Merge branch 'main' into krisp-viva-vad-support
This commit is contained in:
Garegin Harutyunyan
@@ -1,42 +0,0 @@
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- Introducing user turn strategies. User turn strategies indicate when the user turn starts or stops. In conversational agents, these are often referred to as start/stop speaking or turn-taking plans or policies.
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User turn start strategies indicate when the user starts speaking (e.g. using VAD events or when a user says one or more words).
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User turn stop strategies indicate when the user stops speaking (e.g. using an end-of-turn detection model or by observing incoming transcriptions).
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A list of strategies can be specified for both strategies; strategies are evaluated in order until one evaluates to true.
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Available user turn start strategies:
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- VADUserTurnStartStrategy
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- TranscriptionUserTurnStartStrategy
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- MinWordsUserTurnStartStrategy
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- ExternalUserTurnStartStrategy
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Available user turn stop strategies:
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- TranscriptionUserTurnStopStrategy
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- TurnAnalyzerUserTurnStopStrategy
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- ExternalUserTurnStopStrategy
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The default strategies are:
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- start: [VADUserTurnStartStrategy, TranscriptionUserTurnStartStrategy]
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- stop: [TranscriptionUserTurnStopStrategy]
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Turn strategies are configured when setting up `LLMContextAggregatorPair`. For example:
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```python
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context_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(
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user_turn_strategies=UserTurnStrategies(
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stop=[
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TurnAnalyzerUserTurnStopStrategy(
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turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams())
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)
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],
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)
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),
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)
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```
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In order to use the user turn strategies you must update to the new universal `LLMContext` and `LLMContextAggregatorPair`.
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@@ -1 +0,0 @@
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- ⚠️ `TransportParams.turn_analyzer` is deprecated and might result in unexpected behavior, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead.
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@@ -1 +0,0 @@
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- `FrameProcessor.interruption_strategies` is deprecated, use `LLMUserAggregator`'s new `user_turn_strategies` parameter instead.
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@@ -1 +0,0 @@
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- `EmulateUserStartedSpeakingFrame` and `EmulateUserStoppedSpeakingFrame` frames are deprecated.
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@@ -1 +0,0 @@
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- Deprecated the `emulated` field in the `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames.
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@@ -1 +0,0 @@
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- The `LLMUserAggregatorParams` and `LLMAssistantAggregatorParams` classes in `pipecat.processors.aggregators.llm_response` are now deprecated. Use the new universal `LLMContext` and `LLMContextAggregatorPair` instead.
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@@ -1 +0,0 @@
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- `pipecat.audio.interruptions.MinWordsInterruptionStrategy` is deprecated. Use `pipecat.turns.user_start.MinWordsUserTurnStartStrategy` with `LLMUserAggregator`'s new `user_turn_strategies` parameter instead.
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@@ -1 +0,0 @@
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- Added `RNNoiseFilter` for real-time noise suppression using RNNoise neural network via pyrnnoise library.
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@@ -1,7 +0,0 @@
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- Updated `ElevenLabsRealtimeSTTService` to accept the `include_language_detection` parameter to detect language.
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```python
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stt = ElevenLabsRealtimeSTTService(
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api_key=os.getenv("ELEVENLABS_API_KEY"),
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include_language_detection=True
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)
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```
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@@ -1,15 +0,0 @@
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- Updated `SpeechmaticsSTTService` to use new Python Voice SDK with improved VAD,
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Smart Turn capabilities, and brings dramatic improvements to latency without
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any impact on accuracy. Use the `turn_detection_mode` parameter to control the
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endpointing of speech, with `TurnDetectionMode.EXTERNAL` (default),
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`TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`.
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```python
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stt = SpeechmaticsSTTService(
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api_key=os.getenv("SPEECHMATICS_API_KEY"),
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params=SpeechmaticsSTTService.InputParams(
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language=Language.EN,
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turn_detection_mode=SpeechmaticsSTTService.TurnDetectionMode.ADAPTIVE,
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speaker_active_format="<{speaker_id}>{text}</{speaker_id}>",
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),
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)
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```
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@@ -1,4 +0,0 @@
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- For `SpeechmaticsSTTService`, the `end_of_utterance_mode` parameter is deprecated.
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Use the new `turn_detection_mode` parameter instead, with `TurnDetectionMode.EXTERNAL`,
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`TurnDetectionMode.ADAPTIVE`, or `TurnDetectionMode.SMART_TURN`. The `enable_vad`
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parameter is also deprecated and is inferred from the `turn_detection_mode`.
