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a7af461cdb
The control plane gains senses — cheap, deterministic, no LLM:
- lyra/perceive.py: lexicon+signal heuristic → {sentiment, intensity, tilt, kind:
emotional|strategic|meta|build|casual}. Good at the action-relevant signal,
especially tilt (the mental-game core). Word-boundary matching so 'line' doesn't
fire inside 'pipeline'.
- mind: _perceive fills ctx.moment; _route keeps the manual mode as the dominant
frame but, on a genuinely charged moment, adds a per-turn register nudge — tilt →
"meet him there, warm and steady, don't clip into logging"; up/energized → "match
his energy." Neutral turns get nothing (don't over-narrate). Injected via
build_messages(moment=...). Logged to /logs for observability.
- tests: perceive read (tilt/strategy/up/build/casual) + route nudge on/off.
Suite 92 green, ruff clean.
Complements modes (manual frame) — perceive refines register within it, doesn't
override. Model routing (mind/mouth) is P3.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
98 lines
4.0 KiB
Python
98 lines
4.0 KiB
Python
"""Perceive: read the moment from what Brian just said — cheap, deterministic, no LLM.
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The control plane's senses. A lexicon + signal heuristic that estimates emotional
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charge (sentiment, intensity, tilt) and the kind of turn (emotional / strategic /
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meta / build / casual). It's rough on purpose — the point of the society-of-parts
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design is that *most* parts are free heuristics and the LLM is the exception.
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What it's GOOD at: catching the obvious, action-relevant signal — especially tilt
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(the mental-game core of her job). What it's NOT: nuanced understanding (that's the
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LLM's job downstream). `route` turns this read into a per-turn register nudge.
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"""
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from __future__ import annotations
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import re
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# Negative / tilt charge — frustration, downswing, mental-game trouble.
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_NEG = (
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"tilt", "tilted", "steaming", "steam", "frustrated", "pissed", "angry", "annoyed",
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"hate", "sick of", "fed up", "card dead", "carddead", "cold deck", "brutal", "cooler",
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"punt", "punted", "spew", "spewing", "stuck", "losing", "bad beat", "badbeat",
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"unlucky", "rigged", "sigh", "ugh", "fml", "can't win", "cant win", "miserable",
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"over it", "fuck this", "hate this", "can't catch", "cant catch",
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)
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# Positive / up charge — running good, energized.
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_POS = (
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"great", "awesome", "love", "crushing", "running good", "rungood", "hell yeah",
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"let's go", "lets go", "stoked", "pumped", "feeling good", "on fire", "dialed",
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"killing it", "in the zone", "so good", "amazing",
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)
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_PROFANITY = ("fuck", "fucking", "shit", "damn", "bullshit", "fml")
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# Strategic / poker-analysis cues.
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_STRATEGY = (
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"fold", "call", "raise", "3bet", "three-bet", "range", "equity", "gto", "bluff",
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"value", "river", "turn", "flop", "preflop", "pot odds", "outs", "should i",
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"what would you", "sizing", "check-raise", "overbet", "line",
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)
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# Meta / about-her cues.
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_META = (
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"do you", "are you", "yourself", "conscious", "sentient", "you feel", "you exist",
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"your thoughts", "your mind", "who are you", "what are you", "your own",
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)
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# Building / technical cues.
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_BUILD = (
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"code", "function", "bug", "build", "implement", "refactor", "architecture",
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"prompt", "python", "commit", "deploy", "pipeline", "algorithm", "repo", "api",
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"schema", "module", "wire it", "the model",
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)
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def _clamp(x: float, lo: float = 0.0, hi: float = 1.0) -> float:
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return max(lo, min(hi, x))
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def _hits(text: str, lexicon: tuple[str, ...]) -> int:
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"""Count lexicon matches. Multi-token terms match as substrings ('card dead');
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single words match on word boundaries so 'line' doesn't fire inside 'pipeline'."""
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n = 0
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for term in lexicon:
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if " " in term or "-" in term or "'" in term:
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n += 1 if term in text else 0
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else:
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n += 1 if re.search(rf"\b{re.escape(term)}\b", text) else 0
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return n
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def read(user_msg: str) -> dict:
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"""Estimate the emotional charge + kind of this turn. Returns
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{sentiment: -1..1, intensity: 0..1, tilt: 0..1, kind: str}."""
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t = (user_msg or "").lower()
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words = re.findall(r"[a-z']+", t)
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neg = _hits(t, _NEG)
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pos = _hits(t, _POS)
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prof = _hits(t, _PROFANITY)
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exclam = user_msg.count("!")
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caps = sum(1 for w in re.findall(r"[A-Za-z]{2,}", user_msg) if w.isupper())
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short_and_hot = len(words) <= 6 and (neg or exclam or prof)
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intensity = _clamp(0.2 * exclam + 0.25 * caps + 0.3 * prof + (0.2 if short_and_hot else 0))
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sentiment = _clamp((pos - neg) * 0.5, -1.0, 1.0)
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tilt = _clamp(0.35 * neg + 0.5 * intensity) if (neg or prof) else 0.0
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if tilt >= 0.4 or (neg and sentiment < 0):
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kind = "emotional"
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elif _hits(t, _STRATEGY):
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kind = "strategic"
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elif _hits(t, _META):
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kind = "meta"
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elif _hits(t, _BUILD):
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kind = "build"
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elif pos and intensity >= 0.3:
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kind = "emotional" # up/energized still wants an emotional read
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else:
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kind = "casual"
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return {"sentiment": round(sentiment, 2), "intensity": round(intensity, 2),
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"tilt": round(tilt, 2), "kind": kind}
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