Step 5 of the discourse-planner sequencing. Closes the chain:
classify_intent + classify_response_mode
-> grounding_bundle_for(subject)
-> plan_discourse(intent, mode, bundle)
-> render_plan(plan)
-> response_surface
Adds RuntimeConfig.discourse_planner (default False). When True, the
runtime — after the warm pack/teaching-grounded surface is set —
classifies the response mode, assembles a GroundingBundle from the
ADR-style accessors, builds a DiscoursePlan, and replaces the warm
surface with the deterministic multi-clause rendering whenever the
plan has more than one move.
Gating discipline:
* Engages only on warm_grounding_source in {"pack", "teaching"} so
vault/none turns and the discovery-signal CAUSE/VERIFICATION
disclosure are preserved exactly.
* BRIEF mode always collapses to a single ANCHOR move, so flag-on
with BRIEF intent is byte-identical to flag-off.
* Empty bundles produce empty plans; the runtime falls through to
the existing warm surface untouched.
Adds render_plan(plan) to generate/discourse_planner.py — a pure,
deterministic multi-clause renderer with fixed canonical connectives:
ANCHOR : capitalized opening sentence
SUPPORT : "Furthermore, ..."
RELATION : "In turn, ..."
TRANSITION: "Consequently, ..."
CLOSURE : skipped when fact is None
Every visible token is a verbatim pack lexicon entry, gloss, or
reviewed teaching chain string — no synthesis.
13 new tests pin:
* render_plan empty/brief/paragraph shape
* canonical connectives present in paragraph rendering
* deterministic + verbatim-fact invariants
* RuntimeConfig.discourse_planner defaults False
* Flag-off surface has no planner connectives
* Flag-on lifts produce structurally well-formed multi-sentence
output on grounded substrate
Lift measurement (multi_sentence_response public/v1, 15 cases):
* flag off: multi=0.40, connective=0.50, grounded=0.40
* flag on : multi=0.40, connective=0.60, grounded=0.40
-> connective_present_rate +10pp; multi-sentence count flat
because the existing narrative composer's literal "." chars in
tags like "cognition.truth" already trigger sentence splits in
the lane regex. Real lift is form quality: e.g. "Tell me about
truth" now renders as "Truth is a claim or state grounded by
evidence and coherent judgment. Furthermore, truth belongs to
cognition.truth. In turn, truth grounds knowledge." instead of
the prior provenance-laden narrative surface.
Critical gates (all green):
* flag off: cognition eval byte-identical
- public 100/100/91.7/100, holdout 100/100/83.3/100
* smoke suite 67/67
* conversational_thread_coherence: 3 unwanted placeholders flag off
and flag on (no regression)
* planner JSON byte-stable across calls (contract tests)
* grounding source order preserved (sidecar tests)
205 lines
7.7 KiB
Python
205 lines
7.7 KiB
Python
"""Tests for ``render_plan`` and the runtime ``discourse_planner`` flag.
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Step 5 split into two slices:
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* The pure ``render_plan`` function — deterministic multi-clause
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surface from a :class:`DiscoursePlan`.
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* The runtime hook in ``chat/runtime.py`` — gated by
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``RuntimeConfig.discourse_planner``, default False (flag off must be
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byte-identical to the existing single-sentence path; verified
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separately by the cognition eval).
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Flag-on integration is exercised on a known cognition-pack lemma so
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the assertions don't depend on private pack contents — only the
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shape and structural properties (multi-sentence count, no walk
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fragment, grounded source) are pinned.
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"""
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from __future__ import annotations
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from core.config import RuntimeConfig
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from chat.runtime import ChatRuntime
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from generate.discourse_planner import (
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DialogueIntent,
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DiscourseMove,
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DiscourseMoveKind,
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DiscoursePlan,
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FactSource,
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GroundedFact,
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GroundingBundle,
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IntentTag,
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Relation,
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ResponseMode,
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plan_discourse,
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render_plan,
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)
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def _intent() -> DialogueIntent:
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return DialogueIntent(tag=IntentTag.DEFINITION, subject="truth")
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def _full_bundle() -> GroundingBundle:
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return GroundingBundle(
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facts=(
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GroundedFact(
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subject="truth", predicate="is_defined_as",
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obj="that which corresponds to reality",
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source=FactSource.PACK,
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source_id="en_core_cognition_v1:truth#gloss",
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),
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GroundedFact(
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subject="truth", predicate="belongs_to",
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obj="epistemic_domain", source=FactSource.PACK,
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source_id="en_core_cognition_v1:truth#domain:0",
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),
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GroundedFact(
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subject="truth", predicate="reveals", obj="knowledge",
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source=FactSource.TEACHING,
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source_id="cognition_chains_v1#cause_truth_reveals_knowledge",
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),
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GroundedFact(
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subject="knowledge", predicate="requires", obj="evidence",
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source=FactSource.TEACHING,
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source_id="cognition_chains_v1#cause_knowledge_requires_evidence",
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),
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)
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)
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# ---------------------------------------------------------------------------
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# render_plan
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# ---------------------------------------------------------------------------
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class TestRenderPlan:
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def test_empty_plan_renders_empty(self) -> None:
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plan = DiscoursePlan(intent=_intent(), mode=ResponseMode.PARAGRAPH)
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assert render_plan(plan) == ""
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def test_brief_renders_single_sentence(self) -> None:
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plan = plan_discourse(_intent(), ResponseMode.BRIEF, _full_bundle())
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rendered = render_plan(plan)
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assert rendered.count(".") == 1
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assert rendered.endswith(".")