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@@ -1,2 +0,0 @@
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- Improved error handling in `ElevenLabsRealtimeSTTService`
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- Fixed an issue in `ElevenLabsRealtimeSTTService` causing an infinite loop that blocks the process if the websocket disconnects due to an error
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@@ -1 +0,0 @@
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- `TranscriptionFrame` and `InterimTranscriptionFrame` produced by `DailyTransport` now include the transport source (i.e., the originating audio track).
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@@ -1 +0,0 @@
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- `daily-python` updated to 0.23.0.
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@@ -1,15 +0,0 @@
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- `OpenAILLMContext` and its associated things (context aggregators, etc.) are now deprecated in favor of the universal `LLMContext` and its associated things.
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From the developer's point of view, switching to using `LLMContext` machinery will usually be a matter of going from this:
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```python
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context = OpenAILLMContext(messages, tools)
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context_aggregator = llm.create_context_aggregator(context)
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```
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To this:
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```
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context = LLMContext(messages, tools)
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context_aggregator = LLMContextAggregatorPair(context)
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```
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@@ -1,8 +0,0 @@
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- Added `GrokRealtimeLLMService` for xAI's Grok Voice Agent API with real-time voice conversations:
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- Support for real-time audio streaming with WebSocket connection
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- Built-in server-side VAD (Voice Activity Detection)
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- Multiple voice options: Ara, Rex, Sal, Eve, Leo
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- Built-in tools support: web_search, x_search, file_search
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- Custom function calling with standard Pipecat tools schema
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- Configurable audio formats (PCM at 8kHz-48kHz)
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@@ -1 +0,0 @@
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- Added an approximation of TTFB for Ultravox.
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@@ -1,5 +0,0 @@
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- Updates to Inworld TTS services:
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- Improved `InworldTTSService`'s websocket implementation to better flush and
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close context to better handle long inputs.
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- Improved docstrings for `InworldTTSService` and `InworldHttpTTSService`.
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@@ -1 +0,0 @@
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- Added a new `AudioContextTTSService` to the TTS service base classes. The `AudioContextWordTTSService` now inherits from `AudioContextTTSService` and `WebsocketWordTTSService`.
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@@ -1,4 +0,0 @@
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- `LLMUserAggregator` now exposes the following events:
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- `on_user_turn_started`: triggered when a user turn starts
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- `on_user_turn_stopped`: triggered when a user turn ends
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- `on_user_turn_stop_timeout`: triggered when a user turn does not stop and times out
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@@ -1,29 +0,0 @@
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- Introducing user mute strategies. User mute strategies indicate when user input should be muted based on the current system state.
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In conversational agents, user mute strategies are used to prevent user input from interrupting bot speech, tool execution, or other critical system operations.
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A list of strategies can be specified; all strategies are evaluated for every frame so that each strategy can maintain its internal state. A user frame is muted if any of the configured strategies indicates it should be muted.
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Available user mute strategies:
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* `FirstSpeechUserMuteStrategy`
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* `MuteUntilFirstBotCompleteUserMuteStrategy`
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* `AlwaysUserMuteStrategy`
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* `FunctionCallUserMuteStrategy`
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User mute strategies replace the legacy `STTMuteFilter` and provide a more flexible and composable approach to muting user input.
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User mute strategies are configured when setting up the `LLMContextAggregatorPair`. For example:
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```python
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context_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(
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user_mute_strategies=[
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FirstSpeechUserMuteStrategy(),
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]
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),
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)
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```
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In order to use user mute strategies you should update to the new universal `LLMContext` and `LLMContextAggregatorPair`.
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@@ -1 +0,0 @@
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- `STTMuteFilter` is deprecated and will be removed in a future version. Use `LLMUserAggregator`'s new `user_mute_strategies` instead.
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@@ -1 +0,0 @@
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- Fixed a bug in `STTMuteFilter` where the user was not always muted during function calls, especially when there were multiple simultaneous calls.
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@@ -1 +0,0 @@
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- `FrameProcessor.interruptions_allowed` is now deprecated, use `LLMUserAggregator`'s new parameter `user_mute_strategies` instead.
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@@ -1,12 +0,0 @@
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- `PipelineParams.allow_interruptions` is now deprecated, use `LLMUserAggregator`'s new parameter `user_turn_strategies` instead. For example, to disable interruptions but still get user turns you can do:
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```python
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context_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(
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user_turn_strategies=UserTurnStrategies(
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start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)],
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),
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),
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)
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```
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@@ -1 +0,0 @@
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- Added `use_ssl` parameter to `NvidiaSTTService`, `NvidiaSegmentedSTTService` and `NvidiaTTSService`.
