mirror of
https://github.com/langgenius/dify.git
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684 lines
26 KiB
Python
684 lines
26 KiB
Python
"""Pure diagnostic views of the qualified native HTTP or Code profile graph.
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Structural qualification is not admission, authorization, binding provenance or
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proof of dispatch. The trusted host must reload the protected request/ref/profile,
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features and current Workflow revision. This component never changes operational
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events, runtime outputs, variable pools, filters, journals or checkpoint data.
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Every observer must request its own projection before any serialization/offload.
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"""
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from __future__ import annotations
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import math
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from collections.abc import Mapping, Sequence
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from datetime import datetime, timezone
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from typing import Any, Literal, NoReturn, Self, overload
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from graphon.engine.layer import ExecutionLimitsLayer, Layer
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from graphon.engine_events import (
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EngineEvent,
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GraphEdgeSkippedEvent,
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GraphEdgeTakenEvent,
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GraphRunAbortedEvent,
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GraphRunFailedEvent,
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GraphRunPartialSucceededEvent,
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GraphRunPausedEvent,
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GraphRunStartedEvent,
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GraphRunSucceededEvent,
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NodeEvent,
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NodeRunExceptionEvent,
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NodeRunFailedEvent,
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NodeRunIterationFailedEvent,
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NodeRunIterationNextEvent,
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NodeRunIterationStartedEvent,
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NodeRunIterationSucceededEvent,
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NodeRunLoopFailedEvent,
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NodeRunLoopNextEvent,
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NodeRunLoopStartedEvent,
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NodeRunLoopSucceededEvent,
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NodeRunPauseRequestedEvent,
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NodeRunReasoningChunkEvent,
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NodeRunRetryEvent,
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NodeRunStartedEvent,
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NodeRunStreamChunkEvent,
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NodeRunSucceededEvent,
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)
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from graphon.entities.pause_reason import SchedulingPause
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from graphon.entities.workflow_start_reason import WorkflowStartReason
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from graphon.enums import WorkflowNodeExecutionMetadataKey as Metadata
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from graphon.enums import WorkflowNodeExecutionStatus
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from graphon.model_runtime.entities.llm_entities import LLMUsage
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from graphon.node_events.base import NodeRunResult
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from graphon.nodes.end.entities import EndNodeData
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from graphon.nodes.iteration.entities import IterationNodeData, IterationStartNodeData
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from graphon.nodes.loop.entities import LoopEndNodeData, LoopNodeData, LoopStartNodeData
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from graphon.nodes.start.entities import StartNodeData
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from graphon.variables.input_entities import VariableEntityType
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from graphon.variables.segments import (
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ArrayAnySegment,
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ArrayBooleanSegment,
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ArrayFileSegment,
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ArrayNumberSegment,
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ArrayObjectSegment,
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ArrayStringSegment,
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BooleanSegment,
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FloatSegment,
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IntegerSegment,
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NoneSegment,
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ObjectSegment,
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StringSegment,
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)
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from runtime_contracts.builder.execution import (
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BuilderExecutionPolicyError,
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canonical_digest,
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canonical_json,
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)
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from runtime_contracts.builder.native.contracts import NativeTestContextRef
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from runtime_contracts.builder.native.runtime_contracts import (
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ResolvedNativeTestContext,
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)
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from services.dify_builder.native_testing.context_binding import NativeRuntimeProfile
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from services.dify_builder.native_testing.http_binding import (
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describe_http_resource,
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validate_native_http_profile,
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)
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_REDACTED = "[native content redacted]"
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_REASON = "native_observation_unsupported"
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_ERROR_KINDS = frozenset(
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{
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"HTTPResponseCodeError",
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"HttpRequestNodeError",
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"AuthorizationConfigError",
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"FileFetchError",
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"InvalidHttpMethodError",
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"ResponseSizeError",
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"RequestBodyError",
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"InvalidURLError",
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"native_execution_error",
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}
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)
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# Schema allowlist only: execution/version/class resolution stays with the real
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# native factory. No constructors, replacement registry or executor lives here.
