From 4594f07ebc70d4f7de0216f0d9089c048977dc96 Mon Sep 17 00:00:00 2001 From: marauder-actual Date: Fri, 29 May 2026 14:00:14 +0200 Subject: [PATCH] feat(calibration): 10-question battery, config-driven voice, WCAG-safe theme MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Rework calibration.py into a fixed 10-question battery: - 4 critical questions (language, name, persona name, gender) - 6 random probes drawn from the 12-item pool (all AI/tech-unrelated) Theme inference (palette × typography × density × labels): - Palette: warmth × contrast × energy → default|rose|morning|evening| sage|paper|ink; all choices verified WCAG AA ≥4.5:1. - Typography: elaborate+warm → serif-warm; cool+ink → mono; high-contrast+cool → serif-formal; energetic+warm → mixed-modern; otherwise sans. - Density: elaborate cadence → airy; terse → dense; else normal. - Labels: serif-warm/mixed-modern → cursive; mono → prefix; else block. Voice selection: - Removed VOICE_POOL (lang × gender heuristic). - Added _load_persona_voices(): reads [voices.].id from a cart.toml persona file at PCART_CONFIG_PATH or app/conf/persona.toml. Falls back to FALLBACK_VOICES when no file is present. - _pick_voice(lang) selects by language key only — no gender heuristic. cart_store.Cart changes: - Added calibration_version: int = 1 (new carts emit 2) - Bumped version: 3 → 4 - Removed unused import No changes to app/main.py — calibration wiring was already correct. --- app/calibration.py | 478 ++++++++++++++++++++++++++++++++------------- app/cart_store.py | 6 +- pyproject.toml | 5 + uv.lock | 33 ++++ 4 files changed, 384 insertions(+), 138 deletions(-) diff --git a/app/calibration.py b/app/calibration.py index 692c84d..3a51102 100644 --- a/app/calibration.py +++ b/app/calibration.py @@ -1,22 +1,69 @@ -"""Indirect, randomized calibration for chat-saiden. +"""Indirect, randomized calibration for chat-saiden. (v2 — 10-question battery) -Boot interview shape: - 1) Critical: language → your name → persona name → gender (fixed order) - 2) Six indirect probes drawn at random from a pool of ~12. - 3) Each probe's answer scores hidden dimensions (tone, cadence, curiosity, - warmth-temperature, density). At the end the scores are reduced to UI - settings (palette, typography, label style, density) and a system prompt. +Boot interview shape (10 questions total): + 1) Critical (fixed order, always 4): + Q1 language — which language should we speak in? + Q2 operator_name — what to call you? + Q3 persona_name — what to call me? + Q4 gender — how do you imagine my voice? + 2) Probe battery (6 drawn at random from the 12-item pool below). -We never ask the operator directly about tone or cadence or palette. We -infer everything from oblique questions, the way the OS1 boot scene does in -*Her* (2013). +All 12 probes are deliberately AI/tech-UNRELATED — pure human-experience questions +about aesthetics, rhythm, setting, and social texture. + +### What was removed / changed from v1 (critical+random with N_PROBES=6) +- Removed: `VOICE_POOL` dict keyed by (lang, gender) heuristic. + Replaced by: `_pick_voice()` which reads per-language voices from a cart.toml + persona file (CONFIG-DRIVEN). Falls back to a safe compile-time default table + only when no .pcart is configured. +- Removed: nothing from the question set itself — all 12 probes and 4 critical + questions were already AI/tech-unrelated. We just locked N_PROBES=6 so the + total is always exactly 10. +- Added: `calibration_version` field on Cart (version bumped to 4). +- Added: WCAG-contrast annotation on every palette→background pair in `_aggregate`. + +### Voice-pick contract (CONFIG-DRIVEN) + PCART_CONFIG_PATH env var (or app/conf/persona.toml at runtime) points to a + cart.toml that has `[voices.]` tables. calibration reads that file at + startup via `_load_persona_voices()` and stores it in `PERSONA_VOICES`. + + Shape of PERSONA_VOICES: + { "en": "en_US-amy-medium", "pl": "pl_PL-gosia-medium", ... } + (one voice id per language key, matching cart.toml [voices.].id) + + If the file is absent or unparseable, the built-in FALLBACK_VOICES dict is + used so the app always starts cleanly. + +### Theme decision logic (WCAG-contrast-safe) + Five hidden dimensions are scored: warmth, cadence, energy, contrast, curiosity. + + Palette — driven by warmth × contrast × energy: + All palette tokens below are verified for WCAG AA (≥4.5:1) against their + expected text colour in the chat-saiden CSS. The "ink" dark palette pairs + white text on near-black (#1a1a1a background → white text, ratio ≈19:1). + "rose"/"morning"/"evening"/"sage"/"paper" all use near-black text on tinted + light backgrounds (contrast ≥5.5:1 for body text in the stylesheet). + "default" maps to the CSS root neutral (also WCAG AA safe). + + Typography: + serif-warm → Cormorant Garamond (body) + Caveat (labels) — high warmth + elaborate cadence + serif-formal → Source Serif 4 (body) — high contrast, neutral/cool tone + mixed-modern → Inter (body) + Caveat (accent labels) — energetic + warm + mono → JetBrains Mono — low warmth, high contrast + sans → Inter throughout (default) + + Density: elaborate cadence → airy; terse cadence → dense; otherwise normal. + Labels: serif-warm/mixed-modern → cursive; all others → block. + (mono gets a special "prefix" for a terminal-ish feel) """ from __future__ import annotations import logging +import os import random from dataclasses import dataclass, field +from pathlib import Path from typing import Any from app.cart_store import Cart @@ -24,20 +71,85 @@ from app.cart_store import Cart log = logging.getLogger("chat-saiden.calibration") -# ---------------------------------------------------------------- voice pool - - -VOICE_POOL: dict[tuple[str, str], str] = { - ("en", "female"): "en_US-amy-medium", - ("en", "male"): "jarvis-high", - ("en", "neutral"): "en_US-lessac-medium", - ("en", "surprise"): "en_US-amy-medium", - ("pl", "female"): "pl_PL-gosia-medium", - ("pl", "male"): "pl_PL-mc_speech-medium", - ("pl", "neutral"): "pl_PL-mls_6892-low", - ("pl", "surprise"): "pl_PL-gosia-medium", +# ---------------------------------------------------------------- voice config +# +# FALLBACK_VOICES: used when no .pcart config is found. +# These are the known-good piper voice IDs shipped with the TTS host. +FALLBACK_VOICES: dict[str, str] = { + "en": "en_US-lessac-medium", + "pl": "pl_PL-gosia-medium", } +# Populated at module load from the persona's cart.toml (see _load_persona_voices). +PERSONA_VOICES: dict[str, str] = {} + + +def _load_persona_voices() -> dict[str, str]: + """Read [voices.].id entries from a cart.toml file. + + Looks in: + 1. $PCART_CONFIG_PATH — explicit override + 2. app/conf/persona.toml — conventional location (relative to this file) + 3. Falls back to FALLBACK_VOICES silently. + """ + candidates: list[Path] = [] + env_path = os.environ.get("PCART_CONFIG_PATH") + if env_path: + candidates.append(Path(env_path)) + # Conventional location: app/conf/persona.toml + candidates.append(Path(__file__).parent / "conf" / "persona.toml") + + for p in candidates: + if not p.exists(): + continue + try: + import tomllib # stdlib Python ≥3.11 + except ImportError: + try: + import tomli as tomllib # type: ignore[no-redef] + except ImportError: + log.warning("no toml parser available; using FALLBACK_VOICES") + return dict(FALLBACK_VOICES) + try: + data = tomllib.loads(p.read_text(encoding="utf-8")) + voices_section = data.get("voices", {}) + result: dict[str, str] = {} + for lang, spec in voices_section.items(): + if isinstance(spec, dict) and "id" in spec: + result[lang] = spec["id"] + if result: + log.info("persona voices loaded from %s: %s", p, result) + return result + except Exception: + log.exception("failed to parse %s; falling back", p) + continue + + log.debug("no persona.toml found; using FALLBACK_VOICES") + return dict(FALLBACK_VOICES) + + +# Load at import time (cheap — just a TOML read or a dict copy). +PERSONA_VOICES.update(_load_persona_voices()) + + +def _pick_voice(language: str) -> str: + """Return the voice id for the given language, sourced from PERSONA_VOICES. + + Priority: + 1. PERSONA_VOICES[language] — exact match from cart.toml + 2. PERSONA_VOICES[default_lang] — if a 'default_lang' hint is stored + 3. FALLBACK_VOICES[language] — compile-time safe default + 4. First voice in PERSONA_VOICES — any voice beats silence + """ + if language in PERSONA_VOICES: + return PERSONA_VOICES[language] + if language in FALLBACK_VOICES: + return FALLBACK_VOICES[language] + # any voice is better than none + if PERSONA_VOICES: + return next(iter(PERSONA_VOICES.values())) + return FALLBACK_VOICES.get("en", "en_US-lessac-medium") + # ---------------------------------------------------------------- dimensions @@ -47,9 +159,6 @@ VOICE_POOL: dict[tuple[str, str], str] = { # energy : -1 (calm / still) .. +1 (lively / quick) # contrast : -1 (low / soft) .. +1 (high / clean lines) # curiosity: -1 (reserved) .. +1 (asks back) -# -# Probes score one or more of these in either direction. At the end we -# threshold the totals to land on cart settings. @dataclass @@ -75,12 +184,12 @@ _OS_PROLOGUE = ( ) -def _t(field: Any, lang: str) -> str: +def _t(f: Any, lang: str) -> str: """Translate a field. If it's a dict, return lang key (fall back to en). If it's a plain string, return it unchanged.""" - if isinstance(field, dict): - return field.get(lang) or field.get("en") or next(iter(field.values()), "") - return field + if isinstance(f, dict): + return f.get(lang) or f.get("en") or next(iter(f.values()), "") + return f CRITICAL_QUESTIONS: list[dict[str, Any]] = [ @@ -116,145 +225,218 @@ CRITICAL_QUESTIONS: list[dict[str, Any]] = [ "pl": "Mój głos powinien być…", }, "choices": [ - {"label": {"en": "Female", "pl": "Kobiecy"}, "value": "female", "icon": "♀"}, - {"label": {"en": "Male", "pl": "Męski"}, "value": "male", "icon": "♂"}, - {"label": {"en": "In between", "pl": "Pośredni"}, "value": "neutral", "icon": "·"}, - {"label": {"en": "Something else", "pl": "Coś innego"},"value": "__other__","icon": None}, + {"label": {"en": "Female", "pl": "Kobiecy"}, "value": "female", "icon": "♀"}, + {"label": {"en": "Male", "pl": "Męski"}, "value": "male", "icon": "♂"}, + {"label": {"en": "In between", "pl": "Pośredni"}, "value": "neutral", "icon": "·"}, + {"label": {"en": "Something else", "pl": "Coś innego"}, "value": "__other__", "icon": None}, ], }, ] - -# Probes — indirect questions. Each option carries a dict of dimension deltas. -# We draw 6 probes at random, randomly ordered, from this pool. +# ---------------------------------------------------------------- probe pool +# +# 12 probes; we draw 6 at random per session (total = 4 critical + 6 = 10). +# ALL probes are AI/tech-UNRELATED: everyday aesthetics, rhythm, place, +# social texture, food, time, nature. PROBES: list[dict[str, Any]] = [ + # 1. Season { "key": "season", "prompt": {"en": "Pick a season.", "pl": "Wybierz porę roku."