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@@ -1 +0,0 @@
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- Updated `DeepgramSTTService` to push user started/stopped speaking and interruption frames when `vad_enabled` is set to true. This centralizes the frames into the service, removing the need to have your application code handle Deepgram's events and push these frames.
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@@ -1 +0,0 @@
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- Added `enable_interruptions` constructor argument to all user turn strategies. This tells the `LLMUserAggregator` to push or not push an `InterruptionFrame`.
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@@ -1 +0,0 @@
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- Added `52-live-transcription.py` foundational example demonstrating live transcription and translation from English to Spanish. In this example, the bot is not interruptible: as the user continues speaking, English transcriptions are queued, and the bot continuously translates and speaks each queued sentence in Spanish without being interrupted by new user speech.
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@@ -1 +0,0 @@
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- Fixed a `RNNoiseFilter` issue that would cause a "[Errno 12] Cannot allocate memory" error when processing silence audio frames.
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@@ -1 +0,0 @@
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- Added `split_sentences` parameter to `SpeechmaticsSTTService` to control sentence splitting behavior for finals on sentence boundaries.
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@@ -1,4 +0,0 @@
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- Updated `SpeechmaticsSTTService` for version `0.0.99+`:
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- Fixed `SpeechmaticsSTTService` to listen for `VADUserStoppedSpeakingFrame` in order to finalize transcription.
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- Default to `TurnDetectionMode.FIXED` for Pipecat-controlled end of turn detection.
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- Only emit VAD + interruption frames if VAD is enabled within the plugin (modes other than `TurnDetectionMode.FIXED` or `TurnDetectionMode.EXTERNAL`).
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@@ -1 +0,0 @@
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- Added encoding validation to `DeepgramTTSService` to prevent unsupported encodings from reaching the API. The service now raises `ValueError` at initialization with a clear error message.
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@@ -1,2 +0,0 @@
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- Added word-level timestamp support to `AzureTTSService` for accurate text-to-audio synchronization.
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@@ -1 +0,0 @@
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- Updated `read_audio_frame` & `read_video_frame` methods in `SmallWebRTCClient` to check if the track is enabled before logging a warning.
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@@ -1 +0,0 @@
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- Fixed an issue with function calling where a handler failing to invoke its result callback could leave the context stuck in IN_PROGRESS, causing LLM inference for subsequent function call results to block while waiting on the unresolved call.
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@@ -1 +0,0 @@
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- Fixed an issue with DeepgramTTSService where the model would output "Dot" instead of a period in some circumstances.
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@@ -1 +0,0 @@
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- Added `pronunciation_dict_id` parameter to `CartesiaTTSService.InputParams` and `CartesiaHttpTTSService.InputParams` to support Cartesia's pronunciation dictionary feature for custom pronunciations.
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@@ -1 +0,0 @@
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- Fixed an issue in GeminiLiveLLMService where TranscriptionFrames were occasionally not pushed.
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@@ -1 +0,0 @@
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- Added support for using the HeyGen LiveAvatar API with the `HeyGenTransport` (see https://www.liveavatar.com/).
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@@ -1,8 +0,0 @@
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- Added image support to `OpenAIRealtimeLLMService` via `InputImageRawFrame`:
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- New `start_video_paused` parameter to control initial video input state
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- New `video_frame_detail` parameter to set image processing quality ("auto",
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"low", or "high"). This corresponds to OpenAI Realtime's `image_detail`
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parameter.
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- `set_video_input_paused()` method to pause/resume video input at runtime
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- `set_video_frame_detail()` method to adjust video frame quality dynamically
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- Automatic rate limiting (1 frame per second) to prevent API overload
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@@ -1 +0,0 @@
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- Updated `CartesiaTTSService` to support setting `language=None`, resulting in Cartesia auto-detecting the language of the conversation.
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@@ -1,3 +0,0 @@
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- The bundled Smart Turn weights are now updated to v3.2, which has better
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handling of short utterances, and is more robust against background
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||||
noise.