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_SCALAR_SCHEMAS = (
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StartNodeData,
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EndNodeData,
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IterationNodeData,
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IterationStartNodeData,
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LoopNodeData,
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LoopStartNodeData,
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LoopEndNodeData,
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)
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_GRAPH_EVENTS = frozenset(
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{
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GraphRunStartedEvent,
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GraphRunSucceededEvent,
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GraphRunFailedEvent,
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GraphRunPartialSucceededEvent,
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GraphRunAbortedEvent,
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GraphRunPausedEvent,
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GraphEdgeTakenEvent,
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GraphEdgeSkippedEvent,
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}
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)
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_NODE_EVENTS = frozenset(
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{
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NodeRunStartedEvent,
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NodeRunSucceededEvent,
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NodeRunFailedEvent,
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NodeRunExceptionEvent,
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NodeRunRetryEvent,
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NodeRunStreamChunkEvent,
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NodeRunReasoningChunkEvent,
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NodeRunPauseRequestedEvent,
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NodeRunIterationStartedEvent,
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NodeRunIterationNextEvent,
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NodeRunIterationSucceededEvent,
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NodeRunIterationFailedEvent,
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NodeRunLoopStartedEvent,
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NodeRunLoopNextEvent,
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NodeRunLoopSucceededEvent,
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NodeRunLoopFailedEvent,
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}
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)
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_ID_FIELDS = frozenset(
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{
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"id",
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"node_id",
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"in_iteration_id",
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"in_loop_id",
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"predecessor_node_id",
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"edge_id",
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"source_node_id",
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"target_node_id",
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}
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)
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_COUNT_FIELDS = frozenset({"exceptions_count", "retry_index", "index", "steps"})
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_CONTENT_FIELDS = frozenset({"inputs", "outputs", "extras"})
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_HISTORY = "__dify_retry_history" # Existing native retry contract, not an authority key.
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def _refuse() -> NoReturn:
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raise BuilderExecutionPolicyError(_REASON)
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@overload
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def _identity(value: Any, *, optional: Literal[False] = False) -> str: ...
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@overload
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def _identity(value: Any, *, optional: bool) -> str | None: ...
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def _identity(value: Any, *, optional: bool = False) -> str | None:
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if value is None and optional:
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return None
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if type(value) is not str or not value or len(value) > 512:
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_refuse()
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return value
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def _count(value: Any) -> int:
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if type(value) is not int or not 0 <= value <= 2**63 - 1:
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_refuse()
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return value
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def _shape(value: Any, *, depth: int = 0, budget: list[int] | None = None) -> dict[str, Any]:
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"""Validate bounded plain values without rendering objects or leaking keys.
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All children are checked, even when only eight shapes are displayed. The
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Exact native scalar and JSON segments are inspected through their values.
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Empty files segments are allowed; file-bearing segments are not.
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"""
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if budget is None:
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budget = [100_000]
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budget[0] -= 1
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if depth > 24 or budget[0] < 0:
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_refuse()
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kind = type(value)
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if value is None:
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return {"type": "null"}
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if kind is bool:
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return {"type": "boolean"}
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if kind is int:
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return {"type": "integer"}
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if kind is float:
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if not math.isfinite(value):
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_refuse()
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return {"type": "number"}
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if kind is str:
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return {"type": "string", "length": len(value)}
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if kind in (
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NoneSegment,
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StringSegment,
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FloatSegment,
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IntegerSegment,
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BooleanSegment,
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ObjectSegment,
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ArrayAnySegment,
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ArrayStringSegment,
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ArrayNumberSegment,
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ArrayObjectSegment,
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ArrayBooleanSegment,
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):
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return _shape(value.value, depth=depth + 1, budget=budget)
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if kind is ArrayFileSegment and type(value.value) in (list, tuple) and not value.value:
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return {"type": "array", "length": 0}
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if kind is dict:
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if not all(type(key) is str for key in value):
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_refuse()
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shapes = [_shape(item, depth=depth + 1, budget=budget) for item in value.values()]
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return {
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"type": "object",
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"fields": len(value),
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"values": shapes[:8] if depth < 3 else [],
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}
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if kind in (list, tuple):
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shapes = [_shape(item, depth=depth + 1, budget=budget) for item in value]
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return {
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"type": "array",
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"length": len(value),
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"items": shapes[:8] if depth < 3 else [],
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}
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return _refuse()
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def _pause(reason: Any) -> SchedulingPause:
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if type(reason) is not SchedulingPause or type(reason.message) is not str:
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_refuse()
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return SchedulingPause(message=_REDACTED)
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class NativeHttpObservationPolicy:
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"""An immutable-identity structural snapshot, never an execution receipt.
