Standardize all STT, TTS, and LLM service classes to declare `_settings` with the narrowed Settings type as a class-level annotation. This gives editors and type checkers the specific type when hovering or autocompleting on `self._settings` in each service and its subclasses. Inline `self._settings: Type = ...` assignments are replaced with plain `self._settings = ...`.
`filter_incomplete_user_turns` and `user_turn_completion_config` were only handled in the legacy dict-based `_update_settings` code path. This adds them to `LLMSettings` and introduces `LLMService._update_settings_from_typed` so the typed path handles them too.
Does not (yet) touch `InputParams`, to avoid scope creep and touching something currently part of the public API. But there is a lot of overlap between `*Settings` object fields and `InputParams` fields.
Other than discoverability/typing, these are some other improvements brought by this refactor:
- There is now a single code path (see `_update_settings_from_typed`) where services can respond to settings changes (by, say, reconnecting if needed), improving maintainability and guaranteeing one and only one reconnection no matter which settings changed
- `set_language`/`set_model`/`set_voice`—which we're assuming are usable as public methods, though *not* recommended over `*UpdateSettingsFrame`—all use the same code path as settings updates. They're also now all consistent in that, if a service needs to respond to a change (by, say, reconnecting if needed), any of these methods will kick off that process. Note that this is technically a behavior change.
- Several services now properly react to changed settings by reconnecting:
- `AWSTranscribeSTTService`
- `AzureSTTService`
- `SonioxSTTService`
- `GladiaSTTService`
- `SpeechmaticsSTTService`
- `AssemblyAISTTService`
- `CartesiaSTTService`
- `FishAudioTTSService` (would previously only reconnect when `model` changed)
- `GoogleSTTService`
- `SpeechmaticsSTTService` (which previously only handled *some* settings updates through a nonstandard public `update_params` method)
- `GradiumSTTService`
- `NvidiaSegmentedSTTService` (which previously only handled changes to language)
- Bookkeeping across various services has been reduced, mostly by deduping ivars; the `self._settings` ivar is treated as the source of truth
NOTE: I pretty much guarantee that there are services missed in this PR in terms of bringing to consistency with how updates are handled (like whether changes in certain fields trigger reconnects when they need to). We can squash remaining inconsistencies as we stumble onto them, service by service. The goal here is to get things *mostly* in order, and establish the infrastructure and patterns we'll need going forward.
The outer try/except in each service decorator caught both tracing
setup errors and application errors from the wrapped function. If the
function itself raised (e.g. LLM rate limit, TTS timeout), the
exception was caught and the function was called a second time.
Fix by tracking whether the original function was called via a
fn_called flag. If the function was already called, re-raise the
exception instead of falling back to untraced re-execution.
The class_decorators.py module (Traceable, @traceable, @traced) is not
used anywhere in the codebase. Mark it deprecated and fix the misleading
comment in service_decorators.py that referenced it as if it were active.
Consolidate _tracing_enabled and _tracing_context from LLMService,
STTService, and TTSService into the shared AIService base class.
Extract _get_turn_context() helper in service_decorators.py to
encapsulate the repeated pattern across all traced decorators.
Add model-specific params (arcana: repetition_penalty, temperature, top_p;
mistv2: no_text_normalization, save_oovs, segment) with dynamic query param
building via _build_settings(). Model/voice/param changes now trigger
WebSocket reconnection since all settings are URL query params.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This allows non-websocket STT services (like SarvamSTTService, which uses
the Sarvam Python SDK for connection management) to reuse the same keepalive
pattern. Subclasses override _send_keepalive() and _is_keepalive_ready() for
their specific protocol.
ConversationContextProvider and TurnContextProvider were singletons that
stored tracing context as class-level state. When two PipelineTask instances
ran concurrently, they would overwrite each other's context, causing service
spans to attach to the wrong pipeline's turn span.
Replace both singletons with a single TracingContext object owned by each
PipelineTask, threaded to services via StartFrame.
The Grok API now returns prefixed voice names (e.g. "human_Ara") in
session.updated events, causing Pydantic validation errors. Widen the
voice field type from GrokVoice to GrokVoice | str to accept both
user-facing names and server-returned values.
OpenAI's AsyncStream uses close() while async generators (e.g. from
OpenPipe) use aclose(). Replace direct async-with on the stream with a
helper that handles both protocols.
Adds opt-in keepalive_timeout and keepalive_interval params to
WebsocketSTTService. When enabled, a background task sends silent audio
(or a service-specific protocol message) when the connection has been
idle, preventing server-side timeout disconnects.
Subclasses override _send_keepalive(silence) to wrap the silence in
their wire format. The default sends raw PCM bytes.
Enables keepalive for ElevenLabs (10s), Gladia (20s), and Soniox (1s),
replacing their per-service custom keepalive tasks.
