSpec[Any, Any],
) -> dict[str, SyncRegistryHandler]:
return _build_registry(specs, export="sync")
def build_async_registry(
*specs: NodeSpec[Any, Any],
) -> dict[str, AsyncRegistryHandler]:
return _build_registry(specs, export="async")
@overload
def _build_registry(
specs: tuple[NodeSpec[Any, Any], ...],
*,
export: Literal["sync"],
) -> dict[str, SyncRegistryHandler]: ...
@overload
def _build_registry(
specs: tuple[NodeSpec[Any, Any], ...],
*,
export: Literal["async"],
) -> dict[str, AsyncRegistryHandler]: ...
def _build_registry(
specs: tuple[NodeSpec[Any, Any], ...],
*,
export: Literal["sync", "async"],
) -> dict[str, Any]:
if export == "sync":
return {spec.name: spec.to_registry_handler() for spec in specs}
if export == "async":
return {spec.name: spec.to_async_registry_handler() for spec in specs}
raise ValueError(f"unknown registry export mode {export!r}")
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from __future__ import annotations
from collections.abc import Mapping
from typing import Any, TypeVar
from pydantic import BaseModel
from wf_core import RuntimeContext, Workflow, execute_workflow
from .spec import NodeSpec
InputT = TypeVar("InputT", bound=BaseModel)
OutputT = TypeVar("OutputT", bound=BaseModel)
def subgraph_node(
*,
name: str,
workflow: Workflow,
registry: Mapping[str, Any],
input_model: type[InputT],
output_model: type[OutputT],
description: str | None = None,
) -> NodeSpec[InputT, OutputT]:
def run_subgraph(payload: InputT, ctx: RuntimeContext) -> OutputT:
child_run = execute_workflow(
workflow,
payload.model_dump(),
registry,
)
return output_model.model_validate(child_run.output)
return NodeSpec(
name=name,
input_model=input_model,
output_model=output_model,
outcomes=("ok",),
fn=run_subgraph,
description=description or f"Subgraph wrapper for {workflow.name}",
is_async=False,
)