v1.3.0

- Pipecat pipelines are multi-agent compatible by default. The new multi-agent framework (`pipecat.workers`) turns every `PipelineWorker`  (previously `PipelineTask`) into a peer on a shared bus that passes typed messages, dispatches `@job` work, and coordinates with siblings, while existing single-pipeline code keeps running untouched. `examples/multi-worker/` ships ready-to-run patterns: LLM handoff, parallel debate, sidecar code assistants and hardware controllers, distributed deployments over Redis or PGMQ, point-to-point WebSocket proxies, and UI workers driving a web client over RTVI.
  (PR [#4493](https://github.com/pipecat-ai/pipecat/pull/4493))

- Added `UIWorker` (`pipecat.workers.ui`): an LLM worker that observes and drives a client web UI over the RTVI UI channel — for voice agents that act on what the user is looking at. It reads the page's accessibility snapshots, routes client UI events to `@ui_event` handlers, drives the page with UI commands (`scroll_to`, `highlight`, `select_text`, `click`, `set_input_value`), and answers screen-grounded questions. `PipelineWorker` connects it to the client automatically when RTVI is enabled — no extra wiring.
    - A voice agent delegates a turn via the built-in `respond` job; the worker returns an answer for the voice LLM to speak, or speaks it verbatim through the agent's TTS with `respond_to_job(answer, tts_speak=True)`.
    - `ReplyToolMixin` provides a ready-made `reply` tool (a spoken answer plus the standard UI actions).
    - `ui_job_group(...)` fans work out to peer workers, surfaced to the client as cancellable progress cards.
    - `UI_STATE_PROMPT_GUIDE` is drop-in system-prompt text that teaches the LLM the `<ui_state>` wire format.
  (PR [#4540](https://github.com/pipecat-ai/pipecat/pull/4540))

- Added `VonageVideoConnectorTransport`, a new transport integration for real-time Vonage WebRTC sessions using the Vonage Video Connector library.
  (PR [#4052](https://github.com/pipecat-ai/pipecat/pull/4052))

- Added `InceptionLLMService` for Inception's Mercury 2 diffusion reasoning model, with support for `reasoning_effort` and `realtime` settings.
  (PR [#4423](https://github.com/pipecat-ai/pipecat/pull/4423))

- Added plain WebSocket transport support to the development runner. Bots can now accept connections from non-telephony WebSocket clients (e.g., browser apps using protobuf framing) via the `/ws-client` endpoint alongside other transports.
  (PR [#4442](https://github.com/pipecat-ai/pipecat/pull/4442))

- Added `GET /status` endpoint to the development runner that reports which transports the running instance accepts (all by default, or the single transport passed via `-t`).
  (PR [#4442](https://github.com/pipecat-ai/pipecat/pull/4442))

- Added support for the Rime `coda` TTS model to `RimeTTSService` and `RimeHttpTTSService`. The `temperature`, `top_p`, and `repetition_penalty` settings are not used by `coda`. Also added a `timeScaleFactor` setting (for the `arcana` and `coda` models) to both services — values above 1.0 slow down audio playback; values below 1.0 speed it up.
  (PR [#4511](https://github.com/pipecat-ai/pipecat/pull/4511))

- Added `max_endpoint_delay_ms` to `SonioxSTTService.Settings`, controlling the maximum delay (500-3000 ms) before endpoint detection finalizes a turn.
  (PR [#4521](https://github.com/pipecat-ai/pipecat/pull/4521))

- Added `LLMService.append_system_instruction(...)`: append durable text to a service's system instruction so it's included on every inference and survives context resets.
  (PR [#4540](https://github.com/pipecat-ai/pipecat/pull/4540))

- Added `CartesiaTurnsSTTService` for streaming speech-to-text against the Cartesia Streaming ASR v2 (Ink-2) turn-based WebSocket endpoint (`/stt/turns/websocket`). The server drives turn boundaries via `turn.start` / `turn.update` / `turn.end` messages, which the service translates into `UserStartedSpeakingFrame`, finalized `TranscriptionFrame`, and `UserStoppedSpeakingFrame`. Eager end-of-turn predictions and turn resumes (`turn.eager_end` and `turn.resume`) are surfaced via the `on_turn_eager_end` and `on_turn_resume` event handlers.
  (PR [#4552](https://github.com/pipecat-ai/pipecat/pull/4552))