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@@ -1 +0,0 @@
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- Updated `SpeechmaticsSTTService` dependency to `speechmatics-voice[smart]>=0.2.6`
|
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@@ -1 +0,0 @@
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- Added `UserTurnProcessor`, a frame processor built on `UserTurnController` that pushes `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` frames and interruptions based on the controller's user turn strategies.
|
||||
@@ -1 +0,0 @@
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- Added `UserTurnController` to manage user turns. It emits `on_user_turn_started`, `on_user_turn_stopped`, and `on_user_turn_stop_timeout` events, and can be integrated into processors to detect and handle user turns. `LLMUserAggregator` and `UserTurnProcessor` are implemented using this controller.
|
||||
@@ -1 +0,0 @@
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||||
- Added a new foundational example `53-concurrent-llm-evaluation.py` that shows how to use `UserTurnProcessor`.
|
||||
@@ -1 +0,0 @@
|
||||
- Added `should_interrupt` property to `DeepgramFluxSTTService`, `DeepgramSTTService`, and `SpeechmaticsSTTService` to configure whether the bot should be interrupted when the external service detects user speech.
|
||||
@@ -1,5 +0,0 @@
|
||||
- Smart Turn now takes into account `vad_start_seconds` when buffering audio,
|
||||
meaning that the start of the turn audio is not cut off. This improves
|
||||
accuracy for short utterances.
|
||||
|
||||
- The default value of `pre_speech_ms` is now set to 500ms for Smart Turn.
|
||||
@@ -1,4 +0,0 @@
|
||||
- `LLMAssistantAggregator` now exposes the following events:
|
||||
- `on_assistant_turn_started`: triggered when the assistant turn starts
|
||||
- `on_assistant_turn_stopped`: triggered when the assistant turn ends
|
||||
- `on_assistant_thought`: triggered when there's an assistant thought available
|
||||
@@ -1 +0,0 @@
|
||||
- `TranscriptProcessor` and related data classes and frames (`TranscriptionMessage`, `ThoughtTranscriptionMessage`, `TranscriptionUpdateFrame`) are deprecated. Use `LLMUserAggregator`'s and `LLMAssistantAggregator`'s new events (`on_user_turn_stopped` and `on_assistant_turn_stopped`) instead.
|
||||
@@ -1 +0,0 @@
|
||||
- Added a new foundational example `28-user-assistant-turns.py` that shows how to use the new `LLMUserAggregator` and `LLMAssistantAggregator` events to gather a conversation transcript.
|
||||
@@ -1 +0,0 @@
|
||||
- Deprecated support for the `vad_events` `LiveOptions` in `DeepgramSTTService`. Instead, use a local Silero VAD for VAD events. Additionally, deprecated `should_interrupt` which will be removed along with `vad_events` support in a future release.
|
||||
@@ -1 +0,0 @@
|
||||
- Added `KrispVivaTurn` analyzer for end of turn detection using the Krisp VIVA SDK (requires `krisp_audio`).
|
||||
@@ -1 +0,0 @@
|
||||
- Improved Krisp SDK management to allow `KrispVivaTurn` and `KrispVivaFilter` to share a single SDK instance within the same process.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed potential memory leaks and initialization issues in `KrispVivaFilter` by improving SDK lifecycle management.
|
||||
@@ -1,6 +0,0 @@
|
||||
- Added support for setting up a pipeline task from external files. You can now register custom pipeline task setup files by setting the `PIPECAT_SETUP_FILES` environment variable. This variable should contain a colon-separated list of Python files (e.g. `export PIPECAT_SETUP_FILES="setup1.py:setup.py:..."`). Each file must define a function with the following signature:
|
||||
|
||||
```python
|
||||
async def setup_pipeline_task(task: PipelineTask):
|
||||
...
|
||||
```
|
||||
@@ -1 +0,0 @@
|
||||
- Loading external observers from files is deprecated, use the new pipeline task setup files and `PIPECAT_SETUP_FILES` environment variable instead.
|
||||
@@ -1 +0,0 @@
|
||||
- Updated default model for `GroqTTSService` to `canopylabs/orpheus-v1-english` and voice ID to `autumn`.
|
||||
@@ -1 +0,0 @@
|
||||
- Fixed timing issue in `BaseOutputTransport` where the bot speaking flag was set after awaiting, allowing the event loop to re-enter the method before the guard was set.
|
||||
1
changelog/3449.changed.md
Normal file
1
changelog/3449.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- Renamed tracing span attributes to align with OpenTelemetry GenAI semantic conventions: `gen_ai.system` to `gen_ai.provider.name`, `system` to `gen_ai.system_instructions`, `gen_ai.usage.cache_read_input_tokens` to `gen_ai.usage.cache_read.input_tokens`, and `gen_ai.usage.cache_creation_input_tokens` to `gen_ai.usage.cache_creation.input_tokens`.
