Deepgram SDK 6.x surfaces connection errors from send_media() instead
of silently swallowing them. This causes error floods when the WebSocket
disconnects since every queued audio frame hits the dead connection.
Wrap send_media() in try/except: on failure, log one warning and set
self._connection = None so subsequent frames skip until the existing
_connection_handler reconnects.
In some cases the openai provider could answer with a `chunk.choices[0].delta.audio = None`, so the process context fails with error:
```
pipecat/services/openai/base_llm.py:552): Error during completion: 'NoneType' object has no attribute 'get'
```
When an InterruptionFrame arrives, the Python-side audio task is
cancelled but frames already submitted to rtc.AudioSource continue
playing from its internal buffer. This causes the bot to keep speaking
for several seconds after being interrupted.
Fix by overriding process_frame in LiveKitOutputTransport to call
audio_source.clear_queue() on InterruptionFrame, immediately flushing
the buffered audio.
ErrorFrames propagating upstream from downstream processors (e.g. TTS) would
enter the ServiceSwitcher via process_frame, traverse the active service sub-pipeline,
and reach push_frame where they incorrectly triggered failover. Now only errors whose
processor is one of the managed services trigger handle_error. Also fix the log in
handle_error to attribute errors to the actual source processor rather than the
current active_service.
Closes#4139
Gemini 3.x can bundle multiple fields (e.g. model_turn and
output_transcription) on the same server_content message. The previous
elif chain would only process the first matching field and silently
drop the rest. Switch to independent if checks so every field is
handled.
When Gemini Live was configured with local VAD (server-side VAD disabled),
the service was listening for the wrong frame types and not sending
ActivityStart/ActivityEnd events to the server. Now it listens for
VADUserStartedSpeakingFrame/VADUserStoppedSpeakingFrame and sends the
appropriate activity signals when local VAD is in use.
Also removes the unnecessary local SileroVADAnalyzer from server-side VAD
examples and adds a new 26a example demonstrating local VAD configuration.
Set GRPC_VERBOSITY=ERROR by default so users do not see noisy fork
handler and abseil warnings from the gRPC C library. Users can still
override by setting GRPC_VERBOSITY themselves.
nvidia-riva-client 2.25.1 ships with gencode compiled against protobuf
6.31.1, which requires a runtime >= 6.31.1. Update protobuf from 5.29.6
to >=6.31.1,<7 and grpcio-tools from 1.67.1 to 1.78.0 to match.
Regenerate frames_pb2.py with the new compiler.
Add DeepgramFluxSageMakerSTTService that combines SageMaker's HTTP/2
transport with Flux's JSON turn detection protocol (StartOfTurn,
EndOfTurn, EagerEndOfTurn, TurnResumed). Includes mid-stream Configure
support, silence watchdog, and an example bot.
Both GrokLLMService and XAIHttpTTSService use the same xAI API (api.x.ai),
so move Grok source files into the xai module. Leave deprecation shims in
the old grok/ paths for backward compatibility.
- Rename XAITTSService → XAIHttpTTSService and XAITTSSettings → XAIHttpTTSSettings
- Add language_to_xai_language() with explicit LANGUAGE_MAP using resolve_language()
- Remove deprecated InputParams, params, voice, language init params
- Remove XAI_DEFAULT_SAMPLE_RATE and XAI_PCM_CODEC constants; add encoding param
- Set sample_rate=None default (picked up from PipelineParams or user)
- Use Language.EN enum instead of string "en" for default language
- Add changelog/4031.added.md
- Add 07e-interruptible-xai.py foundational example
- Update 14g-function-calling-grok.py to use XAIHttpTTSService
- Register 07e in run-release-evals.py
