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.
Introduce ClientConnectedFrame (SystemFrame) pushed by all transports
when a client connects. StartupTimingObserver uses this to measure
transport readiness — the time from StartFrame to first client
connection — via a new on_transport_readiness_measured event.
Tracks how long each processor start method takes during pipeline
startup by measuring StartFrame arrive/leave deltas. Emits a timing
report via the on_startup_timing_report event and auto-logs a summary.
Internal pipeline processors are excluded from reports by default.
- 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
- Wire up passing speed setting to Groq, even though only a value of 1.0 is supported today
- Update the 55y example to switch voices instead of changing speed
- Add a 55zn example to exercise runtime updates of Groq STT
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.
- Storage mode: for use in `self._settings`. All fields should be specified, i.e. should not be `NOT_GIVEN`.
- Delta mode: for use in `*UpdateSettingsFrame`.
In service of this, this commit:
- Adds a runtime check that all fields are specified in storage mode
- Updates all services to specify all fields in stored settings
- Updates all services to no longer check for `is_given` in stored settings (not necessary anymore)
- Updates relevant docstrings
- Renames `update` to `delta` in `*UpdateSettingsFrame`
- Updates community integrations guide
Move speech detection tracking outside the per-frame loop in append_audio
since is_speech applies to the whole buffer. Add debug log in
analyze_end_of_turn to show state and probability at decision time. Update
the Krisp VIVA example to use Cartesia TTS and turn analyzer strategy.
Adds a TTS service that connects to Deepgram models deployed on AWS
SageMaker endpoints via HTTP/2 bidirectional streaming. Supports the
Deepgram TTS protocol (Speak, Flush, Clear, Close) over the BiDi
client, with interruption handling and per-turn TTFB metrics.
Updates the example and env.example with separate STT/TTS endpoint names.
- 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
