- /flow renders the dialog engine's current step as a mock screen (consent,
age, onboarding and scales with progress, mood 0–10, free text, dose
reminder, crisis with hotlines and breathing, safety plan), so every
engine scenario gets the design without duplicating its logic
- today / meds / doctor / profile / messages tabs; navy sidebar and
emergency rail on desktop, emergency block and tab bar on phones
- API: GET /me/{token}/today (today's doses, week marks, next visit, demo
clock time); demo ЕМИАС sign-in seeds the persona's synthetic profile and
prescription from the dashboard fixtures
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
A second channel to the same dialog engine as the Telegram bot: consent,
onboarding, scales and check-ins come from app/dialog; the bot is unchanged.
- API: /auth/emias (doctor's one-time connect code via EmiasMock),
/auth/emias/demo (synthetic personas), /auth/anonymous (random token,
nothing stored in the identity DB), /crisis/resources from crisis.yaml
- web/: React + TS + Vite, mobile-first, safe areas, hash routing,
tokens and texts isolated for a Capacitor mobile build
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- app/scheduler/demo.py: run_until(now) replays due and fresh events in time order: dose rows +
med_reminder, missed after 2 h without an answer → monitoring, daily_checkin, scale_due by the
config/modules.yaml schedules, daily monitoring pass (silence, missed doses) → reach_out/scale_due
- idempotent via scheduler_events (unique token+key); stale events are not sent; no contact without
consent or during an open crisis
- config/scheduler.yaml: times and windows; runs while the questionnaire release is off
- POST /demo/clock/advance replays the scheduler up to the new time
Refs #13
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- app/services/snapshot.py: PatientSnapshot from the clinical DB (field mapping, age, therapy day,
recent C-SSRS risk, weapon access from dialog facts)
- app/services/monitoring.py: RuleMonitoring registered via register_monitoring; persists alert/crisis
actions, crisis_acute audit, enhanced_monitoring flag, cached status_color, notifies the doctor (and
the doctor on duty for crises) after commit; a running crisis is not restarted
- demo clock offset persisted in clock_state, restored on scheduler start
- tests: Andrey's 13 days through the service → G G G Y Y G G G G Y Y Y R
Refs #38
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
- No same-day C-SSRS repeat: a risk screen completed within cssrs_cooldown_hours is not queued again
after PHQ-9 item 9 >= 1 (scale crisis path, rule schedule_scale, scale_due); crisis script and alerts stay.
- Scale intro registry: register_scale_intro(scale_id, text_or_fn); start_scale(intro=None) uses it.
veteran_daily migrated from per-scale on_enter hooks.
- Prefix triggers "button:<prefix>:*" with trigger_payload(event); medication buttons carry the dose
(med:taken:<dose_id>, ...), med_pending dropped; payload-less legacy buttons answer as stale.
- Abandoned-step timeout: settings.abandon_after_hours (default 6 h) returns abandonable states
(daily.*, meds.*, scale.* not in onboarding) to idle before the next event; never in crisis or with intake on.
Refs #56
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Start screening of the veteran module: peer-tone intro, trauma exposure gate for
PC-PTSD-5, PCL-5/PHQ-9/AUDIT-C via scale sessions (sex asked if unknown), weapon
access question stored as facts for lane B with a safe-storage block on risk,
plain-language result, modules enabled in profile, FAQ, resume after a crisis.
Refs #36
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Deep-link /start <code> binds the chat via IdentityProvider, text and
button presses go to get_engine().handle(), replies render as inline
keyboards and are sent verbatim (no parse_mode). TelegramOutbox delivers
scheduler pushes to bound chats and falls back to the previous outbox.
No-op without TG_BOT_TOKEN; logs carry no text or chat ids.
Refs #11
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01DfbiLXFJswz2EK3qtWF7S7
build_structured() aggregates a PatientCard into scores, flags and
adherence (no patient text, no names); build_summary() sends it through
the LLM gateway, falls back to a config-driven template, keeps an open
acute alert first and caches per (token, provider, data hash).
Refs #19
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Topic from engine or keyword classifier, section via integrations.drug_info,
sentence retrieval by keyword overlap (dosing sentences dropped), LLM only
rephrases the excerpt through gateway.phrase("med_answer") with forbidden-output
and added-content guards; dose questions and missing answers -> None + fallback text.
Refs #15
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Freeze interfaces between lanes A (bot), B (backend), C (dashboard) so three developers work in
parallel without touching each other's files: dialog Event/Reply + engine registry with echo stub,
integration protocols with in-memory defaults, MonitoringService with noop stub, /api/v1 schemas
with fixture-backed routes, frozen main.py wiring, config/modules.yaml + due_scales(), DAR-5,
tzdata, Andrey trajectory, lanes in WORKFLOW, ADR-010.
Refs #34
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Single entry point app/llm/gateway.py: extract_item, extract_checkin,
risk_classify, phrase, summarize_for_doctor. Two-level design:
LLMProvider (transport, GigaChat) and LLMTasks (PromptedTasks over a
provider, or rule-based MockTasks). Shared policy in the gateway:
assert_scrubbed backstop, confidence threshold 0.5, risk failure -> NONE,
forbidden-output filter with config/texts/phrases.yaml fallbacks.
Refs #7
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Rule-based PII scrubber: phones, e-mails, SNILS (checksum-aware), passport,
INN, cards, dates of birth, addresses, URLs/handles and person names
(dictionary in config/privacy/names_ru.yaml + declension, patronymic and
surname heuristics). Idempotent via fixed-point iteration; false-positive
guards for ordinary clinical text. pseudo_id normalises SNILS to 11 digits
and returns HMAC-SHA256 truncated to 32 hex chars.
Refs #2
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Two DeclarativeBases on two engines (ADR-003): identity holds direct
identifiers, clinical holds token-keyed pseudonymised data plus audit_log.
Portable types (JSONB variant, tz-aware UTC timestamps rejecting naive
values) so tests run on SQLite. init_db() runs create_all at startup.
Guardrail #5 checked by AST and import-graph tests.
Refs #6
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Pydantic schema for config/scales/*.yaml, cached loader, score() with
severity bands (sex-specific for AUDIT-C), rule-based C-SSRS triage,
flags (PHQ-9 item 9, PCL-5 >= 33, PHQ-4 subscales) and delta().
Starting literature thresholds for phq9, gad7, pcl5, auditc, pcptsd5,
cssrs_screen, phq4; final values are approved by the psychiatrist (#8).
Refs #3
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
One Postgres with isolated identity/clinical databases and roles (ADR-003),
FastAPI /health, Streamlit placeholder, typed settings with offline defaults.
Refs #1
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Arxip222andClaude Opus 5.5
ElebobaandClaude Opus 5.5