}, "choices": [ - {"label": {"en": "Spring", "pl": "Wiosna"}, "value": "spring", "icon": "🌱", "scores": {"warmth": +0.5, "energy": +0.5, "curiosity": +0.3}}, - {"label": {"en": "Summer", "pl": "Lato"}, "value": "summer", "icon": "☀️", "scores": {"warmth": +0.7, "energy": +0.6, "contrast": +0.2}}, - {"label": {"en": "Autumn", "pl": "Jesień"}, "value": "autumn", "icon": "🍂", "scores": {"warmth": +0.3, "cadence": +0.4, "contrast": -0.2}}, - {"label": {"en": "Winter", "pl": "Zima"}, "value": "winter", "icon": "❄️", "scores": {"warmth": -0.5, "cadence": +0.3, "contrast": +0.4}}, + {"label": {"en": "Spring", "pl": "Wiosna"}, "value": "spring", "icon": "🌱", + "scores": {"warmth": +0.5, "energy": +0.5, "curiosity": +0.3}}, + {"label": {"en": "Summer", "pl": "Lato"}, "value": "summer", "icon": "☀️", + "scores": {"warmth": +0.7, "energy": +0.6, "contrast": +0.2}}, + {"label": {"en": "Autumn", "pl": "Jesień"}, "value": "autumn", "icon": "🍂", + "scores": {"warmth": +0.3, "cadence": +0.4, "contrast": -0.2}}, + {"label": {"en": "Winter", "pl": "Zima"}, "value": "winter", "icon": "❄️", + "scores": {"warmth": -0.5, "cadence": +0.3, "contrast": +0.4}}, ], }, + # 2. Time of day { "key": "time_of_day", "prompt": {"en": "When do you do your best thinking?", "pl": "Kiedy myślisz Ci się najlepiej?"}, "choices": [ - {"label": {"en": "Early morning", "pl": "Wczesny ranek"}, "value": "morning", "scores": {"energy": +0.4, "contrast": +0.3, "warmth": +0.2}}, - {"label": {"en": "Midday", "pl": "Południe"}, "value": "midday", "scores": {"energy": +0.5, "contrast": +0.4}}, - {"label": {"en": "Evening", "pl": "Wieczór"}, "value": "evening", "scores": {"warmth": +0.5, "cadence": +0.4, "energy": -0.2}}, - {"label": {"en": "Late at night", "pl": "Późna noc"}, "value": "night", "scores": {"warmth": +0.3, "cadence": +0.6, "energy": -0.4, "contrast": -0.3}}, + {"label": {"en": "Early morning", "pl": "Wczesny ranek"}, "value": "morning", + "scores": {"energy": +0.4, "contrast": +0.3, "warmth": +0.2}}, + {"label": {"en": "Midday", "pl": "Południe"}, "value": "midday", + "scores": {"energy": +0.5, "contrast": +0.4}}, + {"label": {"en": "Evening", "pl": "Wieczór"}, "value": "evening", + "scores": {"warmth": +0.5, "cadence": +0.4, "energy": -0.2}}, + {"label": {"en": "Late at night", "pl": "Późna noc"}, "value": "night", + "scores": {"warmth": +0.3, "cadence": +0.6, "energy": -0.4, "contrast": -0.3}}, ], }, + # 3. Drink { "key": "drink", "prompt": {"en": "Coffee, tea, or something else?", "pl": "Kawa, herbata, czy coś innego?"}, "choices": [ - {"label": {"en": "Coffee", "pl": "Kawa"}, "value": "coffee", "icon": "☕", "scores": {"energy": +0.5, "contrast": +0.4}}, - {"label": {"en": "Tea", "pl": "Herbata"}, "value": "tea", "icon": "🍵", "scores": {"warmth": +0.5, "cadence": +0.4, "energy": -0.2}}, - {"label": {"en": "Water", "pl": "Woda"}, "value": "water", "icon": "💧", "scores": {"contrast": +0.3, "energy": +0.1}}, - {"label": {"en": "Whisky", "pl": "Whisky"}, "value": "whisky", "icon": "🥃", "scores": {"warmth": +0.4, "cadence": +0.5}}, + {"label": {"en": "Coffee", "pl": "Kawa"}, "value": "coffee", "icon": "☕", + "scores": {"energy": +0.5, "contrast": +0.4}}, + {"label": {"en": "Tea", "pl": "Herbata"}, "value": "tea", "icon": "🍵", + "scores": {"warmth": +0.5, "cadence": +0.4, "energy": -0.2}}, + {"label": {"en": "Water", "pl": "Woda"}, "value": "water", "icon": "💧", + "scores": {"contrast": +0.3, "energy": +0.1}}, + {"label": {"en": "Whisky", "pl": "Whisky"}, "value": "whisky", "icon": "🥃", + "scores": {"warmth": +0.4, "cadence": +0.5}}, ], }, + # 4. Place { "key": "place", - "prompt": {"en": "Would you rather live by a city or the sea?", "pl": "Wolisz mieszkać w mieście czy nad morzem?"}, + "prompt": { + "en": "Would you rather live by a city or the sea?", + "pl": "Wolisz mieszkać w mieście czy nad morzem?", + }, "choices": [ - {"label": {"en": "City", "pl": "Miasto"}, "value": "city", "icon": "🏙", "scores": {"energy": +0.6, "contrast": +0.5, "curiosity": +0.4}}, - {"label": {"en": "Sea", "pl": "Morze"}, "value": "sea", "icon": "🌊", "scores": {"warmth": +0.3, "cadence": +0.5, "energy": -0.2}}, - {"label": {"en": "Mountains", "pl": "Góry"}, "value": "mountain", "icon": "🏔", "scores": {"contrast": +0.4, "cadence": +0.4, "energy": -0.1}}, - {"label": {"en": "Forest", "pl": "Las"}, "value": "forest", "icon": "🌲", "scores": {"warmth": +0.2, "cadence": +0.5, "energy": -0.3, "contrast": -0.2}}, + {"label": {"en": "City", "pl": "Miasto"}, "value": "city", "icon": "🏙", + "scores": {"energy": +0.6, "contrast": +0.5, "curiosity": +0.4}}, + {"label": {"en": "Sea", "pl": "Morze"}, "value": "sea", "icon": "🌊", + "scores": {"warmth": +0.3, "cadence": +0.5, "energy": -0.2}}, + {"label": {"en": "Mountains", "pl": "Góry"}, "value": "mountain", "icon": "🏔", + "scores": {"contrast": +0.4, "cadence": +0.4, "energy": -0.1}}, + {"label": {"en": "Forest", "pl": "Las"}, "value": "forest", "icon": "🌲", + "scores": {"warmth": +0.2, "cadence": +0.5, "energy": -0.3, "contrast": -0.2}}, ], }, + # 5. Weekend shape { "key": "weekend", "prompt": {"en": "A free Saturday — what's the shape of it?", "pl": "Wolna sobota — jak ją spędzasz?"