First sub-project of the "make contact feel real" arc (candle rituals, quantum RNG, tuning, progression, escalation to follow as separate specs). Defines the stability-score contract shared between the backend audio degradation and frontend text-glitch halves so they can build in parallel.
3.7 KiB
Possession Presentation Layer — design
First sub-project of a larger "make contact feel real" arc (candle rituals, quantum RNG, tuning controls, account progression, session escalation — each gets its own later spec). This one: make a successful Direct Contact reply feel like a spirit is fighting through static to possess the channel, rather than a chat bubble appearing. Cosmetic only — the stored transcript and reply text are unaffected; only the live presentation (text stream + voice) carries the effect.
Contract
A single number, stability (0.05–0.98, higher = cleaner possession),
computed once per reply on the backend and shared by both halves of this
build:
# backend/app/possession.py
def compute_stability(rarity: str, magnitude: float, rng: Callable[[], float] = random.random) -> float
- Base by rarity:
common=0.35, uncommon=0.5, rare=0.65, mythic=0.8(rarer spirits hold the channel more steadily). + min(0.15, magnitude / 100)— the anomaly magnitude that most recently triggered contact; a stronger signal, a cleaner line.+ rng()jitter scaled to±0.1.- Clamped to
[0.05, 0.98]. rngis injectable specifically so the later quantum-RNG sub-project can swap in real entropy without touching call sites.
_handle_question in backend/app/ws.py computes this once per question
(using state.entity.rarity_tier and the magnitude of the most recent
anomaly in state.anomalies, defaulting to 50 if none yet) and adds it to
the existing reply_start frame:
{"type": "reply_start", "stability": 0.62}
Backend half (audio degradation)
synthesize_spirit_voice(text, voice, voice_profile, instability=0.0) in
backend/app/tts/piper.py gains an instability param (0.0–1.0,
i.e. 1 - stability) that scales up the noise_level and bitcrush_bits
already passed to apply_effects — do not touch effects.py itself, only
the params synthesize_spirit_voice feeds it. Only the "reply" kind
utterance in _speak (the Direct Contact answer) passes a non-zero
instability; greetings/fragments/ambient whispers are unaffected by this
spec.
Frontend half (text glitch renderer)
frontend/src/lib/possession.ts — pure function(s) that take the
true-so-far streamed text, the stability score, and a tick/frame counter,
and return a display string with corruption bursts and brief stutters that
self-correct. Lower stability = more frequent/longer corruption; stability
above ~0.85 is nearly clean (a subtle flicker only). Must be deterministic
given its inputs (seed any internal randomness from the tick counter, not
Math.random()) so it's unit-testable.
Wire into frontend/src/state/seance.tsx: extend replyStreaming with a
stability: number field, populated from reply_start's stability
(default 1.0 if absent). Wire into frontend/src/components/Transcript.tsx:
render the streaming line through the glitch function instead of raw text,
driven by a ticking interval while streaming.active.
Testing
- Backend: unit tests for
compute_stability(rarity ordering, magnitude bonus, clamping, injected rng determinism) and for theinstability→params scaling insynthesize_spirit_voice. One WS integration test assertingreply_startcarries astabilityfield in range. - Frontend: unit tests for the glitch renderer's pure functions at known low/high stability values (corruption rate, self-correction, determinism for a fixed tick sequence).
Explicitly out of scope here
New WS frame types for interleaved glitch tokens, structural UI takeover, candle rituals, quantum RNG source, tuning dial, account progression, session escalation — all separate later specs per the arc this belongs to.