sketch for runner as a module

Foundational requirements.txt: add silero, websocket optional dep, re…

.github/workflows/format.yaml

@@ -17,7 +17,7 @@ concurrency:
 
 jobs:
   ruff-format:
-    name: "Formatting checker"
+    name: "Code quality checks"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
@@ -39,8 +39,8 @@ jobs:
         run: |
           source .venv/bin/activate
           ruff format --diff
-      - name: Ruff import linter
+      - name: Ruff linter (all rules)
         id: ruff-check
         run: |
           source .venv/bin/activate
-          ruff check --select I
+          ruff check

.github/workflows/publish.yaml

@@ -5,7 +5,7 @@ on:
     inputs:
       gitref:
         type: string
-        description: "what git ref to build"
+        description: "what git tag to build (e.g. v0.0.74)"
         required: true
 
 jobs:

.pre-commit-config.yaml

@@ -4,5 +4,5 @@ repos:
     hooks:
       - id: ruff
         language_version: python3
-        args: [ --select,  I, ]
+        args: [--fix]
       - id: ruff-format

CHANGELOG.md

@@ -5,6 +5,423 @@ All notable changes to **Pipecat** will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Added
+
+- Added a new field `handle_sigterm` to `PipelineRunner`. It defaults to `False`.
+  This field handles SIGTERM signals. The `handle_sigint` field still defaults
+  to `True`, but now it handles only SIGINT signals.
+
+- Added foundational example `14u-function-calling-ollama.py` for Ollama
+  function calling.
+
+- Added `LocalSmartTurnAnalyzerV2`, which supports local on-device inference
+  with the new `smart-turn-v2` turn detection model.
+
+- Added `set_log_level` to `DailyTransport`, allowing setting the logging level
+  for Daily's internal logging system.
+
+### Changed
+
+- Play delayed messages from `ElevenLabsTTSService` if they still belong to the
+  current context.
+
+- Dependency compatibility improvements: Relaxed version constraints for core
+  dependencies to support broader version ranges while maintaining stability:
+
+  - `aiohttp`, `Markdown`, `nltk`, `numpy`, `Pillow`, `pydantic`, `openai`,
+    `numba`: Now support up to the next major version (e.g. `numpy>=1.26.4,<3`)
+  - `pyht`: Relaxed to `>=0.1.6` to resolve `grpcio` conflicts with
+    `nvidia-riva-client`
+  - `fastapi`: Updated to support versions `>=0.115.6,<0.117.0`
+  - `torch`/`torchaudio`: Changed from exact pinning (`==2.5.0`) to compatible
+    range (`~=2.5.0`)
+  - `aws_sdk_bedrock_runtime`: Added Python 3.12+ constraint via environment
+    marker
+  - `numba`: Reduced minimum version to `0.60.0` for better compatibility
+
+- Changed `NeuphonicHttpTTSService` to use a POST based request instead of the
+  `pyneuphonic` package. This removes a package requirement, allowing Neuphonic
+  to work with more services.
+
+- Updated the `deepgram` optional dependency to 4.7.0, which downgrades the
+  `tasks cancelled error` to a debug log. This removes the log from appearing
+  in Pipecat logs upon leaving.
+
+- Upgraded the `websockets` implementation to the new asyncio implementation.
+  Along with this change, we're updating support for versions >=13.1.0 and
+  <15.0.0. All services have been update to use the asyncio implementation.
+
+- Updated `MiniMaxHttpTTSService` with a `base_url` arg where you can specify
+  the Global endpoint (default) or Mainland China.
+
+- Replaced regex-based sentence detection in `match_endofsentence` with NLTK's
+  punkt_tab tokenizer for more reliable sentence boundary detection.
+
+- Changed the `livekit` optional dependency for `tenacity` to
+  `tenacity>=8.2.3,<10.0.0` in order to support the `google-genai` package.
+
+- For `LmntTTSService`, changed the default `model` to `blizzard`, LMNT's
+  recommended model.
+
+### Fixed
+
+- Fixed a dependency issue for uv users where an `llvmlite` version required python 3.9.
+
+- Fixed an issue in `MiniMaxHttpTTSService` where the `pitch` param was the
+  incorrect type.
+
+- Fixed an issue with OpenTelemetry tracing where the `enable_tracing` flag did
+  not disable the internal tracing decorator functions.
+
+- Fixed an issue in `OLLamaLLMService` where kwargs were not passed correctly
+  to the parent class.
+
+- Fixed an issue in `ElevenLabsTTSService` where the word/timestamp pairs were
+  calculating word boundaries incorrectly.
+
+- Fixed an issue where, in some edge cases, the `EmulateUserStartedSpeakingFrame`
+  could be created even if we didn't have a transcription.
+
+- Fixed an issue in `GoogleLLMContext` where it would inject the
+  `system_message` as a "user" message into cases where it was not meant to;