- Added the `STTService.supports_ttfs` property, which subclasses can override to return `False` when TTFS doesn't apply to their architecture (e.g. turn-based STTs where the server defines turn boundaries). When `False`, `STTMetadataFrame` is broadcast with `ttfs_p99_latency=0.0` and the "ttfs_p99_latency not set" warning is suppressed.
  (PR [#4585](https://github.com/pipecat-ai/pipecat/pull/4585))

### Changed

- ⚠️ The development runner now supports all transports (WebRTC, Daily, telephony, plain WebSocket) simultaneously from a single server. The `/start` endpoint accepts a `"transport"` field to select the transport per-request; omitting `-t` at startup enables all transports instead of defaulting to WebRTC. The Daily browser-redirect route moved from `GET /` to `GET /daily`.
  (PR [#4442](https://github.com/pipecat-ai/pipecat/pull/4442))

- Changed the default model for `RimeTTSService` and `RimeHttpTTSService` from `arcana` to `coda`. Code that relied on the implicit default should set `model="arcana"` explicitly to preserve previous behavior.
  (PR [#4511](https://github.com/pipecat-ai/pipecat/pull/4511))

- OpenRouter LLM service now defaults to `openai/gpt-4.1`.
  (PR [#4513](https://github.com/pipecat-ai/pipecat/pull/4513))

- OpenRouter LLM requests now convert `developer` messages to `user` messages by default for broader model compatibility. Override this by subclassing `OpenRouterLLMService` or setting `llm.supports_developer_role = True` for models that support the `developer` role.
  (PR [#4513](https://github.com/pipecat-ai/pipecat/pull/4513))

- `SonioxSTTService` now applies settings updates (e.g. via `STTUpdateSettingsFrame`) using a graceful reconnect instead of a hard disconnect/reconnect, preserving the service's reconnect retry behavior.
  (PR [#4521](https://github.com/pipecat-ai/pipecat/pull/4521))

- Updated the default p99 TTFS latency values for Smallest AI, Mistral, and XAI STT so turn stop timing uses measured values instead of the conservative fallback.
  (PR [#4522](https://github.com/pipecat-ai/pipecat/pull/4522))

- Updated the development runner startup banner to show the prebuilt client URL once and list enabled or disabled transports with install hints.
  (PR [#4524](https://github.com/pipecat-ai/pipecat/pull/4524))

- Services and transports with missing optional dependencies now raise `ImportError` instead of a bare `Exception` when their module is imported without the required extra installed. The original `ModuleNotFoundError` is preserved as `__cause__`, so code that wraps these imports can now use `except ImportError:` cleanly instead of `except Exception:`.
  (PR [#4525](https://github.com/pipecat-ai/pipecat/pull/4525))

- Bumped `pipecat-ai-prebuilt` to 1.0.1 in the `runner` extra, updating the prebuilt client UI served by the development runner.
  (PR [#4531](https://github.com/pipecat-ai/pipecat/pull/4531))

- Replaced the `transformers.WhisperFeatureExtractor` dependency in `LocalSmartTurnAnalyzerV3` with a vendored numpy-only implementation, reducing peak RSS at import from ~566 MB to ~60 MB and cold-start time from ~5.0 s to ~0.3 s. Behavior is numerically equivalent (matches the reference numpy code path within 1e-5 absolute tolerance; ONNX model output is bit-identical on representative inputs).
    - Smart Turn v3 no longer imports `transformers` at module load.
    - Prepares the ground for making `transformers` an optional dependency in a future release.
    - The vendored STFT is vectorized via `numpy.lib.stride_tricks.sliding_window_view` + batched `np.fft.rfft`, cutting `_power_spectrogram` runtime by ~55% (~4.0 ms → ~1.8 ms per call on a typical 8-second segment at 16 kHz) while preserving the same parity tolerances against the reference implementation.
  (PR [#4536](https://github.com/pipecat-ai/pipecat/pull/4536))

