- indicate clearly that it's not meant for public use
- make it clear the `self._settings` is the single source of truth for model information
- set the stage for an upcoming change where `AIService` subclasses won't have to ever worry about explicitly calling an `AIService` method to sync model name to metrics
Across all services, switch from accessing `self._model_name` or `self.model_name` in favor of `self._settings.model`.
- AWSNovaSonicLLMService: new `AWSNovaSonicLLMSettings` with `voice_id` and `endpointing_sensitivity`; remove `self._params` entirely, storing audio I/O config as plain instance variables
- NeuphonicHttpTTSService: reuse `NeuphonicTTSSettings`; use inherited `language` field instead of bespoke `lang_code`
- NvidiaTTSService: new `NvidiaTTSSettings` with `quality`
- PiperTTSService / PiperHttpTTSService: new `PiperTTSSettings` / `PiperHttpTTSSettings` (no extra fields)
- SpeechmaticsTTSService: new `SpeechmaticsTTSSettings` with `max_retries`
Also remove redundant `lang_code` from `NeuphonicTTSSettings` (both WS and HTTP services now use the inherited `TTSSettings.language` field, with automatic enum conversion via the base class).
HTTP services (Neuphonic HTTP, Piper HTTP, Speechmatics) don't override `_update_settings` since the base class applies changes to `self._settings` and subsequent requests read from it automatically.
Also:
- remove unnecessary pass-through `_update_settings` implementation in `FalSTTService`
- warn that `AsyncAITTSService` doesn't currently support runtime settings updates
- update how `GradiumTTSService._update_settings` checks for voice changes
- remove a couple of unnecessary args (because they specified defaults) in other examples
ThinkingConfig was defined as an inner class on the service but referenced in the Settings dataclass declared before the service class, causing a crash at import time. Move ThinkingConfig to a standalone class defined before Settings, and keep a class attribute alias for backward compatibility.
Every `*Settings` dataclass field whose default is `NOT_GIVEN` now carries `_NotGiven` in its type union so the type system accurately reflects the three-state semantics (real value, `None` where applicable, or not-yet-specified). Fields previously typed as bare `Any`, `str`, `float`, `bool`, `list`, `dict`, or `Optional[X]` are now narrowed to the specific type from the corresponding `InputParams` Pydantic model.
- Move `CommitStrategy` up in the file so it could be used by `ElevenLabsRealtimeSTTSettings`
- Fix a bug where `run_tts` would erroneously try to reconnect if a reconnection was already in flight (like a reconnection triggered by `_update_settings`)
42 examples covering STT (13), TTS (21), LLM (4), and realtime (4) services. Each demonstrates updating service settings 10 seconds after client connects, verifying the typed settings machinery end-to-end for every provider.
HumeTTSService now stores its params (description, speed, trailing_silence) in a proper `HumeTTSSettings` dataclass instead of a separate `_params` Pydantic model, making it work with `TTSUpdateSettingsFrame(update=...)`. The old `update_setting(key, value)` method is kept but deprecated.
Also removes the unused no-op `TTSService.update_setting` base method, which was never called by the `TTSUpdateSettingsFrame` pipeline.
The dataclass-based API (`*UpdateSettingsFrame(update=*Settings(...))`) is the preferred path since 0.0.103. The dict path still works but now emits a `DeprecationWarning`.
Change `TTSSettings.language` and `STTSettings.language` from `Any` to `Language | str | _NotGiven`. Add `language_to_service_language` base method and centralized `isinstance`-guarded conversion in `STTService._update_settings` (mirroring TTS). Update the TTS guard from `is not None` to `isinstance(…, Language)` so raw strings pass through unchanged.
Remove now-redundant per-service language conversion from `_update_settings` overrides (ElevenLabs, Azure, Fal, Whisper). Add `language_to_service_language` to Azure STT so the centralized conversion picks it up. Fix AWS and NVIDIA STT `__init__` to convert language at construction time, then simplify their runtime accessors to read `_settings.language` directly.
Note that for services that previously handled applying updates (through methods like `set_model` and `set_language`), we're keeping the update-applying logic (some or most of which is already well-tested) and expanding it to cover all relevant settings fields. Services under this bucket are:
- Deepgram STT
- Deepgram Sagemaker STT
- Elevenlabs STT
- Google STT
- Gradium STT
- OpenAI STT
- Speechmatics STT
Now that all services use typed `ServiceSettings` objects, this removes the interim scaffolding that supported both dict-based and typed settings paths in parallel. Specifically: removes old dict-based `_update_settings(settings: Mapping)` methods from base classes, removes `isinstance(self._settings, ServiceSettings)` guards, simplifies `process_frame` branching, and renames `_update_settings_from_typed` to `_update_settings` across all ~30 service implementations. Also renames the no-arg `_update_settings()` helper on realtime services to `_send_session_update()` to avoid collision, adds `from_mapping` overrides on `GoogleLLMSettings` and `AnthropicLLMSettings` for ThinkingConfig dict-to-object conversion, and replaces a broken no-arg `_update_settings()` call in Gemini Live with a TODO.
- NvidiaSTTService.set_model: convert to proper DeprecationWarning (model can't change at runtime for Riva streaming STT)
- NvidiaTTSService.set_model: same treatment for Riva TTS
- NvidiaSegmentedSTTService.set_model: remove — base class now routes through _update_settings_from_typed which re-creates the recognition config
- GeminiTTSService.set_voice: remove — move AVAILABLE_VOICES validation into _update_settings_from_typed so it fires on both legacy and new paths
