v0.0.68

### Added

- Added `GoogleHttpTTSService` which uses Google's HTTP TTS API.

- Added `TavusTransport`, a new transport implementation compatible with any Pipecat pipeline. When using the `TavusTransport`the Pipecat bot will connect in the same room as the Tavus Avatar and the user.

- Added `PlivoFrameSerializer` to support Plivo calls. A full running example has also been added to `examples/plivo-chatbot`.

- Added `UserBotLatencyLogObserver`. This is an observer that logs the latency between when the user stops speaking and when the bot starts speaking. This gives you an initial idea on how quickly the AI services respond.

- Added `SarvamTTSService`, which implements Sarvam AI's TTS API:
  https://docs.sarvam.ai/api-reference-docs/text-to-speech/convert.

- Added `PipelineTask.add_observer()` and `PipelineTask.remove_observer()` to allow mangaging observers at runtime. This is useful for cases where the task is passed around to other code components that might want to observe the pipeline dynamically.

- Added `user_id` field to `TranscriptionMessage`. This allows identifying the user in a multi-user scenario. Note that this requires that `TranscriptionFrame` has the `user_id` properly set.

- Added new `PipelineTask` event handlers `on_pipeline_started`, `on_pipeline_stopped`, `on_pipeline_ended` and `on_pipeline_cancelled`, which correspond to the `StartFrame`, `StopFrame`, `EndFrame` and `CancelFrame` respectively.

- Added additional languages to `LmntTTSService`. Languages include: `hi`, `id`, `it`, `ja`, `nl`, `pl`, `ru`, `sv`, `th`, `tr`, `uk`, `vi`.

- Added a `model` parameter to the `LmntTTSService` constructor, allowing switching between LMNT models.

- Added `MiniMaxHttpTTSService`, which implements MiniMax's T2A API for TTS.
  Learn more: https://www.minimax.io/platform_overview

- A new function `FrameProcessor.setup()` has been added to allow setting up frame processors before receiving a `StartFrame`. This is what's happening internally: `FrameProcessor.setup()` is called, `StartFrame` is pushed from the beginning of the pipeline, your regular pipeline operations, `EndFrame` or `CancelFrame` are pushed from the beginning of the pipeline and finally `FrameProcessor.cleanup()` is called.

- Added support for OpenTelemetry tracing in Pipecat. This initial implementation includes:

  - A `setup_tracing` method where you can specify your OpenTelemetry exporter
  - Service decorators for STT (`@traced_stt`), LLM (`@traced_llm`), and TTS (`@traced_tts`) which trace the execution and collect properties and metrics (TTFB, token usage, character counts, etc.)
  - Class decorators that provide execution tracking; these are generic and can be used for service tracking as needed
  - Spans that help track traces on a per conversations and turn basis:

  ```
  conversation-uuid
  ├── turn-1
  │   ├── stt_deepgramsttservice
  │   ├── llm_openaillmservice
  │   └── tts_cartesiattsservice
  ...
  └── turn-n
      └── ...
  ```

  By default, Pipecat has implemented service decorators to trace execution of STT, LLM, and TTS services. You can enable tracing by setting `enable_tracing` to `True` in the PipelineTask.

- Added `TurnTrackingObserver`, which tracks the start and end of a user/bot turn pair and emits events `on_turn_started` and `on_turn_stopped` corresponding to the start and end of a turn, respectively.

- Allow passing observers to `run_test()` while running unit tests.

### Changed

- Upgraded `daily-python` to 0.19.1.

- ⚠️ Updated `SmallWebRTCTransport` to align with how other transports handle `on_client_disconnected`. Now, when the connection is closed and no reconnection is attempted, `on_client_disconnected` is called instead of `on_client_close`. The `on_client_close` callback is no longer used, use `on_client_disconnected` instead.

- Check if `PipelineTask` has already been cancelled.

- Don't raise an exception if event handler is not registered.

- Upgraded `deepgram-sdk` to 4.1.0.

- Updated `GoogleTTSService` to use Google's streaming TTS API. The default voice also updated to `en-US-Chirp3-HD-Charon`.

- ⚠️ Refactored the `TavusVideoService`, so it acts like a proxy, sending audio to Tavus and receiving both audio and video. This will make `TavusVideoService` usable with any Pipecat pipeline and with any transport.  This is a **breaking change**, check the `examples/foundational/21a-tavus-layer-small-webrtc.py` to see how to use it.

- `DailyTransport` now uses custom microphone audio tracks instead of virtual microphones. Now, multiple Daily transports can be used in the same process.

- `DailyTransport` now captures audio from individual participants instead of the whole room. This allows identifying audio frames per participant.

- Updated the default model for `AnthropicLLMService` to `claude-sonnet-4-20250514`.

- Updated the default model for `GeminiMultimodalLiveLLMService` to `models/gemini-2.5-flash-preview-native-audio-dialog`.

- `BaseTextFilter` methods `filter()`, `update_settings()`, `handle_interruption()` and `reset_interruption()` are now async.

- `BaseTextAggregator` methods `aggregate()`, `handle_interruption()` and `reset()` are now async.

- The API version for `CartesiaTTSService` and `CartesiaHttpTTSService` has been updated. Also, the `cartesia` dependency has been updated to 2.x.

- `CartesiaTTSService` and `CartesiaHttpTTSService` now support Cartesia's new `speed` parameter which accepts values of `slow`, `normal`, and `fast`.

- `GeminiMultimodalLiveLLMService` now uses the user transcription and usage metrics provided by Gemini Live.

- `GoogleLLMService` has been updated to use `google-genai` instead of the deprecated `google-generativeai`.

### Deprecated

- In `CartesiaTTSService` and `CartesiaHttpTTSService`, `emotion` has been deprecated by Cartesia. Pipecat is following suit and deprecating `emotion` as well.

### Removed

- Since `GeminiMultimodalLiveLLMService` now transcribes it's own audio, the `transcribe_user_audio` arg has been removed. Audio is now transcribed automatically.

- Removed `SileroVAD` frame processor, just use `SileroVADAnalyzer` instead. Also removed, `07a-interruptible-vad.py` example.

### Fixed

- Fixed a `DailyTransport` issue that was not allow capturing video frames if framerate was greater than zero.

- Fixed a `DeegramSTTService` connection issue when the user provided their own `LiveOptions`.

- Fixed a `DailyTransport` issue that would cause images needing resize to block the event loop.

- Fixed an issue with `ElevenLabsTTSService` where changing the model or voice while the service is running wasn't working.

- Fixed an issue that would cause multiple instances of the same class to behave incorrectly if any of the given constructor arguments defaulted to a mutable value (e.g. lists, dictionaries, objects).

- Fixed an issue with `CartesiaTTSService` where `TTSTextFrame` messages weren't being emitted when the model was set to `sonic`. This resulted in the assistant context not being updated with assistant messages.

### Performance

- `DailyTransport`: process audio, video and events in separate tasks.

- Don't create event handler tasks if no user event handlers have been registered.

### Other

- It is now possible to run all (or most) foundational example with multiple transports. By default, they run with P2P (Peer-To-Peer) WebRTC so you can try everything locally. You can also run them with Daily or even with a Twilio phone number.

- Added foundation examples `07y-interruptible-minimax.py` and `07z-interruptible-sarvam.py`to show how to use the `MiniMaxHttpTTSService` and `SarvamTTSService`, respectively.

- Added an `open-telemetry-tracing` example, showing how to setup tracing. The example also includes Jaeger as an open source OpenTelemetry client to review traces from the example runs.

- Added foundational example `29-turn-tracking-observer.py` to show how to use the `TurnTrackingObserver`.