- ⚠️ Renamed the RTVI UI Worker Protocol's vocabulary from the `pipecat-subagents` `task`/`agent` terms to Pipecat's native `job`/`worker`. This spans the wire messages (`ui-task` → `ui-job-group`, `ui-cancel-task` → `ui-cancel-job-group`), their envelope `kind`s and fields (`task_id` → `job_id`, `agents`/`agent_name` → `workers`/`worker_name`), the paired Python models/frames (`UITask*` → `UIJobGroup*`, `RTVIUITask*Frame` → `RTVIUIJobGroup*Frame`), and the `@pipecat-ai/client-js` / `client-react` APIs (`RTVIEvent.UITask` → `UIJobGroup`, `cancelUITask` → `cancelUIJobGroup`, `useUITasks` → `useUIJobGroups`, `UITasksProvider` → `UIJobGroupsProvider`). These primitives shipped in 1.2.0 but were never documented, so no real consumers are affected.
  (PR [#4540](https://github.com/pipecat-ai/pipecat/pull/4540))

- `transformers` is no longer a base dependency, so `pip install pipecat-ai` no longer pulls it in. This follows Smart Turn v3 dropping its `transformers` import; the only remaining users (the deprecated `LocalSmartTurnAnalyzerV2`/CoreML analyzers and the Moondream service) already require the `local-smart-turn` and `moondream` extras, which continue to install `transformers`.
  (PR [#4546](https://github.com/pipecat-ai/pipecat/pull/4546))

- Widened the `deepgram` extra to `deepgram-sdk>=6.1.1,<8` so installations can resolve to either deepgram-sdk 6.x or 7.x. `DeepgramSTTService` now handles the `agent_rest` keyword argument that deepgram-sdk 7.2.0 added to `DeepgramClientEnvironment`, so custom `base_url` configuration keeps working on both 6.x and 7.x.
  (PR [#4565](https://github.com/pipecat-ai/pipecat/pull/4565))

- Dropped the upper bound on the `websockets-base` extra (`websockets>=13.1`) so downstream deployments can resolve to websockets 16.x and beyond. Pipecat's `websockets` usage relies only on the modern `websockets.asyncio` API plus a handful of public symbols, all of which are retained in 16.x.
  (PR [#4565](https://github.com/pipecat-ai/pipecat/pull/4565))

- Changed the default voice for `GradiumTTSService` to `_6Aslh2DxfmnRLmP`.
  (PR [#4569](https://github.com/pipecat-ai/pipecat/pull/4569))

- `InworldRealtimeLLMService` now defaults the STT model to `inworld/inworld-stt-1`.
  (PR [#4573](https://github.com/pipecat-ai/pipecat/pull/4573))

### Deprecated

- `FrameProcessor.pipeline_task` is deprecated; read `FrameProcessor.pipeline_worker` instead. The old name still works but emits a `DeprecationWarning` and will be removed in a future release.
  (PR [#4493](https://github.com/pipecat-ai/pipecat/pull/4493))

- Passing a worker to `WorkerRunner.run()` is deprecated. Register the worker with `WorkerRunner.add_workers()` before calling `run()` instead. The `worker` argument still works but emits a `DeprecationWarning` and will be removed in a future release.
  (PR [#4493](https://github.com/pipecat-ai/pipecat/pull/4493))

- `PipelineTask`, `PipelineTaskParams`, and the `pipecat.pipeline.task` module have been renamed to `PipelineWorker`, `WorkerParams`, and `pipecat.pipeline.worker`. The old names still resolve (the module re-exports the new symbols) but constructing `PipelineTask` / `PipelineTaskParams` emits a `DeprecationWarning`; they will be removed in a future release.
  (PR [#4493](https://github.com/pipecat-ai/pipecat/pull/4493))

- `PipelineRunner` has been renamed to `WorkerRunner` and moved to `pipecat.workers.runner`, since the runner now runs workers (of which `PipelineWorker` is one kind), not just pipelines. Import `WorkerRunner` from `pipecat.workers.runner`. The old `pipecat.pipeline.runner` module still re-exports both names, and `PipelineRunner` still works as a subclass alias, but it emits a `DeprecationWarning` and will be removed in a future release.
  (PR [#4589](https://github.com/pipecat-ai/pipecat/pull/4589))

### Removed

- Removed the unsupported Georgian (`Language.KA`) language mapping from `SonioxSTTService`.
  (PR [#4521](https://github.com/pipecat-ai/pipecat/pull/4521))

