feat(profiler/behave_shell): emit motor.input_modality

BEHAVE-EXTRACTOR.md Phase A Step 2. The first primitive — picked
first because it has the highest discriminative value (HUMAN vs
everyone) and the simplest implementation (paste-event ratio over
total inputs).

* _features/motor.py:input_modality(ctx) emits one Observation
  per session in {typed, pasted, mixed} with confidence 0.75 / 0.70.
* _features/_emit.py centralises the make_observation helper so
  every feature module gets the same Window/source/evidence_ref
  boilerplate without copy-paste.
* Thresholds inherited from the prototype's calibration history
  (MODALITY_PASTED_MIN=0.40, MODALITY_TYPED_MAX=0.05).
* Zero-input session skips emission — registry doesn't admit
  "unknown" here.

Tests: pure-typed → typed, pure-pasted → pasted, mixed → mixed,
output-only session → no observation, full envelope round-trip.
This commit is contained in:
2026-05-03 07:47:38 -04:00
parent c9a81a23c2
commit 879f5e731b
5 changed files with 153 additions and 10 deletions

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@@ -3,9 +3,6 @@
Each entry takes a ``SessionContext`` and yields zero or more
``Observation`` instances. Adding a primitive = adding a function in a
sibling module and appending it to ``FEATURES``.
Step 0 ships an empty tuple — extract_session() is wired but emits
nothing until Step 2.
"""
from __future__ import annotations
@@ -14,7 +11,10 @@ from typing import Callable, Iterable
from decnet_behave_core.spec.envelope import Observation
from decnet.profiler.behave_shell._ctx import SessionContext
from decnet.profiler.behave_shell._features.motor import input_modality
FeatureFn = Callable[[SessionContext], Iterable[Observation]]
FEATURES: tuple[FeatureFn, ...] = ()
FEATURES: tuple[FeatureFn, ...] = (
input_modality,
)

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@@ -0,0 +1,32 @@
"""Helper for building registry-valid :class:`Observation` records.
Every feature module would otherwise repeat the same Window /
source / evidence_ref boilerplate. This helper centralises it and is
the one place to reach when emission semantics change (e.g. when we
start parametrising windows on a per-primitive basis).
"""
from __future__ import annotations
from typing import Any
from decnet_behave_core.spec.envelope import Observation, Window
from decnet.profiler.behave_shell._ctx import SessionContext
def make_observation(
ctx: SessionContext,
*,
primitive: str,
value: Any,
confidence: float,
) -> Observation:
"""Build one :class:`Observation` for the whole-session window."""
return Observation(
primitive=primitive,
value=value,
confidence=confidence,
window=Window(start_ts=ctx.t_start, end_ts=ctx.t_end),
source=ctx.source,
evidence_ref=ctx.evidence_ref,
)

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@@ -0,0 +1,45 @@
"""``motor.*`` feature functions.
Step 2: ``motor.input_modality`` — typed / pasted / mixed.
Step 3: ``motor.paste_burst_rate`` — none / occasional / habitual.
"""
from __future__ import annotations
from typing import Iterator
from decnet_behave_core.spec.envelope import Observation
from decnet.profiler.behave_shell._ctx import SessionContext
from decnet.profiler.behave_shell._features._emit import make_observation
from decnet.profiler.behave_shell._thresholds import (
MODALITY_PASTED_MIN,
MODALITY_TYPED_MAX,
)
def input_modality(ctx: SessionContext) -> Iterator[Observation]:
"""Emit ``motor.input_modality`` ∈ {typed, pasted, mixed}.
Ratio of paste-class events to total inputs. Empty input → skip
emission entirely (the registry doesn't admit ``unknown`` here
and fabricating ``typed`` for a zero-input session is dishonest).
"""
n = len(ctx.input_events)
if n == 0:
return
ratio = ctx.paste_event_count / n
if ratio >= MODALITY_PASTED_MIN:
modality = "pasted"
confidence = 0.75
elif ratio <= MODALITY_TYPED_MAX:
modality = "typed"
confidence = 0.75
else:
modality = "mixed"
confidence = 0.70
yield make_observation(
ctx,
primitive="motor.input_modality",
value=modality,
confidence=confidence,
)