Pipecat-ai

Changed

- `FastAPIWebsocketParams` now require a serializer.

- `TwilioFrameSerializer` now requires a `streamSid`.

Fixed

- Silero VAD number of frames needs to be 512 for 16000 sample rate or 256 for
8000 sample rate.

Fixed

- Fixed an issue with asynchronous STT services (Deepgram and Azure) that could
interruptions to ignore transcriptions.

- Fixed an issue introduced in 0.0.33 that would cause the LLM to generate
shorter output.

Changed

- Upgraded to Cartesia's new Python library 1.0.0. `CartesiaTTSService` now
expects a voice ID instead of a voice name (you can get the voice ID from
Cartesia's playground). You can also specify the audio `sample_rate` and
`encoding` instead of the previous `output_format`.

Fixed

- Fixed an issue with asynchronous STT services (Deepgram and Azure) that could
cause static audio issues and interruptions to not work properly when dealing
with multiple LLMs sentences.

- Fixed an issue that could mix new LLM responses with previous ones when
handling interruptions.

- Fixed a Daily transport blocking situation that occurred while reading audio
frames after a participant left the room. Needs daily-python >= 0.10.1.

Added

- Allow specifying a `DeepgramSTTService` url which allows using on-prem
Deepgram.

- Added new `FastAPIWebsocketTransport`. This is a new websocket transport that
can be integrated with FastAPI websockets.

- Added new `TwilioFrameSerializer`. This is a new serializer that knows how to
serialize and deserialize audio frames from Twilio.

- Added Daily transport event: `on_dialout_answered`. See
https://reference-python.daily.co/api_reference.html#daily.EventHandler

- Added new `AzureSTTService`. This allows you to use Azure Speech-To-Text.

Performance

- Convert `BaseOutputTransport` and `BaseOutputTransport` to fully use asyncio
and remove the use of threads.

Other

- Added `twilio-chatbot`. This is an example that shows how to integrate Twilio
phone numbers with a Pipecat bot.

- Updated `07f-interruptible-azure.py` to use `AzureLLMService`,
`AzureSTTService` and `AzureTTSService`.

Performance

- Break long audio frames into 20ms chunks instead of 10ms.

Added

- Added `report_only_initial_ttfb` to `PipelineParams`. This will make it so
only the initial TTFB metrics after the user stops talking are reported.

- Added `OpenPipeLLMService`. This service will let you run OpenAI through
OpenPipe's SDK.

- Allow specifying frame processors' name through a new `name` constructor
argument.

- Added `DeepgramSTTService`. This service has an ongoing websocket
connection. To handle this, it subclasses `AIService` instead of
`STTService`. The output of this service will be pushed from the same task,
except system frames like `StartFrame`, `CancelFrame` or
`StartInterruptionFrame`.

Changed

- `FrameSerializer.deserialize()` can now return `None` in case it is not
possible to desearialize the given data.

- `daily_rest.DailyRoomProperties` now allows extra unknown parameters.

Fixed

- Fixed an issue where `DailyRoomProperties.exp` always had the same old
timestamp unless set by the user.

- Fixed a couple of issues with `WebsocketServerTransport`. It needed to use
`push_audio_frame()` and also VAD was not working properly.

- Fixed an issue that would cause LLM aggregator to fail with small
`VADParams.stop_secs` values.

- Fixed an issue where `BaseOutputTransport` would send longer audio frames
preventing interruptions.

Other

- Added new `07h-interruptible-openpipe.py` example. This example shows how to
use OpenPipe to run OpenAI LLMs and get the logs stored in OpenPipe.

- Added new `dialin-chatbot` example. This examples shows how to call the bot
using a phone number.