Confirm Q8 account/settings IA and ship the closed-beta gap:
- Extend POST /auth/login with display_name (required for DEMO-YKAVU)
- Entry screen tabs: signup vs already-registered login
- Settings hub with tone, autonomy, sessions, data-flow, logout
- Logout revokes current session and clears local token
Co-authored-by: okuma <o0kuma@users.noreply.github.com>
Add decision-log Q8/Q9 as proposals, account-settings-ia.md for Phase 1
invite-only auth + logout/settings IA, and align PRD/tech-design/roadmap
so implementation waits for Master confirmation.
Co-authored-by: okuma <o0kuma@users.noreply.github.com>
명칭 변경:
- decision-log.md Q6 확정: "분신"(가칭) → "와카뷰 (Ykavu)" — 焚身(분신자살)
동음이의 리스크도 있었고 메신저 브랜드로 부르기 무거웠음. Master가 최종
선택한 이름으로 변경(2026-07-31), 파생 문서(AGENTS.md/CLAUDE.md/PRD 등)·
Flutter 앱 텍스트·web manifest/index.html·AndroidManifest 라벨까지 전부 반영
- ai-service: 본인확인 고정 문구(identity.py)·시스템 프롬프트(generation.py)도
갱신 — 새 이름 기준으로 "본인이야 와카뷰야?" 류 질문을 감지하도록 정규식도
같이 손봄(단순 문자열 치환만으론 어미 형태가 안 맞아서 테스트 추가/조정)
- poc/tone-corpus/의 실험용 프롬프트는 의도적으로 그대로 둠(ai-service README에
이미 명시된 대로 프로덕션과 분리된 실험 도구)
UI/UX:
- mobile/lib/theme/app_theme.dart: 시드 컬러를 인디고/라벤더로 변경, 화면 전체에
깔리는 소프트 그라디언트(라이트: 라벤더→스카이→핑크 파스텔, 다크: 딥 인디고→
네이비→플럼) + 카드/인풋/칩을 반투명 "글래스" 서피스로 전환
- mobile/lib/widgets/gradient_backdrop.dart(신규): MaterialApp.builder에 연결해
모든 화면에 자동으로 그라디언트 배경 적용
- mobile/lib/screens/splash_screen.dart(신규) + main.dart 재구성: 기존엔
session.restore()를 기다리는 동안 아무 것도 안 그려서 흰 화면/텍스트만 뜨는
구간이 있었음 — runApp을 먼저 하고 restore 동안 브랜드 스플래시가 뜨도록 변경
- chat_screen·autonomy_settings_screen·data_flow_screen의 커스텀 패널들도
글래스 스타일로 맞춤
BunsinApp -> YkavuApp (mobile/lib/main.dart, test/widget_test.dart 동기화)
Flutter SDK가 없는 환경이라 flutter analyze/run으로 직접 컴파일 검증은 못했음 —
중괄호/괄호 균형과 기존에 검증된 API 패턴 위주로 신중하게 작성함. go test·
pytest는 전부 통과.
- Flutter: drift + SQLCipher local store for tone samples/KV with
secure-storage passphrase; migrate legacy SharedPreferences
- Core: FCM notifyUser on escalation, admin push-test, push metrics,
DELETE session for multi-device logout
- Docs/roadmap B checkboxes updated; Linux SQLCipher apt notes
Co-authored-by: okuma <o0kuma@users.noreply.github.com>
Flutter weakens the old "single platform = faster dev" argument for
skipping iOS, so tech-design.md §6/§8 now state the reasons that
still hold: v2's OS-layer notification access is Android-only by
Apple's own policy regardless of framework, and the dev environment
is Windows, so an iOS build isn't even possible right now. Flutter
still means no UI rewrite once a Mac is available later.
Reconsidered pure Go (would mean reimplementing and re-verifying the
already-tested AI pipeline) and pure Python (leaves perceived
performance/concurrency headroom on the table for a preemptive
scale bet). Landed on: Go handles auth/messaging/DB, Python keeps
owning generate_draft/escalation_filter/retrieve_style behind an
internal API. backend/ (Python) is now labeled a verified prototype
for the Go rewrite to match, not the final service.
Native wasn't actually required for the v2 OS-layer notification
listener -- Flutter reaches it via platform channels like any other
native Android API, same pattern many production apps already use.
Flutter's faster iteration on the chat UI (already validated in the
click prototype) matters more for v1 than starting native. Updates
tech-design.md §8, roadmap.md's checklist, and AGENTS.md accordingly.
tech-design.md §8 settles the stack (Android/Kotlin, Python/FastAPI,
PostgreSQL, WebSocket relay, Room+SQLCipher) so it stops blocking
item 1 of the build order. roadmap.md's Phase 1 breakdown is now
checkboxes instead of prose, and AGENTS.md adds the rule to check/
update that checklist before and after any Phase 1 app-build task,
rather than tracking progress ad hoc.
blind_eval.py runs PoC #1's blind-eval methodology over N held-out
corpus dialogues automatically (generate_draft.py refactored to
expose draft_reply() so both share the same drafting logic).
retrieve_style.py implements the keyword/recency search from
tech-design.md §2-1 and wires into generate_draft.py as --history,
replacing hand-curated --style files.
Bash access was intermittently restricted for part of this session
(auto-mode safety classifier), so these were initially written and
committed-pending without live execution. Now verified for real:
generate_draft.py's existing behavior still holds after the
draft_reply() refactor, blind_eval.py runs cleanly against val.jsonl,
and retrieve_style.py's original weighted-sum scoring had a real bug
-- recency drowned out keyword overlap for short Korean messages
(particle attachment means "핀란드" and "핀란드는" don't share a
token), so it was effectively returning the most recent messages
regardless of topic. Fixed by ranking on (overlap, recency) instead
of a weighted sum, confirmed the Finland-related exemplar now ranks
first for a matching query.
escalation_filter.py implements tech-design.md §3's first step as an
actual hard gate, not just a system-prompt instruction: money,
appointment-confirmation, and emotional content stop generate_draft.py
before it ever calls Gemini. Self-test 10/10; measured a 0.93% trigger
rate against 82,305 real corpus utterances (mostly factual price
mentions, not personal money requests -- noted as an upper bound, not
a real-usage estimate).
v1 doesn't train a custom model: it retrieves the closest-matching
past messages from the person's own history and feeds them as
few-shot exemplars to the same prompt contract generate_draft.py
already implements, via the hosted Gemini call. Narrows the AI-Hub
base corpus's role to evaluation and future on-device distillation,
since a hosted LLM already covers general Korean fluency.
Resolves the open Q1-Q7 questions as tentative decisions (self-app beta
first, target consumers, MVP scenario = read-receipt relief + group-chat
catch-up, autonomy capped at L0-L2) and builds the standard deliverable
set on top of them, ready for review at the next meeting.
Cursor Agent
Claude