- 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.
- 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
- 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
- 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
- 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
- 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
