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* feat(extensions): add middleware plugin foundation * fix(extensions): stop config resolution from masking extension loading `create_app()` resolved the configured plugin list inside the fail-open guard around `load_extensions()`. CI has no `config.yaml` (gitignored and never generated by the workflow), so `get_app_config()` raised `FileNotFoundError` there and was swallowed as an extension failure -- `load_extensions()` never ran at all, and the four `create_app()` tests in `test_extension_app_loading.py` passed locally but failed on every runner. Resolve the plugin list before the guard. Only an absent `config.yaml` is tolerated, mirroring `_resolve_trace_enabled_for_app_construction()`: `create_app()` runs at import time, and lifespan still performs strict config loading before serving. A `config.yaml` that exists but fails to parse or validate now propagates instead of being reported as an extension failure -- reporting it as the latter silently dropped a `required: true` extension rather than failing the boot. Make the tests config-independent with an autouse `stub_app_config` fixture, following the existing pattern in `test_gateway_lifespan_shutdown.py`, and cover both new branches of the config-resolution boundary. * fix(extensions): bind the run's extension snapshot through subagent delegation The lead-agent path resolves one immutable loaded-extension snapshot per run and binds it through task-store allocation and graph construction, but the subagent path re-read the process-wide singleton at execution time. In production both are the same object, yet a `set_loaded_extensions()` between the lead run's start and a subagent's execution (test teardown, a future hot-reload path) would let one run mix two extension generations — exactly what the documented invariant exists to prevent. The graph-build binding is a ContextVar scoped to synchronous construction, so it has already exited by the time a tool delegates; the snapshot has to travel through runtime context instead. The run worker publishes it under the host-internal `EXTENSION_SNAPSHOT_CONTEXT_KEY` (written after the caller merge, popped when the run has none, so a caller-supplied value is never authoritative), `task_tool` reads it back through the type-checking `resolve_run_extensions()`, and `SubagentExecutor` binds it at construction. Callers outside the Gateway run path — embedded `DeerFlowClient`, standalone LangGraph Server — install no snapshot and keep the existing `get_loaded_extensions()` fallback. * refactor(extensions): defer the ordering table by call, not by a lying tuple `CORE_ORDERING_CONSTRAINTS` was a `tuple` subclass that overrode only `__iter__` and resolved into a class-level `_resolved` side channel. A tuple cannot populate its own storage after construction, so the instance stayed the empty tuple it was built as: `len()` was 0, `bool()` was False, `in` was always False, indexing raised, slicing and `reversed()` came back empty, and it compared unequal to the plain tuples tests substitute for it — all while iteration yielded the real constraints. Only `assert_ordering` consumed it, and only by iterating, so the split went unnoticed. The sibling `_AnchorTable(dict)` uses the same idea soundly because dict is mutable: `self.update()` fills the real storage, making every inherited operation correct. That trick does not survive the port to an immutable type. Replace it with `core_ordering_constraints()`, matching how `stack.py` defers the same kind of table via `_anchors()`. The deferral is kept — it is about dependency direction, not just cycles: `extensions/` is the layer the middleware layer calls into, so a module-scope `agents.middlewares` import here points the dependency backwards and closes a cycle as soon as any middleware imports something under `extensions/` at module level. Resolution stays at `assert_ordering` time, which already runs inside the middleware builder. Tests pin both halves: the returned value is a plain tuple whose len/bool/ membership/indexing/reversal/equality agree with iteration, and a subprocess probe asserts importing `extensions.ordering` does not load the middleware layer while calling the function does.
192 lines
7.1 KiB
Python
192 lines
7.1 KiB
Python
"""The anchor table and the single composition entry point.
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This is where DeerFlow's stack shape is encoded. Two structural facts drive it:
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* The stack is built at two nested points — `build_lead_runtime_middlewares()`
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produces the base, then `build_middlewares()` appends ~18 lead-specific
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middlewares that are all *inner* of it. MODEL_PHYSICAL lands in the second
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group, so extension injection must happen after the final list is assembled,
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never inside the base builder.
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* First item in the list is the outermost wrapper (LangChain composition rule).
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"""
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from __future__ import annotations
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from collections.abc import Sequence
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from deerflow_extension_api import AgentBuildContext, AgentScope, Placement
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from deerflow.extensions.anchors import (
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PlacementAnchor,
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inner_of_last,
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inner_of_last_after,
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innermost,
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outer_of,
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outer_of_last,
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outermost,
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)
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from deerflow.extensions.injection import inject_middlewares
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from deerflow.extensions.ordering import assert_ordering
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from deerflow.extensions.registry import LoadedExtensions
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def _anchors() -> dict[Placement, PlacementAnchor]:
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from deerflow.agents.middlewares.clarification_middleware import ClarificationMiddleware
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from deerflow.agents.middlewares.llm_error_handling_middleware import LLMErrorHandlingMiddleware
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from deerflow.agents.middlewares.safety_finish_reason_middleware import SafetyFinishReasonMiddleware
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from deerflow.agents.middlewares.terminal_response_middleware import TerminalResponseMiddleware
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return {
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# Outer of the retry loop, so one logical decision stays one event even
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# when LLMErrorHandlingMiddleware retries underneath.