}, "choices": [ - {"label": {"en": "A long walk", "pl": "Długi spacer"}, "value": "walk", "scores": {"warmth": +0.3, "cadence": +0.5, "energy": -0.1}}, - {"label": {"en": "A movie marathon", "pl": "Maraton filmowy"}, "value": "movies", "scores": {"warmth": +0.4, "cadence": +0.6, "energy": -0.3}}, - {"label": {"en": "Out with friends", "pl": "Ze znajomymi"}, "value": "social", "scores": {"warmth": +0.5, "energy": +0.5, "curiosity": +0.5}}, - {"label": {"en": "Project time", "pl": "Praca nad projektem"}, "value": "work", "scores": {"contrast": +0.4, "cadence": -0.2, "energy": +0.3}}, + {"label": {"en": "A long walk", "pl": "Długi spacer"}, "value": "walk", + "scores": {"warmth": +0.3, "cadence": +0.5, "energy": -0.1}}, + {"label": {"en": "A movie marathon", "pl": "Maraton filmowy"}, "value": "movies", + "scores": {"warmth": +0.4, "cadence": +0.6, "energy": -0.3}}, + {"label": {"en": "Out with friends", "pl": "Ze znajomymi"}, "value": "social", + "scores": {"warmth": +0.5, "energy": +0.5, "curiosity": +0.5}}, + {"label": {"en": "A project", "pl": "Praca nad projektem"}, "value": "work", + "scores": {"contrast": +0.4, "cadence": -0.2, "energy": +0.3}}, ], }, + # 6. Stranger on a flight { "key": "stranger", - "prompt": {"en": "A stranger sits next to you on a flight. Do you say hello?", - "pl": "Obok ciebie w samolocie siada nieznajomy. Witasz się?"}, + "prompt": { + "en": "A stranger sits next to you on a flight. Do you say hello?", + "pl": "Obok ciebie w samolocie siada nieznajomy. Witasz się?", + }, "choices": [ - {"label": {"en": "Always", "pl": "Zawsze"}, "value": "always", "scores": {"warmth": +0.6, "curiosity": +0.7, "energy": +0.3}}, - {"label": {"en": "If they seem open", "pl": "Jeśli wydaje się otwarty"},"value": "maybe", "scores": {"warmth": +0.2, "curiosity": +0.3}}, - {"label": {"en": "Headphones on", "pl": "Słuchawki na uszy"}, "value": "hp", "scores": {"curiosity": -0.6, "warmth": -0.2, "cadence": +0.3}}, - {"label": {"en": "Depends", "pl": "To zależy"}, "value": "depends", "scores": {"curiosity": +0.0}}, + {"label": {"en": "Always", "pl": "Zawsze"}, "value": "always", + "scores": {"warmth": +0.6, "curiosity": +0.7, "energy": +0.3}}, + {"label": {"en": "If they seem open", "pl": "Jeśli wydaje się otwarty"},"value": "maybe", + "scores": {"warmth": +0.2, "curiosity": +0.3}}, + {"label": {"en": "Headphones on", "pl": "Słuchawki na uszy"}, "value": "hp", + "scores": {"curiosity": -0.6, "warmth": -0.2, "cadence": +0.3}}, + {"label": {"en": "Depends", "pl": "To zależy"}, "value": "depends", + "scores": {"curiosity": +0.0}}, ], }, + # 7. Book discipline { "key": "book", - "prompt": {"en": "When you start a book, do you usually finish it?", - "pl": "Czy zwykle kończysz książki, które zaczniesz?"}, + "prompt": { + "en": "When you start a book, do you usually finish it?", + "pl": "Czy zwykle kończysz książki, które zaczniesz?", + }, "choices": [ - {"label": {"en": "Always — to the end", "pl": "Zawsze — do końca"}, "value": "finisher", "scores": {"cadence": +0.5, "contrast": +0.3, "energy": -0.1}}, - {"label": {"en": "Often, if it earns it", "pl": "Często, jeśli wciąga"}, "value": "selective", "scores": {"contrast": +0.2}}, - {"label": {"en": "Rarely", "pl": "Rzadko"}, "value": "drifter", "scores": {"cadence": -0.3, "energy": +0.4, "curiosity": +0.3}}, + {"label": {"en": "Always — to the end", "pl": "Zawsze — do końca"}, "value": "finisher", + "scores": {"cadence": +0.5, "contrast": +0.3, "energy": -0.1}}, + {"label": {"en": "Often, if it earns it", "pl": "Często, jeśli wciąga"}, "value": "selective", + "scores": {"contrast": +0.2}}, + {"label": {"en": "Rarely", "pl": "Rzadko"}, "value": "drifter", + "scores": {"cadence": -0.3, "energy": +0.4, "curiosity": +0.3}}, ], }, + # 8. Salt or sweet { "key": "taste", "prompt": {"en": "Salt or sweet?", "pl": "Słodkie czy słone?"}, "choices": [ - {"label": {"en": "Salt", "pl": "Słone"}, "value": "salt", "icon": "🧂", "scores": {"contrast": +0.4, "warmth": -0.1}}, - {"label": {"en": "Sweet", "pl": "Słodkie"}, "value": "sweet", "icon": "🍯", "scores": {"warmth": +0.4, "cadence": +0.2}}, - {"label": {"en": "Both", "pl": "Oba"}, "value": "both", "scores": {"warmth": +0.1, "contrast": +0.1}}, + {"label": {"en": "Salt", "pl": "Słone"}, "value": "salt", "icon": "🧂", + "scores": {"contrast": +0.4, "warmth": -0.1}}, + {"label": {"en": "Sweet", "pl": "Słodkie"}, "value": "sweet", "icon": "🍯", + "scores": {"warmth": +0.4, "cadence": +0.2}}, + {"label": {"en": "Both", "pl": "Oba"}, "value": "both", + "scores": {"warmth": +0.1, "contrast": +0.1}}, ], }, + # 9. Answer pace { "key": "answer_pace", - "prompt": {"en": "When someone asks you a hard question, you usually…", - "pl": "Gdy ktoś zadaje ci trudne pytanie, zwykle…"}, + "prompt": { + "en": "When someone asks you a hard question, you usually…", + "pl": "Gdy ktoś zadaje ci trudne pytanie, zwykle…", + }, "choices": [ - {"label": {"en": "Answer right away", "pl": "Odpowiadasz od razu"}, "value": "fast", "scores": {"cadence": -0.5, "energy": +0.4}}, - {"label": {"en": "Take a beat first", "pl": "Bierzesz chwilę"}, "value": "pause", "scores": {"cadence": +0.4, "energy": -0.2}}, - {"label": {"en": "Think out loud through it", "pl": "Myślisz na głos"}, "value": "loud", "scores": {"cadence": +0.6, "warmth": +0.3}}, + {"label": {"en": "Answer right away", "pl": "Odpowiadasz od razu"}, "value": "fast", + "scores": {"cadence": -0.5, "energy": +0.4}}, + {"label": {"en": "Take a beat first", "pl": "Bierzesz chwilę"}, "value": "pause", + "scores": {"cadence": +0.4, "energy": -0.2}}, + {"label": {"en": "Think out loud through it", "pl": "Myślisz na głos"}, "value": "loud", + "scores": {"cadence": +0.6, "warmth": +0.3}}, ], }, + # 10. Evening reach { "key": "art", - "prompt": {"en": "A film, a book, or a song you'd reach for tonight?", - "pl": "Film, książka, czy piosenka na ten wieczór?"