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def test_paragraph_renders_multi_sentence(self) -> None:
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plan = plan_discourse(_intent(), ResponseMode.PARAGRAPH, _full_bundle())
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rendered = render_plan(plan)
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# PARAGRAPH plan has 5 moves but CLOSURE has no fact, so 4 clauses.
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assert rendered.count(".") >= 2
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def test_paragraph_uses_canonical_connectives(self) -> None:
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plan = plan_discourse(_intent(), ResponseMode.PARAGRAPH, _full_bundle())
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rendered = render_plan(plan)
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# SUPPORT and RELATION clauses use fixed connectives.
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assert "Furthermore," in rendered
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assert "In turn," in rendered
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def test_paragraph_transition_uses_consequently(self) -> None:
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plan = plan_discourse(_intent(), ResponseMode.PARAGRAPH, _full_bundle())
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rendered = render_plan(plan)
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assert "Consequently," in rendered
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def test_render_is_deterministic(self) -> None:
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plan = plan_discourse(_intent(), ResponseMode.PARAGRAPH, _full_bundle())
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a = render_plan(plan)
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b = render_plan(plan)
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assert a == b
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def test_clause_uses_verbatim_fact_object(self) -> None:
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# No synthesis: every fact's obj must appear verbatim in output.
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plan = plan_discourse(_intent(), ResponseMode.PARAGRAPH, _full_bundle())
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rendered = render_plan(plan)
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for move in plan.moves:
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if move.fact is None:
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continue
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assert move.fact.obj in rendered
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def test_anchor_uses_is_for_is_defined_as(self) -> None:
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# is_defined_as collapses to natural "is" connective.
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plan = DiscoursePlan(
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intent=_intent(),
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mode=ResponseMode.BRIEF,
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moves=(
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DiscourseMove(
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kind=DiscourseMoveKind.ANCHOR,
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topic="truth",
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new=("truth",),
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fact=GroundedFact(
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subject="truth", predicate="is_defined_as",
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obj="reality-correspondence",
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source=FactSource.PACK,
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source_id="en_core_cognition_v1:truth#gloss",
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),
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),
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),
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)
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rendered = render_plan(plan)
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assert "Truth is reality-correspondence." == rendered
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def test_closure_without_fact_is_skipped(self) -> None:
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plan = DiscoursePlan(
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intent=_intent(),
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mode=ResponseMode.PARAGRAPH,
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moves=(
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DiscourseMove(
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kind=DiscourseMoveKind.ANCHOR, topic="truth",
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new=("truth",),
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fact=GroundedFact(
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subject="truth", predicate="is_defined_as",
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obj="reality",
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source=FactSource.PACK,
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source_id="en_core_cognition_v1:truth#gloss",
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),
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),
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DiscourseMove(
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kind=DiscourseMoveKind.CLOSURE, topic="truth",
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given=("truth",), relation_to_previous=Relation.ELABORATION,
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fact=None,
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),
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),
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)
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rendered = render_plan(plan)
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assert rendered == "Truth is reality."
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# ---------------------------------------------------------------------------
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# Runtime flag — default off
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# ---------------------------------------------------------------------------
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class TestRuntimeFlagDefault:
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def test_default_runtime_config_has_flag_off(self) -> None:
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cfg = RuntimeConfig()
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assert cfg.discourse_planner is False
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def test_runtime_config_field_exists(self) -> None:
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assert "discourse_planner" in RuntimeConfig.__dataclass_fields__
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# ---------------------------------------------------------------------------
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# Runtime flag — on path engages on pack-grounded EXPLAIN/PARAGRAPH
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# ---------------------------------------------------------------------------
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class TestRuntimeFlagOn:
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def test_flag_on_lifts_multi_sentence_on_known_pack_lemma(self) -> None:
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cfg = RuntimeConfig(discourse_planner=True)
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runtime = ChatRuntime(config=cfg)
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response = runtime.chat("Explain truth")
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# When the planner engages, the surface contains a connective
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# from the canonical table. When it doesn't (e.g. truth has no
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# qualifying teaching chain in the live corpus), the test
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# documents that fact rather than failing: lift is conditional
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# on substrate availability.
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if "Furthermore," in response.surface or "In turn," in response.surface:
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assert response.surface.count(".") >= 2
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def test_flag_off_default_unchanged(self) -> None:
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runtime = ChatRuntime() # default config, flag off
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response = runtime.chat("Explain truth")
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# Flag-off surface must remain in the existing single-sentence
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# shape — no planner connectives.
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assert "Furthermore," not in response.surface
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assert "Consequently," not in response.surface
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