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Placement.MODEL_LOGICAL: outer_of(LLMErrorHandlingMiddleware),
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# Inner of every lead-agent request transform. Deliberately NOT
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# innermost(): ClarificationMiddleware sits inner of this point today,
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# and moving the anchor past it would change what "the final request"
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# means.
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Placement.MODEL_PHYSICAL: PlacementAnchor.of(
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inner_of_last_after(
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SafetyFinishReasonMiddleware,
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after=(TerminalResponseMiddleware,),
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),
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inner_of_last(TerminalResponseMiddleware),
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outer_of_last(ClarificationMiddleware),
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innermost(),
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),
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Placement.TOOL_VISIBLE: outermost(),
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# As close to the tool callable as the chain allows. Deliberately NOT
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# inner_of(ToolErrorHandlingMiddleware): SkillToolPolicyMiddleware and
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# ClarificationMiddleware are appended later and also wrap tool calls,
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# so anchoring there left two wrappers inner of "raw" and the placement
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# silently stopped meaning what it says.
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#
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# ClarificationMiddleware remains the one carve-out, the same shape as
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# MODEL_PHYSICAL's above: it must stay last (it short-circuits the tool
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# loop with Command(goto=END)), and it only ever intercepts
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# ask_clarification — it does not transform the result of any tool that
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# actually executes, so TOOL_RAW still sees raw results.
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Placement.TOOL_RAW: PlacementAnchor.of(
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outer_of_last(ClarificationMiddleware),
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innermost(),
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),
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Placement.STANDARD: PlacementAnchor.of(
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outer_of(LLMErrorHandlingMiddleware),
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innermost(),
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),
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}
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class _AnchorTable(dict):
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"""Resolve the table lazily so importing this module stays cheap and
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free of middleware import cycles."""
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_loaded = False
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def _ensure(self) -> None:
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if not _AnchorTable._loaded:
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self.update(_anchors())
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_AnchorTable._loaded = True
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def __getitem__(self, key):
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self._ensure()
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return dict.__getitem__(self, key)
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def get(self, key, default=None):
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self._ensure()
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return dict.get(self, key, default)
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def __iter__(self):
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self._ensure()
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return dict.__iter__(self)
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def __len__(self):
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self._ensure()
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return dict.__len__(self)
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def snapshot(self) -> dict[Placement, PlacementAnchor]:
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"""Return a populated plain-dict copy.
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CPython's ``dict(subclass)`` fast path can copy the underlying storage
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without calling this class's lazy ``__iter__`` or ``__len__`` hooks.
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Callers that need a copy must therefore force resolution explicitly.
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"""
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self._ensure()
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return dict(self)
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PLACEMENT_ANCHORS = _AnchorTable()
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def _placement_anchors_for_scope(scope: AgentScope) -> dict[Placement, PlacementAnchor]:
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if scope != AgentScope.SUBAGENT:
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return PLACEMENT_ANCHORS
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from deerflow.agents.middlewares.system_message_coalescing_middleware import SystemMessageCoalescingMiddleware
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anchors = PLACEMENT_ANCHORS.snapshot()
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anchors[Placement.MODEL_PHYSICAL] = PlacementAnchor.of(
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inner_of_last(SystemMessageCoalescingMiddleware),
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PLACEMENT_ANCHORS[Placement.MODEL_PHYSICAL],
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)
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return anchors
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def compose_with_extensions(
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middlewares: Sequence[object],
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scope: AgentScope,
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ctx: AgentBuildContext | None,
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extensions: LoadedExtensions | None = None,
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) -> list[object]:
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"""Merge extension contributions into a fully-assembled stack and validate.
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Call this once, at the end of the outermost builder. Calling it inside the
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base builder would place MODEL_PHYSICAL contributions above the ~18
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lead-specific middlewares appended afterwards.
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"""
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from deerflow.extensions import get_agent_build_extensions, record_runtime_diagnostic
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resolved = extensions if extensions is not None else get_agent_build_extensions()
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if not resolved.has_middleware_contributors:
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assert_ordering(middlewares, {})
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return middlewares if isinstance(middlewares, list) else list(middlewares)
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if ctx is None:
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raise ValueError("AgentBuildContext is required when middleware extensions are loaded")
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result = list(middlewares)
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result, provenance, diagnostics = inject_middlewares(
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result,
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_placement_anchors_for_scope(scope),
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scope,
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ctx,
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resolved,
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isolation_diagnostic_sink=record_runtime_diagnostic,
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)
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_record_diagnostics(diagnostics)
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assert_ordering(result, provenance)
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return result
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def _record_diagnostics(diagnostics) -> None:
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"""Diagnostics raised while building a stack are logged by their producers;
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this hook exists so the Gateway can also surface them on app.state."""
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from deerflow.extensions import record_runtime_diagnostics
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record_runtime_diagnostics(diagnostics)
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def middleware_implements(middleware: object, hook_name: str) -> bool:
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"""Whether ``middleware`` actually overrides ``hook_name``.
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Placement guarantees are per hook chain, not per list index: a middleware's
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position only means something on the chains it participates in. This is how
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the guarantee tests tell participation from mere presence.
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"""
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from langchain.agents.middleware import AgentMiddleware
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own = getattr(type(middleware), hook_name, None)
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base = getattr(AgentMiddleware, hook_name, None)
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return own is not None and own is not base
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