New feature: after generating any clinical note, the app automatically
suggests relevant billing codes displayed as clickable chips below the output.
Backend (src/routes/billing.js):
- POST /api/suggest-codes endpoint analyzes note text
- Extracts diagnoses from Assessment section via regex
- Looks up ICD-10 codes: local common pediatric map (40+ conditions)
first, then NLM Clinical Tables API for unknown terms
- Suggests CPT E/M codes based on note type, visit complexity,
ROS/PE system counts, and MDM level estimation
- Supports: outpatient (new/established), well visit (age-based),
ED, inpatient (admit/subsequent/discharge)
Frontend (public/js/app.js):
- suggestBillingCodes() renders collapsible card with ICD-10 and CPT chips
- Click any chip to copy the code to clipboard
- Shows E/M level assessment (diagnosis count, ROS, PE, MDM complexity)
- Disclaimer: "Suggestions only. Always verify codes."
Integration: called after note generation in all 6 tabs
(encounter, SOAP, sick visit, well visit, hospital course, chart review)
- Fix: DELETE all other sessions query used empty string fallback when
req.sessionId was undefined, causing id != '' to match ALL rows
(including current session). Now skips deletion if sessionId unknown.
- Fix: Revoke All endpoint returns error if current session not identified
- Fix: var confirm shadowing window.confirm in password change handler
Security:
- Add session management: users can view/revoke active sessions in Settings
- Add password change in Settings (requires current password, HIBP check)
- Force logout all sessions on password reset
- Fix logout to destroy server-side session (was only clearing cookie)
- Add trust proxy for correct client IP in rate limiting and audit logs
- Add CORS support for multiple domains (CORS_ORIGINS env var)
- Add HIBP breach check endpoint and inline warnings on password fields
Audit logging:
- Add audit logging to all 24 PHI-handling endpoints across 13 route files
- Covers: generation, transcription, TTS, refine, encounters, documents, Nextcloud
- All fire-and-forget (no response delay)
AI improvements:
- Refine now includes original source material (transcript, notes, labs)
so AI can reference the full input when modifying output
- Add correction tracking (trackAIOutput) to sick visit and well visit tabs
- Fix sickvisit missing from encounter save noteIdMap
UI fixes:
- Non-blocking busy bar for transcription and AI generation (replaces full-screen overlay)
- Fix encounter recording: hide record button during recording (was showing two stop buttons)
- Fix ROS/PE "All WNL" stacking duplicate event handlers; add Clear buttons
- Enlarge AI instructions textarea in Learning Hub CMS
Domain:
- Primary domain now app.pedshub.com, with scribe.pedshub.com and peds.danvics.com as CORS origins
- Add Cloudflare Turnstile to login, register, and password reset forms
- Switch AI provider to LiteLLM, transcription to OpenAI Whisper
- Change domain to scribe.pedshub.com
- Fix PPTX export: add tables, bold/italic, numbered lists, code blocks, blockquotes
- Fix announcement banner close button (CSP was blocking inline onclick)
- Fix auth middleware: empty Bearer token now falls through to cookie auth
- Fix audio backups: only save on transcription failure, stop auto-deleting on success
- Soften AI correction injection to prevent model hallucination from correction history
- Fix LiteLLM TTS model name handling (no incorrect openai/ prefix)
- Expand AI instructions textarea in Learning Hub CMS
- Update README for v6 with all features and providers
- Add comprehensive docs/: architecture, API reference, database schema,
authentication, AI providers, speech, learning hub, configuration, deployment
- Fix model search for all providers: Bedrock now falls back to built-in
list (with live ListFoundationModels attempt), Azure returns built-in list
- Add Test button on every model row (built-in, discovered, custom) that
sends a live prompt and shows response + latency in a toast
- Add TTS management section: search voices from provider API (Google TTS
voices.list, LiteLLM /v1/models, ElevenLabs /v1/voices), Set as Default
writes tts.voice/tts.model to DB, runtime respects DB override
- Add STT management section: search models from provider (Gemini, Whisper,
LiteLLM, OpenAI, local), Set as Default writes stt.model to DB, runtime
respects DB override in transcribe.js
- Add Embedding models section: search from provider (LiteLLM, Vertex,
OpenAI), Set as Default writes embeddings.model+dimensions to DB,
embeddings.js respects DB override
- Add record-and-transcribe STT test (browser MediaRecorder)
- Add TTS synthesize-and-play test (returns base64 audio)
- Add embedding generate test (shows dims + vector sample)
- Expand PUT /config/:key(*) whitelist to include tts., stt., embeddings.
