Replace direct references to settings class names (e.g. `FooSettings`) with the nested `Settings` alias form throughout all 87 service files:
- Type annotations: `Settings`
- Runtime code: `self.Settings`
- Docstrings: `ServiceClass.Settings`
- Cross-file inheritance: `ParentService.Settings`
This makes the `Settings` alias the canonical way to reference a service's settings, keeping only the class definition and alias assignment as the remaining hits for each raw settings class name.
* Add ServiceSwitcherStrategyFailover for automatic error-based service switching
Introduce a strategy hierarchy: ServiceSwitcherStrategy (base) →
ServiceSwitcherStrategyManual (handles ManuallySwitchServiceFrame) →
ServiceSwitcherStrategyFailover (adds error-based failover). ServiceSwitcher
now defaults to ServiceSwitcherStrategyManual with strategy_type optional.
Non-fatal ErrorFrames are forwarded to the strategy via handle_error().
* Move metadata request into _set_active_if_available
Requesting metadata is part of making a service active, so it belongs
alongside setting _active_service and firing on_service_switched. This
removes the duplicate queue_frame calls from ServiceSwitcher push_frame
and process_frame.
DailyTransportClient.start_transcription() accepted a settings
parameter but always used self._params.transcription_settings
instead, silently discarding any custom settings passed by callers.
Change transcription_settings to Optional[DailyTranscriptionSettings]
defaulting to None. The default settings are now applied at the call
site when transcription is started, and start_transcription receives
the serialized settings dict directly.
Use CustomVideoSource/CustomVideoTrack for the default camera output instead of
VirtualCameraDevice, mirroring how audio already uses CustomAudioSource/CustomAudioTrack.
Add support for custom video destinations (register_video_destination, add/remove
custom video tracks, routing in write_video_frame) so multiple video tracks can be
published simultaneously.
* Add system_instruction parameter to run_inference
Allow callers to provide a custom system instruction directly when calling
run_inference, without having to construct provider-specific context objects.
For OpenAI, the instruction is prepended as a system message (preserving
existing messages). For Anthropic, Google, and AWS Bedrock, it overrides the
single system field with a warning when an existing system instruction is
present in the context.
* Use system_instruction parameter in _generate_summary
Pass the summarization prompt via run_inference's system_instruction
parameter instead of embedding it as a system message in the context.
* Add changelog for #3968
Constructor/settings system_instruction now takes priority over the
context system message. Previously the context value would overwrite
the constructor value on every call. Warn when both are set.
After interruption, both _playing_context_id and _turn_context_id are
None. If a subclass calls append_to_audio_context(None, frame), the
recovery path matches (None == None) and creates a bogus audio context
that blocks the handler from ever processing the real context.
Early-return when context_id is falsy to prevent this.
The Deepgram TTS service was bypassing pipecats audio context management
system, pushing audio frames directly via push_frame() instead of routing
them through append_to_audio_context(). This caused stale audio to leak
into the pipeline after interruptions and missed ordered playback
guarantees.
- Route audio frames through append_to_audio_context() with context
availability checks to discard stale post-interruption frames
- Handle Flushed responses by appending TTSStoppedFrame and removing
the audio context to signal completion
- Replace _handle_interruption override with on_audio_context_interrupted
hook (the recommended pattern used by ElevenLabs and Cartesia)
- Remove redundant process_frame override that caused double-flush
(base class already flushes via on_turn_context_completed)
- Remove redundant start_tts_usage_metrics call (base class handles
aggregated usage metrics)