### Fixed

- Fixed Azure TTS last word being missed by observers and RTVI UI. The completion signal was racing with word timestamp processing, causing the final word's `TTSTextFrame` to arrive after `TTSStoppedFrame`. Completion is now routed through the word boundary queue to ensure all words are processed before signaling stream end.
  (PR [#4306](https://github.com/pipecat-ai/pipecat/pull/4306))

- Fixed skipped TTS frames (e.g. code blocks filtered via `skip_aggregator_types`) being emitted to the assistant context immediately instead of waiting for preceding spoken frames to finish. They now hold their position in the frame sequence and are flushed only after all earlier spoken sentences are complete, keeping context ordering correct.
  (PR [#4380](https://github.com/pipecat-ai/pipecat/pull/4380))

- Fixed Cartesia word timestamps leaking SSML tag text (e.g. `<spell>`, `<emotion>`, `<break>`) into word entries. Tags are now stripped before processing, so word-to-text attribution remains accurate when SSML markup is present in the TTS input.
  (PR [#4380](https://github.com/pipecat-ai/pipecat/pull/4380))

- Fixed `BaseOutputTransport` reordering frames that share the same presentation timestamp. Frames with equal PTS values are now emitted in insertion order, preventing subtle audio/text sequencing bugs when multiple frames arrive at the same time.
  (PR [#4380](https://github.com/pipecat-ai/pipecat/pull/4380))

- Fixed `TTSTextFrame` entries losing their original text structure when word timestamps are enabled. Each `TTSTextFrame` now carries a `raw_text` field containing the corresponding span of the original LLM-produced text (including pattern delimiters such as `<card>4111 1111 1111 1111</card>`), so the assistant context receives properly-tagged content rather than the cleaned words returned by the TTS provider. Also handles words that straddle two sentence boundaries by splitting them and attributing each part to its correct source frame.
  (PR [#4380](https://github.com/pipecat-ai/pipecat/pull/4380))

- Fixed `PipelineTask.cancel()` hanging when cancellation is requested before the initial `StartFrame` reaches the pipeline sink.
  (PR [#4455](https://github.com/pipecat-ai/pipecat/pull/4455))

- Fixed `SmallWebRTCClient.read_audio_frame` and `read_video_frame` busy-looping on `MediaStreamError`. When a track raises `MediaStreamError`, the generator now clears the track reference (`_audio_input_track` / `_video_input_track` / `_screen_video_track`) so the loop parks on the existing `is None` gate instead of re-entering `recv()` at ~100 Hz on a permanently-failed track. Renegotiation still resumes seamlessly: when `_handle_client_connected` reassigns a fresh track, the loop picks up frames from the new track.
  (PR [#4491](https://github.com/pipecat-ai/pipecat/pull/4491))

- Fixed `ElevenLabsSTTService` crashing when `language` was passed as `None`. When `language` is not set, the service now lets ElevenLabs auto-detect the audio language.
  (PR [#4507](https://github.com/pipecat-ai/pipecat/pull/4507))

- Fixed `NvidiaSTTService` so unexpected gRPC stream drops reconnect cleanly using the active audio iterator, while service shutdown and cancellation still close that iterator and stop the streaming worker without leaving it stuck waiting for more audio.
  (PR [#4512](https://github.com/pipecat-ai/pipecat/pull/4512))

- Fixed websocket STT connection setup failures so services clear stale websocket state and emit non-fatal error frames, allowing `ServiceSwitcher` failover to keep agents running.
  (PR [#4514](https://github.com/pipecat-ai/pipecat/pull/4514))

- Fixed `ElevenLabsTTSService` and `ElevenLabsHttpTTSService` inserting unwanted spaces between words when synthesizing Chinese or Japanese. Word timestamps for these languages already include their own spacing, so they are now forwarded with `includes_inter_frame_spaces=True` to avoid double-spacing in transcripts and context.
  (PR [#4517](https://github.com/pipecat-ai/pipecat/pull/4517))

- Fixed the development runner so missing optional transport dependencies disable only their related routes instead of failing startup in all-transport mode.
  (PR [#4524](https://github.com/pipecat-ai/pipecat/pull/4524))

- Fixed a race in `ElevenLabsTTSService` where the periodic keepalive could be sent for a new turn's context before that context's `voice_settings` initialization message, causing ElevenLabs to close the WebSocket with a 1008 policy violation (`voice_settings field must be provided in the first message ...`). The keepalive now only targets a context once its context-init has been sent.
  (PR [#4527](https://github.com/pipecat-ai/pipecat/pull/4527))