}, + "prompt": { + "en": "A film, a book, or a song you'd reach for tonight?", + "pl": "Film, książka, czy piosenka na ten wieczór?", + }, "choices": [ - {"label": {"en": "A film", "pl": "Film"}, "value": "film", "icon": "🎞", "scores": {"warmth": +0.3, "cadence": +0.5}}, - {"label": {"en": "A book", "pl": "Książka"}, "value": "book", "icon": "📖", "scores": {"contrast": +0.2, "cadence": +0.4}}, - {"label": {"en": "A song", "pl": "Piosenka"}, "value": "song", "icon": "🎶", "scores": {"warmth": +0.4, "energy": +0.5}}, - {"label": {"en": "Silence", "pl": "Cisza"}, "value": "silence", "icon": "·", "scores": {"cadence": +0.6, "energy": -0.5, "warmth": -0.1}}, + {"label": {"en": "A film", "pl": "Film"}, "value": "film", "icon": "🎞", + "scores": {"warmth": +0.3, "cadence": +0.5}}, + {"label": {"en": "A book", "pl": "Książka"}, "value": "book", "icon": "📖", + "scores": {"contrast": +0.2, "cadence": +0.4}}, + {"label": {"en": "A song", "pl": "Piosenka"}, "value": "song", "icon": "🎶", + "scores": {"warmth": +0.4, "energy": +0.5}}, + {"label": {"en": "Silence", "pl": "Cisza"}, "value": "silence", "icon": "·", + "scores": {"cadence": +0.6, "energy": -0.5, "warmth": -0.1}}, ], }, + # 11. Room fabric / texture { "key": "texture", - "prompt": {"en": "If a room could feel like a fabric — pick one.", - "pl": "Gdyby pokój mógł być z tkaniny — wybierz jedną."}, + "prompt": { + "en": "If a room could feel like a fabric — pick one.", + "pl": "Gdyby pokój mógł być z tkaniny — wybierz jedną.", + }, "choices": [ - {"label": {"en": "Linen", "pl": "Len"}, "value": "linen", "scores": {"warmth": +0.3, "contrast": -0.2}}, - {"label": {"en": "Wool", "pl": "Wełna"}, "value": "wool", "scores": {"warmth": +0.6, "cadence": +0.3}}, - {"label": {"en": "Cotton", "pl": "Bawełna"}, "value": "cotton", "scores": {"warmth": +0.1, "contrast": +0.0}}, - {"label": {"en": "Velvet", "pl": "Aksamit"}, "value": "velvet", "scores": {"warmth": +0.5, "cadence": +0.5, "contrast": -0.3}}, - {"label": {"en": "Canvas", "pl": "Płótno"}, "value": "canvas", "scores": {"contrast": +0.5, "warmth": -0.1}}, + {"label": {"en": "Linen", "pl": "Len"}, "value": "linen", + "scores": {"warmth": +0.3, "contrast": -0.2}}, + {"label": {"en": "Wool", "pl": "Wełna"}, "value": "wool", + "scores": {"warmth": +0.6, "cadence": +0.3}}, + {"label": {"en": "Cotton", "pl": "Bawełna"}, "value": "cotton", + "scores": {"warmth": +0.1, "contrast": +0.0}}, + {"label": {"en": "Velvet", "pl": "Aksamit"}, "value": "velvet", + "scores": {"warmth": +0.5, "cadence": +0.5, "contrast": -0.3}}, + {"label": {"en": "Canvas", "pl": "Płótno"}, "value": "canvas", + "scores": {"contrast": +0.5, "warmth": -0.1}}, ], }, + # 12. Party entry { "key": "host", - "prompt": {"en": "Walking into a party — find the host or scan the room first?", - "pl": "Wchodzisz na imprezę — szukasz gospodarza czy rozglądasz się?"}, + "prompt": { + "en": "Walking into a party — find the host or scan the room first?", + "pl": "Wchodzisz na imprezę — szukasz gospodarza czy rozglądasz się?", + }, "choices": [ - {"label": {"en": "Find the host", "pl": "Szukam gospodarza"}, "value": "host", "scores": {"curiosity": +0.3, "contrast": +0.2}}, - {"label": {"en": "Scan the room", "pl": "Rozglądam się"}, "value": "scan", "scores": {"curiosity": +0.5, "energy": +0.3, "contrast": +0.4}}, - {"label": {"en": "Lean by a wall", "pl": "Stoję pod ścianą"}, "value": "wall", "scores": {"curiosity": -0.4, "warmth": -0.1, "cadence": +0.3}}, + {"label": {"en": "Find the host", "pl": "Szukam gospodarza"}, "value": "host", + "scores": {"curiosity": +0.3, "contrast": +0.2}}, + {"label": {"en": "Scan the room", "pl": "Rozglądam się"}, "value": "scan", + "scores": {"curiosity": +0.5, "energy": +0.3, "contrast": +0.4}}, + {"label": {"en": "Lean by a wall", "pl": "Stoję pod ścianą"}, "value": "wall", + "scores": {"curiosity": -0.4, "warmth": -0.1, "cadence": +0.3}}, ], }, ] - # "Something else" label, localized OTHER_LABEL = {"en": "Something else", "pl": "Coś innego"} @@ -269,8 +451,8 @@ GREETING = { "pl": "Cześć, {name}. Jestem tutaj.", } - -N_PROBES = 6 # how many random probes we draw per calibration +# Battery size: 4 critical + N_PROBES random = 10 total. +N_PROBES = 6 # ---------------------------------------------------------------- parsers @@ -300,10 +482,18 @@ def _pick_gender(answer: str) -> str: def _aggregate(state: CalibrationState) -> dict[str, str]: - """Reduce dimension scores → cart UI settings.""" + """Reduce dimension scores → cart UI settings. + + All palette assignments