- Add @aws-sdk/client-bedrock as optional dependency for live Bedrock discovery
NEW FEATURES:
- Bulk Import button in Admin Panel → Developmental Milestones section
- "Import Default Milestones Data" button appears when database is empty
- "Re-import All" button to clear and re-import all static data
- Visible notice when no milestones exist with one-click import
IMPROVEMENTS:
- Auto-shows empty state notice when database has no milestones
- Backend bulk-import endpoint now supports clearExisting parameter
- Imports ALL age groups from static data (birth to 11 years)
- Better UX - admin doesn't need CLI to populate milestone data
FIXES:
- Makes milestone admin editing feature discoverable and usable
- No need to manually run import script anymore
FIXES:
- Milestones now show correctly on encounter page (use static fallback if DB empty)
- Static data preserved as MILESTONES_DATA_STATIC for compatibility
- Database-driven milestones still work (admin can edit via CMS)
NEW FEATURES:
- OpenID Connect (OIDC) authentication support (PocketID, Keycloak, Azure AD, etc.)
- Comprehensive setup guide: OPENID_SETUP.md
- Auto-linking existing users by email on SSO login
- Multiple PDF upload support in Learning Hub (up to 10 files)
- 100 MB per file limit (was 20 MB)
- Full PDF content used for AI generation
- Embeddings use first ~8K chars for semantic search
IMPROVEMENTS:
- Updated UI to show multiple file selection with list
- Drag-and-drop supports multiple files
- Better file upload validation and error handling
- Added clarifying comments about embedding truncation
Features:
- Admin can add, edit, and delete developmental milestones via dashboard
- Milestones stored in PostgreSQL (developmental_milestones table)
- Client-side loads milestones from API instead of static file
- Import script to migrate existing static data to database
- Organized by age group and domain
- Supports sorting and filtering
Admin UI:
- New section in Admin panel for milestone management
- Filter by age group
- Add/Edit modal with validation
- Delete with confirmation
- Auto-complete for age groups and domains
API Endpoints:
- GET /api/milestones-data - Public endpoint for authenticated users
- GET /api/admin/milestones - List all milestones (admin only)
- GET /api/admin/milestones/meta - Get age groups and domains
- POST /api/admin/milestones - Create milestone
- PUT /api/admin/milestones/:id - Update milestone
- DELETE /api/admin/milestones/:id - Delete milestone
- POST /api/admin/milestones/bulk-import - Bulk import
Usage:
1. Run import script: node scripts/import-milestones.js
2. Access Admin dashboard → Developmental Milestones section
3. Add/Edit/Delete milestones as needed
Emails: white card, clean typography, dark button, no gradients.
Same minimal aesthetic as Linear/Resend/Notion emails.
Verify page responses also updated to match.
LiteLLM /audio/transcriptions gives 'Unmapped provider' for Vertex AI Chirp.
The correct approach: use /v1/chat/completions with a Gemini model and send
audio as base64 input_audio content block — Gemini natively understands audio.
Set LITELLM_STT_MODEL to your Gemini model name (e.g. gemini-2.5-flash).
- Bug 1: When user selected "Outpatient" review type but had any subspecialty
visit cards filled in, the backend ignored the top-level type and switched to
the subspecialty prompt. Fixed: top-level type dropdown is now definitive.
Per-visit note types only control data formatting/labeling, not prompt selection.
- Bug 2: Labs entered in a visit card were silently dropped for outpatient and
subspecialty visits (only ED visit labs were included). Fixed: per-visit labs
now appear immediately after their visit content, labeled with the visit date.
- Improved lab labeling: visit labs are labeled "Labs from this visit (date)"
and the separate labs section is labeled "ADDITIONAL LABS (not tied to a
specific visit)" so the AI clearly distinguishes them.
- TTS response now includes X-TTS-Provider header (google-tts, litellm/model, elevenlabs)
- Frontend reads header and shows actual provider in toast instead of hardcoded "Adam/ElevenLabs"
- CORS exposes X-TTS-Provider header so frontend can access it
- Updated .env.example: clarify that LITELLM_TTS_MODEL and LITELLM_STT_MODEL
can be either the model_name alias OR the full provider/model path depending
on your LiteLLM config (important for BAA compliance routing)
vertex_ai/chirp does not work via LiteLLM's audio transcription proxy.
Changed default LITELLM_STT_MODEL from vertex_ai/chirp to whisper-1.
Updated .env.example documentation to match.
STT: Vertex AI Chirp not supported via LiteLLM proxy (confirmed by docs).
Now uses Gemini directly (transcribeGoogle.js) — auto-detected when
GOOGLE_VERTEX_PROJECT is set, fallback to AWS then OpenAI.
TTS: LiteLLM Vertex TTS DOES work but requires the model_list ALIAS
(tts-1) not the underlying path (vertex_ai/text-to-speech).