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Instantiate through qualify. No method establishes ownership/currentness or
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describes an unprepared occurrence as dispatched. Optional values preserve
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None for existing diagnostic consumers; all actual content is redacted.
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"""
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def __init__(
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self,
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*,
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graph_json: bytes,
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nodes: dict[str, tuple[str, str]],
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edges: tuple[tuple[str | None, str, str], ...],
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):
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self._graph_json = graph_json
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self._nodes = nodes.copy()
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self._edges = edges
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@classmethod
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def qualify(
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cls,
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*,
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context: ResolvedNativeTestContext,
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profile: NativeRuntimeProfile,
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code_qualification=None,
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) -> Self:
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"""Check actual server profile and descriptor shapes, without protected IO.
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Context has no stored profile/features or serialized Workflow revision
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material. The host must verify them against their real owner first; no
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substitute profile or invented Workflow revision hash is accepted here.
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An admitted scalar graph can have no HTTP resources; the exact empty
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descriptor match still requires every existing node schema and guard.
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"""
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try:
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if type(context) is not ResolvedNativeTestContext or type(profile) is not NativeRuntimeProfile:
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_refuse()
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if type(context.ref) is not NativeTestContextRef:
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_refuse()
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for model in (context, context.ref, profile):
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if model.model_extra or set(model.__dict__) != set(type(model).model_fields):
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_refuse()
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# Unchecked frozen DTO copies can contain arbitrary objects. Inspect
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# plain fields before Pydantic serialization can warn with repr(data).
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profile_data = dict(profile)
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_shape(profile_data)
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from services.dify_builder.native_testing.sandbox.qualification import (
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PROFILE_ID as CODE_PROFILE_ID,
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)
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from services.dify_builder.native_testing.sandbox.qualification import (
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NativeCodeQualification,
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describe_code_resource,
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)
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code_profile = profile.profile_id == CODE_PROFILE_ID
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if code_profile:
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if type(code_qualification) is not NativeCodeQualification:
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_refuse()
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code_qualification.validate_profile(NativeRuntimeProfile.model_validate(profile_data))
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else:
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validate_native_http_profile(NativeRuntimeProfile.model_validate(profile_data))
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context_data = dict(context)
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context_data["ref"] = dict(context.ref)
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_shape(context_data)
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checked = ResolvedNativeTestContext.model_validate(context_data)
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if (
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checked.execution_mode != "native"
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or checked.parent_invocation_id is not None
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or checked.call_depth != 0
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or not checked.native_run_id
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or checked.root_native_run_id != checked.native_run_id
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or checked.input_revision != canonical_digest(checked.inputs)
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):
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_refuse()
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if len(checked.graph_revision) != 64 or any(c not in "0123456789abcdef" for c in checked.graph_revision):
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_refuse()
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graph: dict[str, Any] = checked.graph
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if (
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set(graph) - {"nodes", "edges", "viewport"}
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or type(graph.get("nodes")) is not list
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or type(graph.get("edges")) is not list
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):
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_refuse()
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nodes: dict[str, tuple[str, str]] = {}
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expected = []
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schemas = {schema.model_fields["type"].default: schema for schema in _SCALAR_SCHEMAS}
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for item in graph["nodes"]:
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if type(item) is not dict or type(item.get("data")) is not dict:
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_refuse()
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node_id = _identity(item.get("id"))
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raw = item["data"]
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kind, version = raw.get("type"), raw.get("version", "1")
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if node_id in nodes or type(kind) is not str or version != "1":
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_refuse()
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nodes[node_id] = (kind, version)
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if code_profile and kind in {"code", "template-transform"}:
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expected.append(
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describe_code_resource(
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qualification=code_qualification,
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node_id=node_id,
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raw=raw,
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workflow_revision=checked.graph_revision,
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app_id=checked.app_id,
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workflow_id=checked.workflow_id,
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)
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)
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elif kind == "http-request" and not code_profile:
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expected.append(
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describe_http_resource(
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node_id=node_id,