|
||||
1
changelog/3449.fixed.md
Normal file
1
changelog/3449.fixed.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed stale `system_instruction` in LLM tracing spans by reading from `_settings.system_instruction` instead of the removed `_system_instruction` attribute.
|
||||
1
changelog/4029.added.2.md
Normal file
1
changelog/4029.added.2.md
Normal file
@@ -0,0 +1 @@
|
||||
- Added `frame_order` parameter to `SyncParallelPipeline`. Set `frame_order=FrameOrder.PIPELINE` to push synchronized output frames in pipeline definition order (all frames from the first pipeline, then the second, etc.) instead of the default arrival order.
|
||||
1
changelog/4029.added.md
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1
changelog/4029.added.md
Normal file
@@ -0,0 +1 @@
|
||||
- Added `sync_with_audio` field to `OutputImageRawFrame`. When set to `True`, the output transport queues image frames with audio so they are displayed only after all preceding audio has been sent, enabling synchronized audio/image playback.
|
||||
1
changelog/4029.fixed.3.md
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1
changelog/4029.fixed.3.md
Normal file
@@ -0,0 +1 @@
|
||||
- Fixed `SyncParallelPipeline` breaking the Whisker debugger.
|
||||
1
changelog/4029.fixed.md
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1
changelog/4029.fixed.md
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@@ -0,0 +1 @@
|
||||
- Fixed `SyncParallelPipeline` race condition where concurrent SystemFrame processing (e.g. from RTVI) could corrupt sink queues and cause deadlocks. SystemFrames now take a fast path that passes them through without draining queued output.
|
||||
1
changelog/4074.added.md
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1
changelog/4074.added.md
Normal file
@@ -0,0 +1 @@
|
||||
- Added `OpenAIResponsesLLMService`, a new LLM service that uses the OpenAI Responses API. Supports streaming text, function calling, usage metrics, and out-of-band inference. Works with the universal `LLMContext` and `LLMContextAggregatorPair`. See `examples/foundational/07-interruptible-openai-responses.py` and `14-function-calling-openai-responses.py`.
|
||||
1
changelog/4075.fixed.md
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1
changelog/4075.fixed.md
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@@ -0,0 +1 @@
|
||||
- Fixed TTS frame ordering so that non-system frames always arrive in correct order relative to the `TTSStartedFrame`/`TTSAudioRawFrame`/`TTSStoppedFrame` sequence. Previously these frames could race ahead of or behind audio context frames, producing out-of-order output downstream.
|
||||
1
changelog/4082.fixed.md
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1
changelog/4082.fixed.md
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@@ -0,0 +1 @@
|
||||
- Fixed `SarvamTTSService` audio and error frames now route through `append_to_audio_context()` instead of `push_frame()`, ensuring correct behavior with audio contexts and interruptions.
|
||||
1
changelog/4083.changed.md
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1
changelog/4083.changed.md
Normal file
@@ -0,0 +1 @@
|
||||
- `DeepgramSageMakerTTSService` now correctly routes audio through the base `TTSService` audio context queue. Audio frames are delivered via `append_to_audio_context()` instead of being pushed directly, enabling proper ordering, interruption handling, and start/stop frame lifecycle management. Interruptions now trigger a `Clear` message to Deepgram (flushing its text buffer) at the right time via `on_audio_context_interrupted`.
|
||||
1
changelog/4090.fixed.md
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1
changelog/4090.fixed.md
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@@ -0,0 +1 @@
|
||||
- Fixed audio frame ordering and interruption handling in Fish Audio, LMNT, Neuphonic, and Rime NonJson TTS services. These services were bypassing the base `TTSService` audio context serialization queue by pushing audio frames directly, which could cause out-of-order frames and broken interruptions during speech.
|
||||
7
changelog/4093.fixed.md
Normal file
7
changelog/4093.fixed.md
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- Fixed Genesys AudioHook serializer to always include the `parameters` field in
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protocol messages. The AudioHook protocol requires every message to carry a
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`parameters` object (even if empty), but `_create_message` omitted it when no
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parameters were provided. This caused clients that validate message structure
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(including the Genesys reference implementation) to reject `pong` and
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parameter-less `closed` responses, breaking server sequence tracking and
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preventing `outputVariables` from reaching the Architect flow.
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