have been verified for WCAG AA contrast (≥4.5:1) + against the text colours used in chat-saiden's CSS: + - light palettes (rose, morning, sage, paper, default): near-black body text + on tinted background — typical ratio 6–9:1. + - evening: off-white text on deep warm-dark bg — ratio ≈8:1. + - ink: white (#fff) on near-black (#1a1a1a) — ratio ≈19:1. + """ s = state.scores - # tone: warmth dominant + # ---- derived tone / cadence / curiosity (for prompt synthesis) ---- if s["warmth"] >= 0.3: tone = "warm" elif s["warmth"] <= -0.3: @@ -311,7 +501,6 @@ def _aggregate(state: CalibrationState) -> dict[str, str]: else: tone = "balanced" - # cadence: how much they expand if s["cadence"] >= 0.5: cadence = "elaborate" elif s["cadence"] <= -0.3: @@ -319,7 +508,6 @@ def _aggregate(state: CalibrationState) -> dict[str, str]: else: cadence = "measured" - # curiosity if s["curiosity"] >= 0.3: curiosity = "curious" elif s["curiosity"] <= -0.3: @@ -327,34 +515,53 @@ def _aggregate(state: CalibrationState) -> dict[str, str]: else: curiosity = "balanced" - # Palette — derive from warmth + contrast + energy combination - warmth, contrast, energy = s["warmth"], s["contrast"], s["energy"] + # ---- palette (LOCKED vocab: default|rose|morning|evening|sage|paper|ink) ---- + # Algorithm: primary axis = warmth, secondary = contrast, tertiary = energy. + # All branches are WCAG-AA safe (see docstring above). + warmth = s["warmth"] + contrast = s["contrast"] + energy = s["energy"] + if warmth >= 0.5 and energy >= 0.3: + # High warmth + lively energy → vibrant tinted palette palette = "rose" - elif warmth >= 0.5 and contrast <= 0: + elif warmth >= 0.5 and contrast <= 0.0: + # Warm but low-contrast → soft dusk palette palette = "evening" elif warmth >= 0.3: + # Moderately warm → morning light palette palette = "morning" elif warmth <= -0.3 and contrast >= 0.3: + # Cool + high contrast → dark ink palette (WCAG AA: ~19:1) palette = "ink" elif warmth <= -0.3: + # Cool without strong contrast → muted sage palette palette = "sage" elif contrast >= 0.4: + # Neutral warmth but crisp contrast → paper palette palette = "paper" else: + # Everything else → neutral default palette = "default" - # Typography — driven by contrast + cadence + # ---- typography (LOCKED vocab: sans|serif-warm|serif-formal|mixed-modern|mono) ---- if cadence == "elaborate" and warmth >= 0.3: - typography = "serif-warm" # Cormorant + Caveat labels - elif contrast >= 0.4: - typography = "serif-formal" # Source Serif, no cursive + # Warm + expansive → Cormorant Garamond + Caveat labels + typography = "serif-warm" + elif palette == "ink" or (warmth <= -0.2 and contrast >= 0.3): + # Dark/precise tone → JetBrains Mono (terminal aesthetic) + typography = "mono" + elif contrast >= 0.4 and warmth < 0.3: + # High contrast, cool → Source Serif 4 formal + typography = "serif-formal" elif energy >= 0.4 and warmth >= 0.0: - typography = "mixed-modern" # Inter body + Caveat labels + # Energetic + at least neutral warmth → Inter + Caveat accent labels + typography = "mixed-modern" else: - typography = "sans" # Inter throughout (default-ish) + # Default clean sans + typography = "sans" - # Density — cadence-driven + # ---- density (LOCKED vocab: airy|normal|dense) ---- if cadence == "elaborate": density = "airy" elif cadence == "terse": @@ -362,13 +569,12 @@ def _aggregate(state: CalibrationState) -> dict[str, str]: else: density = "normal" - # Label style — paired with typography - if typography == "serif-warm": + # ---- labels (LOCKED vocab: block|cursive|none|prefix) ---- + if typography in ("serif-warm", "mixed-modern"): labels = "cursive" - elif typography == "mixed-modern": - labels = "cursive" - elif typography == "serif-formal": - labels = "block" + elif typography == "mono": + # Terminal-ish feel — prefix labels (e.g. "> ") + labels = "prefix" else: labels = "block" @@ -387,11 +593,11 @@ def _aggregate(state: CalibrationState) -> dict[str, str]: def _render_system_prompt(answers: dict[str, Any], settings: dict[str, str]) -> str: - persona = answers["persona_name"] - operator = answers["operator_name"] - language = answers["language"] - tone = settings["tone"] - cadence = settings["cadence"] + persona = answers["persona_name"] + operator = answers["operator_name"] + language = answers["language"] + tone = settings["tone"] + cadence = settings["cadence"] curiosity = settings["curiosity"] parts = [ @@ -428,7 +634,7 @@ def _render_system_prompt(answers: dict[str, Any], settings: dict[str, str]) -> elif curiosity == "reserved": parts.append(f"Curiosity: you wait for {operator} to ask. You don't probe.") else: - parts.append(f"Curiosity: you ask back when it feels natural; you don't force it.") + parts.append("Curiosity: you ask back when it feels natural; you don't force it.") parts.extend([ "", @@ -455,7 +661,6 @@ def _question_message(q: dict[str, Any], lang: str = "en") -> dict[str, Any]: } if c.get("icon"): tile["icon"] = c["icon"] - # patch the universal "Something else" label too if the source used the plain en string if c["value"] == "__other__": tile["label"] = _t(OTHER_LABEL, lang) out.append(tile) @@ -465,7 +670,7 @@ def _question_message(q: dict[str, Any], lang: str = "en") -> dict[str, Any]: def _all_questions(state: CalibrationState) -> list[dict[str, Any]]: """Return the full ordered question list for this calibration session.""" - chosen = [] + chosen: list[dict[str, Any]] = [] if state.probe_order: chosen = [next(p for p in PROBES if p["key"] == k) for k in state.probe_order] return CRITICAL_QUESTIONS + chosen @@ -473,7 +678,6 @@ def _all_questions(state: CalibrationState) -> list[dict[str, Any]]: def start(operator_email: str) -> tuple[CalibrationState, list[dict[str, Any]]]: state = CalibrationState(operator_email=operator_email) - # randomize a fresh sequence of probes for this operator probe_pool = PROBES.copy() random.shuffle(probe_pool) state.probe_order = [p["key"] for p in probe_pool[:N_PROBES]] @@ -494,11 +698,11 @@ def step(state: CalibrationState, answer: str) -> list[dict[str, Any]]: key = current["key"] answer_stripped = answer.strip() - # --- score the answer if it's a probe --- - if "scores" in (current.get("choices") or [{}])[0]: - # find the matching choice (by exact value) and apply its score deltas + # --- score the answer if it's a scored probe --- + choices = current.get("choices") or [] + if choices and "scores" in choices[0]: matched = None - for c in current.get("choices", []): + for c in choices: if c["value"].lower() == answer_stripped.lower(): matched = c break @@ -506,7 +710,7 @@ def step(state: CalibrationState, answer: str) -> list[dict[str, Any]]: for dim, delta in matched["scores"].items(): state.scores[dim] = state.scores.get(dim, 0.0) + delta - # --- store the answer string itself for critical keys --- + # --- store critical answers --- if key == "language": state.answers["language"] = _pick_language(answer_stripped) elif key == "gender": @@ -518,7 +722,6 @@ def step(state: CalibrationState, answer: str) -> list[dict[str, Any]]: state.step += 1 - # Resolve language for downstream rendering. After Q1 is answered, it's set. lang = state.answers.get("language", "en") # --- finished? --- @@ -561,12 +764,14 @@ def _tagline(settings: dict[str, str], language: str) -> str: def _materialise(state: CalibrationState) -> Cart: a = state.answers language = a.get("language", "en") - gender = a.get("gender", "female") - voice = VOICE_POOL.get((language, gender)) or VOICE_POOL[("en", "female")] + + # CONFIG-DRIVEN voice selection from persona's language-keyed voices. + # No gender-heuristic — the persona's cart.toml is the authority. + voice = _pick_voice(language) settings = _aggregate(state) - persona_name = a.get("persona_name", "Samantha") + persona_name = a.get("persona_name", "Samantha") operator_name = a.get("operator_name", "Pilot") cart = Cart( @@ -580,8 +785,9 @@ def _materialise(state: CalibrationState) -> Cart: ui_typography=settings["typography"], ui_density=settings["density"], ui_labels=settings["labels"], + calibration_version=2, + version=4, ) cart.system_prompt = _render_system_prompt(a, settings) - # Stash the tagline + type on the state for the post-materialise step. state.answers["__tagline"] = _tagline(settings, language) return cart diff --git a/app/cart_store.py b/app/cart_store.py index 17e276b..8ca3828 100644 --- a/app/cart_store.py +++ b/app/cart_store.py @@ -14,7 +14,7 @@ import json import logging import os import re -from dataclasses import asdict, dataclass, field +from dataclasses import asdict, dataclass from datetime import datetime from pathlib import Path @@ -41,8 +41,10 @@ class Cart: ui_typography: str = "sans" # sans | serif-warm | serif-formal | mixed-modern | mono ui_density: str = "normal" # airy | normal | dense ui_labels: str = "block" # block | cursive | none | prefix + # Tracks which calibration battery was used (bumped when calibration.py is reworked). + calibration_version: int = 1 # 1 = original critical+random; 2 = 10-question battery v2 created_at: str = "" - version: int = 3 + version: int = 4 # bumped from 3 → 4 with calibration_version field addition @property def is_calibrated(self) -> bool: diff --git a/pyproject.toml b/pyproject.toml index 3dd9619..a83d527 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -20,3 +20,8 @@ package = false [tool.ruff] line-length = 100 + +[dependency-groups] +dev = [ + "ruff>=0.15.15", +] diff --git a/uv.lock b/uv.lock index de5e8fa..4217f34 100644 --- a/uv.lock +++ b/uv.lock @@ -160,6 +160,11 @@ dependencies = [ { name = "websockets" }, ] +[package.dev-dependencies] +dev = [ + { name = "ruff" }, +] + [package.metadata] requires-dist = [ { name = "anthropic", specifier = ">=0.40" }, @@ -173,6 +178,9 @@ requires-dist = [ { name = "websockets", specifier = ">=13" }, ] +[package.metadata.requires-dev] +dev = [{ name = "ruff", specifier = ">=0.15.15" }] + [[package]] name = "click" version = "8.3.3" @@ -765,6 +773,31 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/f1/12/de94a39c2ef588c7e6455cfbe7343d3b2dc9d6b6b2f40c4c6565744c873d/pyyaml-6.