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raw=raw,
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workflow_revision=checked.graph_revision,
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app_id=checked.app_id,
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workflow_id=checked.workflow_id,
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)
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)
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elif kind in schemas:
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parsed = schemas[kind].model_validate(raw, strict=True)
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if isinstance(parsed, StartNodeData) and any(
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v.type in (VariableEntityType.FILE, VariableEntityType.FILE_LIST) for v in parsed.variables
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):
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_refuse()
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if isinstance(parsed, EndNodeData) and any(
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v.value_type in ("secret", "file", "array[file]") for v in parsed.outputs
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):
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_refuse()
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else:
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_refuse()
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if canonical_json(expected) != canonical_json(list(checked.resource_manifest)):
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_refuse()
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if sum(kind == "start" for kind, _ in nodes.values()) != 1:
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_refuse()
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for item in graph["nodes"]:
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raw = item["data"]
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if raw["type"] in ("loop", "iteration"):
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start = raw.get("start_node_id")
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if start not in nodes or nodes[start][0] != raw["type"] + "-start":
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_refuse()
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edges: list[tuple[str | None, str, str]] = []
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edge_ids: set[str] = set()
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for edge in graph["edges"]:
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if type(edge) is not dict or edge.get("source") not in nodes or edge.get("target") not in nodes:
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_refuse()
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edge_id = edge.get("id")
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if edge_id is not None:
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edge_id = _identity(edge_id)
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if edge_id in edge_ids:
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_refuse()
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edge_ids.add(edge_id)
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edges.append((edge_id, edge["source"], edge["target"]))
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return cls(graph_json=canonical_json(graph), nodes=nodes, edges=tuple(edges))
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except Exception:
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raise BuilderExecutionPolicyError(_REASON) from None
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@overload
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def values(self, values: None) -> None: ...
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@overload
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def values(self, values: Mapping[str, Any]) -> dict[str, Any]: ...
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def values(self, values: Mapping[str, Any] | None) -> dict[str, Any] | None:
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"""Return a fresh explicit marker and bounded typed shape; never raw keys."""
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if values is None:
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return None
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if type(values) is not dict:
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_refuse()
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return {"redacted": True, "shape": _shape(values)}
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@overload
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def error(self, error: None) -> None: ...
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@overload
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def error(self, error: BaseException | str) -> str: ...
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def error(self, error: BaseException | str | None) -> str | None:
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"""Exceptions never have str/repr/args inspected, even for known classes."""
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if error is None:
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return None
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if type(error) is str and error in _ERROR_KINDS:
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return error
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if type(error) is str or isinstance(error, BaseException):
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return "native_execution_error"
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return _refuse()
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def graph(self, graph: Mapping[str, Any]) -> dict[str, Any]:
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"""Project only the pinned graph; expose topology, never node configuration."""
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_shape(graph)
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if canonical_json(graph) != self._graph_json:
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_refuse()
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return {
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"nodes": [
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{
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"id": node_id,
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"data": {
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"type": kind,
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"version": version,
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"title": kind,
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"redacted": True,
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},
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}
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for node_id, (kind, version) in self._nodes.items()
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],
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"edges": [
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{
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**({"id": edge_id} if edge_id is not None else {}),
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"source": source,
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"target": target,
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}
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for edge_id, source, target in self._edges
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],
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"redacted": True,
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}
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def require_layers(self, layers: Sequence[Layer]) -> None:
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"""Only exact native operational limits are qualified in this pure phase.
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Dify persistence/control/retirement adapters need their own later joint
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qualification. A subclass, Debug/OTel layer or caller claim is insufficient.
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"""
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if type(layers) not in (list, tuple) or any(type(layer) is not ExecutionLimitsLayer for layer in layers):
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_refuse()
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def _metadata(self, metadata: Any, *, container_lengths: bool = False) -> dict[str, Any]:
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"""Keep only native correlation/counters in every diagnostic metadata copy.
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String keys from persisted retry attempts share the existing enum-key
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contract. Only container event metadata has the official length fields.
