- Speechmatics: move config build after super().__init__ and settings
delta so turn_detection_mode (e.g. ADAPTIVE) takes effect
- Google STT: fix example passing bare Language enum instead of list
- Google TTS: add missing explicit defaults for all custom settings fields
- Soniox: fix accidental tuple wrapping of STT service in example
- Speechmatics examples: fix system->user role in kick-off messages
- Deepgram Flux: move tag from settings to __init__ (billing metadata)
- ElevenLabs STT: default tag_audio_events to None (use API default)
- Fal STT: simplify language default handling
- Google TTS: rename GoogleStreamTTSSettings to GoogleTTSSettings
Use "AI service" language instead of listing specific types, add
ServiceSettings as a fallback for direct AIService subclasses, and
clarify delta mode description with a concrete frame example.
The audio fields (sample rates, sample sizes, channel counts) on the deprecated `Params` class had no non-deprecated equivalent. This adds an `AudioConfig` class and `audio_config` init arg so users can specify audio configuration without relying on the deprecated `params` parameter.
Move `session_properties` into `GrokRealtimeLLMSettings`, making `settings` the canonical way to configure Grok Realtime — matching the pattern used across the rest of the codebase. The `session_properties` init arg is now deprecated in favor of `settings=GrokRealtimeLLMSettings(session_properties=...)`.
`system_instruction` is synced bidirectionally between the top-level settings field and `session_properties.instructions`, with top-level taking precedence on conflict. (Unlike OpenAI Realtime, Grok's `SessionProperties` has no `model` field, so no model sync is needed.)
Replace the monolithic rtvi.py with a proper package split by concern
protocol version:
- models_v0.py: deprecated pre-1.0 Pydantic models
- models_v1.py: current RTVI protocol v1 message models
- frames.py: RTVI pipeline frame dataclasses
- observer.py: RTVIObserver and RTVIObserverParams
- processor.py: RTVIProcessor (now lean, imports from submodules)
- __init__.py: re-exports full public API for backward compatability
Move `session_properties` into `OpenAIRealtimeLLMSettings`, making `settings` the canonical way to configure OpenAI Realtime — matching the pattern used across the rest of the codebase. The `session_properties` init arg is now deprecated in favor of `settings=OpenAIRealtimeLLMSettings(session_properties=...)`.
`model` and `system_instruction` are synced bidirectionally between the top-level settings fields and `session_properties.model`/`.instructions`, with top-level taking precedence on conflict.
Add `system_instruction=None` to `default_settings` for OpenAIRealtimeLLMService, GrokRealtimeLLMService, UltravoxRealtimeLLMService, AWSNovaSonicLLMService (Azure inherits from OpenAI), and OpenAIRealtimeBetaLLMService (Azure Beta inherits from OpenAI Beta).
Deprecate `system_instruction` init arg in AWSNovaSonicLLMService in favor of `settings=AWSNovaSonicLLMSettings(system_instruction=...)`. Use `self._settings.system_instruction` directly instead of storing a separate `self._system_instruction`.
Deprecation of `params` and `session_properties` in favor of `settings` for realtime services will be tackled in future work.
Add `system_instruction` field to `LLMSettings` so it is runtime-updatable via settings.
For Google (GoogleLLMService, GoogleVertexLLMService), deprecate the init-time arg since it was already shipped. For Anthropic, AWS Bedrock, and OpenAI, remove the init-time arg entirely since it was never shipped.
Still need to handle realtime services (OpenAI Realtime, Grok Realtime, Gemini Live).
Broaden the "Dynamic Settings Updates" section into "Service Settings"
covering the complete settings pattern: defining a Settings subclass,
wiring it into __init__ with defaults + apply_update, and distinguishing
init-only config from runtime-updatable fields.
- Add dedicated Settings subclasses to 20 LLM services that were
borrowing parent Settings classes (e.g. AzureLLMSettings,
GroqLLMSettings) so users don't need cross-module imports
- Fix field defaults to NOT_GIVEN in BaseWhisperSTTSettings,
OpenAIRealtimeSTTSettings, and NvidiaSegmentedSTTSettings for
delta-mode safety
- Fix incomplete default_settings in AWS, Cartesia, ElevenLabs,
Fish, and Whisper services so validate_complete() passes
- Add auto-discovered tests that verify all Settings classes default
to NOT_GIVEN (delta safety) and all services initialize with
complete settings (store completeness)
Move output_container, output_encoding, output_sample_rate out of
CartesiaTTSSettings into plain instance attributes since they cannot
change at runtime without breaking the audio pipeline. Remove deprecated
speed/emotion fields and their dead references in _build_msg() and
run_tts(). Remove the from_mapping override that only existed to
destructure those now-removed output format fields.
Update all ~192 call sites across 84 service files to pass class references
(e.g. `CartesiaTTSSettings`) instead of string names (`"CartesiaTTSSettings"`)
to `_warn_deprecated_param()`. This enables better IDE refactoring support.
Also fix `from_mapping` return type annotations in 5 settings subclasses to
use `typing.Self` instead of forward reference strings.
ServiceSettings types were introduced for runtime updates via ServiceUpdateSettingsFrame, but there was tension between init-time and runtime APIs: overlapping-but-different InputParams vs ServiceSettings classes, and runtime-updatable fields like `model` and `voice` scattered as direct init args rather than living in a settings object. This unifies them so developers use the same settings type at both init and runtime, improving ergonomics and consistency.
Every concrete AIService subclass (LLM, TTS, STT, ImageGen, Vision, Video) now accepts a `settings` parameter for runtime-updatable config. Old init args (`model`, `voice_id`, `params`/`InputParams`) still work but emit DeprecationWarnings pointing to the new API. When both are provided, `settings` takes precedence. Leaf classes emit warnings; base classes do not, avoiding double warnings in inheritance chains.