Also pass voice param — LiteLLM supports Google Cloud voice names.
Auto-detected when LITELLM_API_BASE is set.
LiteLLM's atranscription has a routing bug with Vertex AI Chirp proxy.
AWS Transcribe is already configured and working. Auto-detect now prefers
AWS over LiteLLM. Use TRANSCRIBE_PROVIDER=litellm to force LiteLLM.
- TTS: switch to axios, drop voice param (configured in LiteLLM per model)
- STT: log full LiteLLM error body so 500s are diagnosable in logs
- TTS: same error detail logging
- Fix 'ElevenLabs unavailable' toast to generic 'TTS unavailable'
- Add red Stop button to encounter recording UI
- TTS: switch from OpenAI SDK to axios (same fix as STT), drop voice
param since it's configured inside LiteLLM per model
- Fix 'ElevenLabs unavailable' toast shown even when provider is LiteLLM
- Add dedicated red Stop button to encounter recording UI
Vertex AI Chirp via LiteLLM rejects/hangs when 'prompt' and
'response_format' are included — these are OpenAI Whisper-only params.
Send only file + model for LiteLLM/Chirp.
Having LITELLM_API_BASE for AI text was auto-routing audio transcription
through LiteLLM even when the proxy has no Whisper model configured,
causing silent hangs. Now LiteLLM STT only activates when LITELLM_STT_MODEL
is explicitly set. Falls back correctly to AWS Transcribe when configured.
OpenAI SDK's audio.transcriptions.create() hangs with LiteLLM
(no timeout, SDK-level incompatibility with multipart handling).
Use axios + form-data directly with 120s timeout — same approach
as ElevenLabs TTS. Handles both {text:"..."} and plain string responses.
- LITELLM_MODELS = [] — no hardcoded models, global selector now only
shows what admin has actually added via Search API
- getAvailableModelsWithOverrides: for LiteLLM returns only custom list
- Remove toggle safety check — admin can disable any/all models freely
- Admin panel always reloads on tab open (was cached, showing stale data)
- Add 'Clear all models' button for LiteLLM to wipe and start fresh
- Add POST /config/models/clear-all endpoint
- TRANSCRIBE_PROVIDER=litellm routes audio to LiteLLM /audio/transcriptions
- TTS_PROVIDER=litellm routes to LiteLLM /audio/speech
- Both auto-detect when LITELLM_API_BASE is set (no extra config needed)
- LITELLM_STT_MODEL (default: whisper-1), LITELLM_TTS_MODEL (default: tts-1)
- LITELLM_TTS_VOICE (default: alloy) — alloy/echo/fable/onyx/nova/shimmer
- ElevenLabs still works if ELEVENLABS_API_KEY is set and TTS_PROVIDER=elevenlabs
- Health endpoint now reports tts provider
- Root cause: PUT /config/:key(*) wildcard was registered before
/config/models/toggle and /config/models/default, intercepting them
and returning "value is required" (body had modelId not value)
- Fix: move all model-specific PUT routes before the wildcard
- LiteLLM: return empty built-in list with discovery hint (hardcoded
models don't match user's proxy — must use Search API)
- After adding a discovered model: auto-select it in the default dropdown
- GET /config/models now returns defaultModel so dropdown pre-selects it
- Add Vertex AI provider (Gemini models via @google-cloud/vertexai SDK)
- Add LiteLLM proxy support (OpenAI-compatible, routes to any provider)
- Admin panel: model search/discover from provider API, enable/disable, custom models, set default
- New endpoints: /config/models/discover, /config/models/add-discovered, /config/models/default
- Updated models.js with VERTEX_MODELS and LITELLM_MODELS lists
- Updated health endpoint with vertex + litellm status
Audio Backups:
- New audio_backups table in PostgreSQL (bytea, gzip compressed)
- POST /api/audio-backups — upload with gzip compression (level 6)
- GET /api/audio-backups — list user's backups
- GET /api/audio-backups/:id/audio — download decompressed audio
- DELETE /api/audio-backups/:id — delete backup
- Auto-cleanup every hour (24h expiry)
- Frontend saves to server first, falls back to IndexedDB
- Settings shows source badge (server/local) per backup
AI Corrections:
- Corrections list is now expandable — click to view original vs corrected
- Shows red "Original" and green "Corrected to" sections
- Click arrow to expand/collapse each correction
- Date shown on each correction
- Add GET /api/transcribe/status endpoint — returns whether any server
transcription provider (Whisper/AWS/Local) is configured
- Frontend checks status on login via checkTranscribeStatus()
- When no provider configured: recording stops instantly, keeps live
Web Speech API text, shows friendly toast — no error, no upload wait
- Works in encounter, dictation, and SOAP tabs
- App now works fully out-of-the-box with just an AI provider key
Keep 8KB CHUNK_SIZE (proven stable) but replace 10ms setTimeout delay
with a microtask break every 16 chunks. This avoids the AWS SDK
"Deserialization error: inspect {error}.\$response" while still
eliminating the ~1.25s/MB artificial delay from the old 10ms sleep.
