pipecat-ai 0.0.75

v0.0.75 [YANKED]

on Python PyPI

This release has been yanked due to resampling issues affecting audio output quality and critical bugs impacting ParallelPipelines functionality.

Please upgrade to version 0.0.76 or later.

Added

• Added an aggregate_sentences arg in CartesiaTTSService, ElevenLabsTTSService, NeuphonicTTSService and RimeTTSService, where the default value is True. When aggregate_sentences is True, the TTSService aggregates the LLM streamed tokens into sentences by default. Note: setting the value to False requires a custom processor before the TTSService to aggregate LLM tokens.

• Added kwargs to the OLLamaLLMService to allow for configuration args to be passed to Ollama.

• Added call hang-up error handling in TwilioFrameSerializer, which handles the case where the user has hung up before the TwilioFrameSerializer hangs up the call.

Changed

• Updated RTVIObserver and RTVIProcessor to match the new RTVI 1.0.0 protocol.
  This includes:

  • Deprecating support for all messages related to service configuaration and actions.
  • Adding support for obtaining and logging data about client, including its RTVI version and optionally included system information (OS/browser/etc.)
  • Adding support for handling the new client-message RTVI message through either a on_client_message event handler or listening for a new RTVIClientMessageFrame
  • Adding support for responding to a client-message with a server-response via either a direct call on the RTVIProcessor or via pushing a new RTVIServerResponseFrame
  • Adding built-in support for handling the new append-to-context RTVI message which allows a client to add to the user or assistant llm context. No extra code is required for supporting this behavior.
  • Updating all JavaScript and React client RTVI examples to use versions 1.0.0 of the clients.

  Get started migrating to RTVI protocol 1.0.0 by following the migration guide:
  https://docs.pipecat.ai/client/migration-guide

• Refactored AWSBedrockLLMService and AWSPollyTTSService to work asynchronously using aioboto3 instead of the boto3 library.

• The UserIdleProcessor now handles the scenario where function calls take longer than the idle timeout duration. This allows you to use the UserIdleProcessor in conjunction with function calls that take a while to return a result.

Fixed

• Updated the NeuphonicTTSService to work with the updated websocket API.

• Fixed an issue with RivaSTTService where the watchdog feature was causing an error on initialization.

Performance

• Remove unncessary push task in each FrameProcessor.