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"""
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if type(metadata) is not dict or any(type(key) not in (str, Metadata) for key in metadata):
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_refuse()
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_shape({key.value if type(key) is Metadata else key: value for key, value in metadata.items()})
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result: dict[str, Any] = {}
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for key, value in metadata.items():
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if key in (
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Metadata.TOTAL_TOKENS,
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Metadata.ITERATION_INDEX,
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Metadata.LOOP_INDEX,
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):
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result[key] = _count(value)
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elif key in (
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Metadata.ITERATION_ID,
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Metadata.LOOP_ID,
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Metadata.PARALLEL_ID,
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Metadata.PARENT_PARALLEL_ID,
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Metadata.PARALLEL_MODE_RUN_ID,
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):
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result[key] = _identity(value)
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elif container_lengths and key in ("iteration_length", "loop_length"):
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result[key] = _count(value)
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return result
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def _process_data(self, data: Any) -> dict[str, Any]:
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projected = self.values(data)
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if projected is None:
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_refuse()
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if _HISTORY in data:
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history = data[_HISTORY]
|
|
if type(history) is not list:
|
|
_refuse()
|
|
projected[_HISTORY] = []
|
|
for attempt in history:
|
|
fields = {
|
|
"retry_index",
|
|
"inputs",
|
|
"process_data",
|
|
"outputs",
|
|
"error",
|
|
"elapsed_time",
|
|
"execution_metadata",
|
|
"created_at",
|
|
"finished_at",
|
|
}
|
|
if type(attempt) is not dict or set(attempt) != fields:
|
|
_refuse()
|
|
elapsed = attempt["elapsed_time"]
|
|
if (
|
|
type(elapsed) not in (float, int)
|
|
or not math.isfinite(elapsed)
|
|
or elapsed < 0
|
|
or _count(attempt["retry_index"]) == 0
|
|
):
|
|
_refuse()
|
|
projected[_HISTORY].append(
|
|
{
|
|
"retry_index": attempt["retry_index"],
|
|
"elapsed_time": elapsed,
|
|
"created_at": _count(attempt["created_at"]),
|
|
"finished_at": _count(attempt["finished_at"]),
|
|
"inputs": self.values(attempt["inputs"]),
|
|
"process_data": self.values(attempt["process_data"]),
|
|
"outputs": self.values(attempt["outputs"]),
|
|
"error": self.error(attempt["error"]),
|
|
"execution_metadata": self._metadata(attempt["execution_metadata"]),
|
|
}
|
|
)
|
|
return projected
|
|
|
|
def _result(self, result: Any) -> NodeRunResult:
|
|
if type(result) is not NodeRunResult or result.model_extra:
|
|
_refuse()
|
|
if (
|
|
type(result.status) is not WorkflowNodeExecutionStatus
|
|
or type(result.llm_usage) is not LLMUsage
|
|
or result.llm_usage != LLMUsage.empty_usage()
|
|
or any(type(item) is not dict for item in (result.inputs, result.outputs, result.process_data))
|
|
or any(type(item) is not str for item in (result.error, result.error_type, result.edge_source_handle))
|
|
):
|
|
_refuse()
|
|
return NodeRunResult(
|
|
status=result.status,
|
|
inputs=self.values(result.inputs),
|
|
outputs=self.values(result.outputs),
|
|
process_data=self._process_data(result.process_data),
|
|
metadata={Metadata(key): value for key, value in self._metadata(result.metadata).items()},
|
|
error=self.error(result.error) if result.error else "",
|
|
error_type=self.error(result.error_type) if result.error_type else "",
|
|
retry_index=_count(result.retry_index),
|
|
edge_source_handle=result.edge_source_handle
|
|
if result.edge_source_handle in ("source", "fail-branch", "success-branch")
|
|
else _REDACTED,
|
|
)
|
|
|
|
def event(self, event: EngineEvent) -> EngineEvent:
|
|
"""Construct an independent real native event from explicit safe fields.
|
|
|
|
Adapters must call this after operational handling and separately for each
|
|
observer. This method neither emits events nor grants native wait/dispatch.