- Switched `BaseSmartTurn` from `time.time()` to `time.monotonic()` for its three internal interval-math sites (audio-buffer timestamps, speech-start tracking, and the pre-speech buffer-trim loop). Wall-clock time can step forward or backward when NTP adjusts the system clock, which would silently corrupt the buffer trim (prune everything / prune nothing) and the speech-window extraction. The corrected primitive is monotonic and matches the existing `time.perf_counter()` usage already in place for inference-latency metrics.
  (PR [#4542](https://github.com/pipecat-ai/pipecat/pull/4542))

- Fixed `SOXRAudioResampler` and `SOXRStreamAudioResampler` ignoring the configured quality setting. Both resamplers were hardcoded to `VHQ`, which meant `RNNoiseFilter`'s `resampler_quality` argument (defaulting to `QQ` for low-latency real-time use) had no effect. The resamplers now honor the configured quality, with `VHQ` retained as the default.
  (PR [#4551](https://github.com/pipecat-ai/pipecat/pull/4551))

- Fixed `GeminiLiveLLMService` (and `GeminiVertexLiveLLMService`) crashing with `'ContextWindowCompressionParams' object has no attribute 'get'` when `context_window_compression` was supplied through the `settings` API (e.g. `settings=GeminiLiveLLMService.Settings(context_window_compression=ContextWindowCompressionParams(...))`). The setting is now handled whether it arrives as a `ContextWindowCompressionParams` object or as a dict.
  (PR [#4563](https://github.com/pipecat-ai/pipecat/pull/4563))

- Fixed `AudioBufferProcessor` concatenating utterances separated by a silent gap. When no user audio arrives for more than 200 ms, silence proportional to the wall-clock gap is now inserted into the user buffer; the same fix is applied symmetrically to the bot buffer, so two bot utterances spoken seconds apart (e.g. progressive hold messages played while a slow function call runs) remain temporally separated in the recorded audio.
  (PR [#4567](https://github.com/pipecat-ai/pipecat/pull/4567))

- `InworldRealtimeLLMService` no longer logs `WARNING`s for unrecognized realtime server events (e.g. `response.output_text.done`); they are now logged at `DEBUG`.
  (PR [#4573](https://github.com/pipecat-ai/pipecat/pull/4573))

- Fixed a spurious `ttfs_p99_latency not set, using default 1.0s` warning emitted by turn-based STT services (`CartesiaTurnsSTTService`, `DeepgramFluxSTTService`) at pipeline start. These services have no meaningful "speech end → final transcript" interval to measure, because the server defines turn boundaries directly.
  (PR [#4585](https://github.com/pipecat-ai/pipecat/pull/4585))

### Performance

- `BaseSmartTurn` now stores raw `int16` PCM views in its audio buffer and defers the `float32` conversion to the once-per-turn segment extraction, eliminating ~50 per-frame numpy allocations per second per analyzer. Output is bit-identical to the previous per-frame conversion path because `int16 → float32 / 32768.0` distributes over concatenation; subclasses (`LocalSmartTurnAnalyzerV3`, `LocalCoreMLSmartTurnAnalyzer`, `HttpSmartTurnAnalyzer`) all receive the same float32 `audio_array` they did before. Also removes a spurious `np.frombuffer(audio_int16, dtype=np.int16)` re-wrap that was a no-op view-of-a-view of already-int16 data.
  (PR [#4542](https://github.com/pipecat-ai/pipecat/pull/4542))

- Reduced the `soxr` resampling quality preset in `LocalSmartTurnAnalyzerV3` from `VHQ` (~26-tap polyphase) to `HQ` (~16-tap), cutting resample CPU time by 30–50% on non-16 kHz audio sources (~3–10 ms saved per turn at 24/48 kHz). Pipelines already delivering 16 kHz audio are unaffected — the existing `actual_rate == _MODEL_SAMPLE_RATE` fast path skips resampling entirely. The two quality presets differ in filter length, not cutoff or interpolation semantics; on a Whisper-style log-mel feature representation the audible difference sits well below the mel filterbank's quantization noise floor, so model predictions are unchanged on representative inputs.
  (PR [#4542](https://github.com/pipecat-ai/pipecat/pull/4542))