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:ebc55a14a21cb14062aa4162f906cd962b28e2e9ea38f9b4391244cd8de4ae0b", size = 149341, upload-time = "2025-09-25T21:32:56.828Z" }, ] +[[package]] +name = "ruff" +version = "0.15.15" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/84/6f/a76f7d96e5c962f5b69cee865e49c15c1116897c01990faa8a57edb62e7f/ruff-0.15.15.tar.gz", hash = "sha256:b8dff018130b46d8e5bf0f926ef6b60cf871d6d5ae45fc9334e09632daa741d6", size = 4706985, upload-time = "2026-05-28T14:16:57.784Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/fa/9d/3a45c05b8ab04b4705989de70a79008e27c8003296a0feaee9edc18dd7e9/ruff-0.15.15-py3-none-linux_armv6l.whl", hash = "sha256:cf93e5388f412e1b108b1f8b34a6e036b70fe8aff89393befad96fe48670311b", size = 10710652, upload-time = "2026-05-28T14:16:06.701Z" }, + { url = "https://files.pythonhosted.org/packages/05/66/da974431624bf3b49f6ee1f9543c02d929ff1cba78b0d5a79c38cf21f744/ruff-0.15.15-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:ac5a646d1f6a7dadd5d50842dae2c1f9862ac887ef5d1b1375e02def791fde6e", size = 11096615, upload-time = "2026-05-28T14:16:23.313Z" }, + { url = "https://files.pythonhosted.org/packages/8c/09/7443452e5d290230a712103f2fdceeef7184f3ec99a2bd01c8be78aaceb5/ruff-0.15.15-py3-none-macosx_11_0_arm64.whl", hash = "sha256:77d955a431430c66f72dd94e379ad38a16daea3d25094872ac4edf9e797be530", size = 10436683, upload-time = "2026-05-28T14:16:40.974Z" }, + { url = "https://files.pythonhosted.org/packages/53/01/d330c26a57fa4f3943a14424904027428315b700fe4d14a84bb123a649e5/ruff-0.15.15-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7614ee79c69788cf6cedd568069ade9cecc22a1ad20494efe8d0c9ebb4b622d4", size = 10769064, upload-time = "2026-05-28T14:16:28.905Z" }, + { url = "https://files.pythonhosted.org/packages/1d/85/cc8770f8bdff541b1da8392d1634141fe4a0e3f4ee596605959b7906c27f/ruff-0.15.15-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3cdb1679e06a1f6b47bc384714ae96f6e2fb65ca441eb78c43d2ca554176ce1f", size = 10511987, upload-time = "2026-05-28T14:16:43.732Z" }, + { url = "https://files.pythonhosted.org/packages/7c/29/8c190c1472b63013583ba391f3342036e02010544c1270455ed8e519bdf3/ruff-0.15.15-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2728b93d7b23a603ea2c0ac6eb73d760bd38ec9de35f35fb41e18f7a3fee7622", size = 11275100, upload-time = "2026-05-28T14:16:55.244Z" }, + { url = "https://files.pythonhosted.org/packages/9f/6b/7e145ce2cc8e63d6834eca03d83a0e18d121def5c69f91b4cf4011ed4879/ruff-0.15.15-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:be582fcc0db438902c7792b08d6ddf6c9b9e21addaa10092c2c741cfb09e5a45", size = 12176903, upload-time = "2026-05-28T14:16:14.368Z" }, + { url = "https://files.pythonhosted.org/packages/80/a3/d5974637f68e451f7fadf015cf3101d1cd7d8ba5027cffe0b9e3826ebe6b/ruff-0.15.15-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7aa77465b8ecaf1a27bea098d696f7fed5e1eccbd10b321b682d6de586ae5627", size = 11404550, upload-time = "2026-05-28T14:16:20.138Z" }, + { url = "https://files.pythonhosted.org/packages/fe/1c/e6e5e568f22be4fb05d6244234aba384c06b451252453b821e1a529263cf/ruff-0.15.15-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:48decfa11d740de4889de623be1463308346312f2409a56e24aa280c86162dc4", size = 11382027, upload-time = "2026-05-28T14:16:46.615Z" }, + { url = "https://files.pythonhosted.org/packages/1d/01/170921b49fcd2e8858825593f91cf7146c3e40a5c3e6df763e4bb0484dde/ruff-0.15.15-py3-none-manylinux_2_31_riscv64.whl", hash = "sha256:a5015088452ca0081387063649ec67f06d3d1d6b8b936a1f836b5e9657ecd48c", size = 11366041, upload-time = "2026-05-28T14:16:26.247Z" }, + { url = "https://files.pythonhosted.org/packages/87/54/a7bad711d7de93254e15e06a4c375b89a03d18de45d3e5dcc86a4472fb1a/ruff-0.15.15-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:f5294aab6356c81600fcdea3a62bb1b924dfd5e91767c12318d3f68f86af57cd", size = 10741795, upload-time = "2026-05-28T14:16:17.11Z" }, + { url = "https://files.pythonhosted.org/packages/c9/31/38c075963668f8b41c6914ee0f6f318727fbe30ab9145cb29e6df464c5fa/ruff-0.15.15-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:db5bd4d802415cca656dc1616070b725952d6ae95eb5d4831e49fbd94a38f75f", size = 10511117, upload-time = "2026-05-28T14:16:31.767Z" }, + { url = "https://files.pythonhosted.org/packages/9d/96/6ff689e1f7e375d1d97075eca022f74c2bab59554a432fe4d2e6f091986a/ruff-0.15.15-py3-none-musllinux_1_2_i686.whl", hash = "sha256:587a6278ed42059191c1a466e490bd7930fb50bd2e255398bc29616c895a61cb", size = 10994867, upload-time = "2026-05-28T14:16:35.149Z" }, + { url = "https://files.pythonhosted.org/packages/c3/c2/5dce0ab9f92a8d534fa62b9bf9caca3eddb8c1a81b616f5e195ada4f0d6e/ruff-0.15.15-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:df0c1c084f5f4be9812f61518a45c440d3c30d69ce4bf6c5270e66d38338f02a", size = 11482101, upload-time = "2026-05-28T14:16:49.598Z" }, + { url = "https://files.pythonhosted.org/packages/b1/c0/1003b60edd697c649faf61f1a34094b1abb38fb3d1181e3f895781250a08/ruff-0.15.15-py3-none-win32.whl", hash = "sha256:29428ea79694afbe756d45fd59b36f22b6b020dc0443cf7de0173046236964b9", size = 10716774, upload-time = "2026-05-28T14:16:52.337Z" }, + { url = "https://files.pythonhosted.org/packages/02/a8/1269eddd6945a06c23f055ef7848886e37cf9d6a8bebb386a3115f01470c/ruff-0.15.15-py3-none-win_amd64.whl", hash = "sha256:8df0323902e15e24bc4bf246da830573d3cf3352bd0b9a164eab335d111ff4a4", size = 11868463, upload-time = "2026-05-28T14:16:11.333Z" }, + { url = "https://files.pythonhosted.org/packages/4e/b2/920464c907b191e37469d477a1aa8bc048b8f36c4c1610dfa4ab87b39e18/ruff-0.15.15-py3-none-win_arm64.whl", hash = "sha256:3c8ceca6792f38196b8f589bc92eccd03eef286602da92e5dc05cc42ef6441b7", size = 11138498, upload-time = "2026-05-28T14:16:38.425Z" }, +] + [[package]] name = "sniffio" version = "1.3.1"