|
|
"""
|
|
cls = type(event)
|
|
if cls not in _GRAPH_EVENTS | _NODE_EVENTS or event.model_extra:
|
|
_refuse()
|
|
if isinstance(event, NodeEvent):
|
|
node_id = _identity(event.node_id)
|
|
if type(event.node_type) is not str or type(event.node_version) is not str:
|
|
_refuse()
|
|
if node_id not in self._nodes or self._nodes[node_id] != (
|
|
event.node_type,
|
|
event.node_version,
|
|
):
|
|
_refuse()
|
|
if cls.__name__.startswith("NodeRunIteration") and event.node_type != "iteration":
|
|
_refuse()
|
|
if cls.__name__.startswith("NodeRunLoop") and event.node_type != "loop":
|
|
_refuse()
|
|
if isinstance(event, GraphEdgeTakenEvent | GraphEdgeSkippedEvent):
|
|
_identity(event.edge_id)
|
|
source, target = (
|
|
_identity(event.source_node_id),
|
|
_identity(event.target_node_id),
|
|
)
|
|
if not any((source, target) == (tail, head) for _, tail, head in self._edges):
|
|
_refuse()
|
|
fields: dict[str, Any] = {}
|
|
raw_fields = dict(event)
|
|
for name in cls.model_fields:
|
|
value = raw_fields[name]
|
|
if name == "container_id":
|
|
fields[name] = "" if value == "" else _identity(value)
|
|
elif name == "frame_id":
|
|
fields[name] = _identity(value)
|
|
elif name in _ID_FIELDS:
|
|
fields[name] = _identity(
|
|
value,
|
|
optional=name in {"in_iteration_id", "in_loop_id", "predecessor_node_id"},
|
|
)
|
|
if name == "predecessor_node_id" and value is not None and value not in self._nodes:
|
|
_refuse()
|
|
elif name in {"node_type", "node_version"}:
|
|
fields[name] = value
|
|
elif name == "node_run_result":
|
|
fields[name] = self._result(value)
|
|
elif name in _COUNT_FIELDS:
|
|
fields[name] = _count(value)
|
|
elif name == "metadata":
|
|
fields[name] = self._metadata(value, container_lengths=True)
|
|
elif name in _CONTENT_FIELDS:
|
|
fields[name] = self.values(value)
|
|
elif name in {"start_at", "finished_at"}:
|
|
if value is None:
|
|
if name == "start_at":
|
|
_refuse()
|
|
elif type(value) is not datetime or (value.tzinfo is not None and type(value.tzinfo) is not timezone):
|
|
_refuse()
|
|
fields[name] = value
|
|
elif name == "node_title":
|
|
if type(value) is not str or not isinstance(event, NodeEvent):
|
|
_refuse()
|
|
fields[name] = event.node_type
|
|
elif name in {"provider_type", "provider_id"}:
|
|
if type(value) is not str:
|
|
_refuse()
|
|
fields[name] = ""
|
|
elif name == "error":
|
|
if type(value) is not str:
|
|
_refuse()
|
|
fields[name] = self.error(value)
|
|
elif name == "reason":
|
|
if cls is GraphRunStartedEvent:
|
|
if type(value) is not WorkflowStartReason:
|
|
_refuse()
|
|
fields[name] = value
|
|
elif cls is NodeRunPauseRequestedEvent:
|
|
fields[name] = _pause(value)
|
|
else:
|
|
fields[name] = self.error(value)
|
|
elif name == "reasons":
|
|
if type(value) is not list:
|
|
_refuse()
|
|
fields[name] = [_pause(reason) for reason in value]
|
|
elif name in {"chunk", "pre_iteration_output", "pre_loop_output"}:
|
|
if name == "chunk" and type(value) is not str:
|
|
_refuse()
|
|
_shape(value)
|
|
fields[name] = _REDACTED
|
|
elif name == "selector":
|
|
_shape(value)
|
|
if not isinstance(event, NodeEvent):
|
|
_refuse()
|
|
fields[name] = [event.node_id, _REDACTED]
|
|
elif name == "source_handle":
|
|
if value is not None and type(value) is not str:
|
|
_refuse()
|
|
fields[name] = None if value is None else _REDACTED
|
|
elif name == "is_final":
|
|
if type(value) is not bool:
|
|
_refuse()
|
|
fields[name] = value
|
|
else:
|
|
_refuse()
|
|
return cls.model_validate(fields)
|