Replace the round-trip push_interruption_task_frame_and_wait() mechanism
with broadcast_interruption(), which pushes an InterruptionFrame both
upstream and downstream directly from the calling processor.
This eliminates race conditions (transcription arriving before the
InterruptionFrame comes back), swallowed-event timeouts (frame blocked
before reaching the sink), and the complexity of _wait_for_interruption
flag / queue bypass / frame.complete() obligations.
- Add broadcast_interruption() to FrameProcessor
- Deprecate push_interruption_task_frame_and_wait() (delegates to new method)
- Remove event field and complete() from InterruptionFrame/InterruptionTaskFrame
- Remove _wait_for_interruption flag and all special-case logic
- Remove frame.complete() calls in stt_mute_filter and llm_response_universal
- Update all 17 call sites to use broadcast_interruption()
- Update tests
Add BotConnectedFrame (SystemFrame) pushed by SFU transports (Daily,
LiveKit, HeyGen, Tavus) when the bot joins the room. Replace the
on_transport_readiness_measured event with on_transport_timing_report
which includes both bot_connected_secs and client_connected_secs.
Azure TTS _handle_canceled was putting None (the normal completion
signal) into the audio queue for all cancellation reasons, so run_tts
treated errors identically to success—silently producing no audio.
Now error cancellations put an Exception marker in the queue, which
run_tts converts to an ErrorFrame.
Azure STT had no canceled event handler at all, so auth failures,
network errors, and rate-limit cancellations were invisible. Added
_on_handle_canceled which pushes an ErrorFrame upstream via push_error.
Fixespipecat-ai/pipecat#3892
When filter_incomplete_user_turns is enabled and an LLMMessagesUpdateFrame
replaces the context via set_messages(), the turn completion instructions
system message was lost. This caused the LLM to stop emitting turn
completion markers. Re-inject the instructions after set_messages() to
fix this.
The ServiceSettings refactor (PR #3714) changed self._settings from
dicts to dataclass subclasses, but tracing code still used .items(),
in containment, and subscript access, causing AttributeError on
every traced call. Use given_fields() for iteration and attribute
access for named fields.
When the user places an RTVIProcessor inside their pipeline and provides
a custom RTVIObserver subclass in observers, PipelineTask correctly
detects both and logs "skipping default ones." However it then
unconditionally prepends self._rtvi to the pipeline, causing the
processor to appear twice in the frame chain.
Track whether the RTVIProcessor was found externally (inside the user
pipeline) vs created internally. Only prepend it when created internally.
Fixes#3867
Add deprecation warnings to start_processing_metrics() and
stop_processing_metrics() on FrameProcessorMetrics and FrameProcessor.
Mark ProcessingMetricsData as deprecated in docstring. All existing
behavior is preserved — the warnings inform users that these will be
removed in a future version.
- Add InterruptionFrame handling with stop_all_metrics()
- Add processing metrics (start/stop) at response boundaries
- Fix agent transcript handling for voice and text modalities:
- Voice mode: push LLMTextFrame (append_to_context=False) and
TTSTextFrame for deltas, skip duplicated final text
- Text mode: push LLMTextFrame with proper response lifecycle,
no TTSTextFrame (downstream TTS handles audio)
- Add output_medium parameter to AgentInputParams and OneShotInputParams
- Improve TTFB measurement using VAD speech end time
- Update example with user turn strategies and transcript events
- Add text-only output example (50a-ultravox-realtime-text.py)
Move the sentence vs token aggregation concern into text aggregators
so all text flows through them regardless of mode. This enables
pattern detection and tag handling to work in TOKEN mode.
- Add TextAggregationMode enum (SENTENCE, TOKEN) as the user-facing
TTS setting, separate from the internal AggregationType
- Add TOKEN mode support to Simple, SkipTags, and PatternPair aggregators
- Add text_aggregation_mode parameter to TTSService and all TTS subclasses
- Deprecate aggregate_sentences in favor of text_aggregation_mode
- Merge TTSService._process_text_frame() into a single codepath
Add TextAggregationMetricsData measuring the time from the first LLM
token to the first complete sentence, representing the latency cost of
sentence aggregation in the TTS pipeline.
This was added in 31daa889e8, but only
to `RimeTTSService`, not to `RimeNonJsonTTSService. Bringing these
to parity means that users switching between the two, with the same
inputs, have more consistent vocalization behaviors.
Introduce a generic TurnMetricsData class for turn detection metrics,
replacing the service-specific SmartTurnMetricsData (now deprecated).
Add end-to-end processing time measurement to KrispVivaTurn, tracking
the interval from VAD speech-to-silence transition to model threshold
crossing. Consume metrics in the strategy _handle_input_audio path
so they are pushed immediately when fresh.
The Krisp VIVA SDK v1.8.0 requires a license key in globalInit(). Add
api_key parameter to KrispVivaSDKManager, KrispVivaTurn, and
KrispVivaFilter with fallback to KRISP_API_KEY env var. Maintain
backwards compatibility with older SDK versions by catching TypeError
and falling back to the old 3-arg signature.