- AWS Transcribe: remove 10ms delay between chunks (was adding ~1.25s/MB),
increase chunk size from 8KB to 32KB (AWS max per frame)
- Add detailed timing logs (ffmpeg, streaming, total) for diagnostics
- OpenAI Whisper: use response_format='text' for faster response parsing
- Frontend: show transcription time in toast, request 16kHz sample rate,
increase bitrate to 32kbps Opus (better quality, still small files)
- Return duration in API response for all providers
- APK: Add WAKE_LOCK, BOOT_COMPLETED, ACCESS_NETWORK_STATE permissions
- APK: Disable allowBackup for medical data security
- APK: AudioRecordingService now acquires wake lock, has stop action in notification
- Serve /.well-known/assetlinks.json for TWA domain verification
- Service worker: cache app shell, stale-while-revalidate for assets, network-first for API
- Admin model management: validate model ID format, prevent built-in conflicts, audit toggle actions, prevent disabling all models
- Bump version to v9.0.0, Docker tag to v9
- Add local Whisper (whisper.cpp / faster-whisper) as transcription provider
Set TRANSCRIBE_PROVIDER=local with configurable model size and binary path
- Upgrade all refine/instruction inputs to resizable textareas across
encounter, dictation, hospital course, chart review, well visit, sick visit
- Make AI memory injection flexible: physician preferences and corrections
are now actively applied (not just "formatting reference"), while still
overridable by current prompt instructions
- OIDC callback now passes only ?sso=ok flag, token stays in
httpOnly cookie (prevents token leaking to logs/referrer/history)
- Frontend auth.js uses cookie-based auth for SSO flow
- Add [PHYSICIAN TEMPLATES] boundary markers around physicianMemories
in all 5 generation routes to mitigate prompt injection
- Consistent boundary format across wellVisit, sickVisit, hpi, soap,
hospitalCourse
OIDC/SSO:
- New /api/auth/oidc route with PKCE for secure authorization
- Supports Azure AD, Okta, Keycloak, PocketID, Google, any OIDC provider
- Admin configurable: issuer, client ID/secret, button label
- Option to disable local auth (force SSO only)
- Auto-creates users on first SSO login, links existing by email
- SSO button on login page, hidden until admin enables OIDC
Firefox:
- Show info toast on first recording that live preview requires
Chrome/Edge; server-side transcription still works in all browsers
AWS Transcribe rejects audio event frames over ~16KB with a
cryptic "Deserialization error" / "Your stream is too big" message
hidden inside the SDK error object. Reducing to 8KB per chunk
fixes both Standard and Medical Transcribe streaming.
When Medical Transcribe fails (wrong IAM permissions, region not
supported), automatically falls back to Standard Transcribe instead
of returning an error. Logs the specific failure reason.
- Add try-catch to /nextcloud/disconnect route (was crashing on DB errors)
- Update docker-compose.yml image tag from v7 to v8
- Remove unused SESSION_SECRET from .env.example
Previously only well-visit and sick-visit used saved physician
templates. Now HPI encounter, HPI dictation, SOAP, and hospital
course all fetch getUserMemoryContext() and pass physicianMemories
to the backend so the AI learns from saved templates/preferences.
- transcribeAWS.js: convert browser WebM/Opus → PCM 16kHz mono via
ffmpeg before sending to AWS Transcribe — PCM is unambiguous and
most reliable; gracefully falls back to ogg-opus if ffmpeg absent
- Dockerfile: install ffmpeg (apk add ffmpeg) so Docker image works
out of the box with AWS Transcribe
- README: document Amazon Transcribe setup, ffmpeg requirement,
Transcribe Medical specialty options, and env vars reference
- New src/utils/transcribeAWS.js: streams audio directly to AWS
Transcribe without requiring an S3 bucket
- Supports AWS_TRANSCRIBE_MEDICAL=true for Transcribe Medical
(better clinical accuracy: drug names, diagnoses, procedures)
- AWS_TRANSCRIBE_SPECIALTY configures specialty (default PRIMARYCARE)
- transcribe.js auto-selects AWS when AWS_BEDROCK_REGION is set,
or can be forced with TRANSCRIBE_PROVIDER=aws|openai
- Falls back to OpenAI Whisper when AWS is not configured
- Add @aws-sdk/client-transcribe-streaming as optional dependency
- Update .env.example with transcription configuration docs