+  it was only meant to do that when there were no "regular" (non-function-call)
+  messages in the context, to ensure that inference would run properly.
+
+- Fixed an issue in `LiveKitTransport` where the `on_audio_track_subscribed` was never emitted.
+
+## [0.0.76] - 2025-07-11
+
+### Added
+
+- Added `SpeechControlParamsFrame`, a new `SystemFrame` that notifies
+  downstream processors of the VAD and Turn analyzer params. This frame is
+  pushed by the `BaseInputTransport` at Start and any time a
+  `VADParamsUpdateFrame` is received.
+
+### Changed
+
+- Two package dependencies have been updated:
+  - `numpy` now supports 1.26.0 and newer
+  - `transformers` now supports 4.48.0 and newer
+
+### Fixed
+
+- Fixed an issue with RTVI's handling of `append-to-context`.
+
+- Fixed an issue where using audio input with a sample rate requiring resampling
+  could result in empty audio being passed to STT services, causing errors.
+
+- Fixed the VAD analyzer to process the full audio buffer as long as it contains
+  more than the minimum required bytes per iteration, instead of only analyzing
+  the first chunk.
+
+- Fixed an issue in ParallelPipeline that caused errors when attempting to drain
+  the queues.
+
+- Fixed an issue with emulated VAD timeout inconsistency in
+  `LLMUserContextAggregator`. Previously, emulated VAD scenarios (where
+  transcription is received without VAD detection) used a hardcoded
+  `aggregation_timeout` (default 0.5s) instead of matching the VAD's
+  `stop_secs` parameter (default 0.8s). This created different user experiences
+  between real VAD and emulated VAD scenarios. Now, emulated VAD timeouts
+  automatically synchronize with the VAD's `stop_secs` parameter.
+
+- Fix a pipeline freeze when using AWS Nova Sonic, which would occur if the
+  user started early, while the bot was still working through
+  `trigger_assistant_response()`.
+
+## [0.0.75] - 2025-07-08
+
+### 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`.
+
+## [0.0.74] - 2025-07-03
+
+### Added
+
+- Added a new STT service, `SpeechmaticsSTTService`. This service provides
+  real-time speech-to-text transcription using the Speechmatics API. It supports
+  partial and final transcriptions, multiple languages, various audio formats,
+  and speaker diarization.
+
+- Added `normalize` and `model_id` to `FishAudioTTSService`.
+
+- Added `http_options` argument to `GoogleLLMService`.
+
+- Added `run_llm` field to `LLMMessagesAppendFrame` and `LLMMessagesUpdateFrame`
+  frames. If true, a context frame will be pushed triggering the LLM to respond.
+
+- Added a new `SOXRStreamAudioResampler` for processing audio in chunks or
+  streams. If you write your own processor and need to use an audio resampler,
+  use the new `create_stream_resampler()`.
+
+- Added new `DailyParams.audio_in_user_tracks` to allow receiving one track per
+  user (default) or a single track from the room (all participants mixed).
+
+- Added support for providing "direct" functions, which don't need an
+  accompanying `FunctionSchema` or function definition dict. Instead, metadata
+  (i.e. `name`, `description`, `properties`, and `required`) are automatically
+  extracted from a combination of the function signature and docstring.
+
+  Usage:
+
+  ```python
+  # "Direct" function
+  # `params` must be the first parameter
+  async def do_something(params: FunctionCallParams, foo: int, bar: str = ""):
+    """
+    Do something interesting.
+
+    Args:
+      foo (int): The foo to do something interesting with.
+      bar (string): The bar to do something interesting with.
+    """
+
+    result = await process(foo, bar)
+    await params.result_callback({"result": result})
+
+  # ...
+
+  llm.register_direct_function(do_something)
+
+  # ...
+
+  tools = ToolsSchema(standard_tools=[do_something])
+  ```
+
+- `user_id` is now populated in the `TranscriptionFrame` and
+  `InterimTranscriptionFrame` when using a transport that provides a `user_id`,
+  like `DailyTransport` or `LiveKitTransport`.
+
+- Added `watchdog_coroutine()`. This is a watchdog helper for couroutines. So,
+  if you have a coroutine that is waiting for a result and that takes a long
+  time, you will need to wrap it with `watchdog_coroutine()` so the watchdog
+  timers are reset regularly.
+
+- Added `session_token` parameter to `AWSNovaSonicLLMService`.
+
+- Added Gemini Multimodal Live File API for uploading, fetching, listing, and
+  deleting files. See `26f-gemini-multimodal-live-files-api.py` for example usage.
+
+### Changed
+
+- Updated all the services to use the new `SOXRStreamAudioResampler`, ensuring smooth
+  transitions and eliminating clicks.
+
+- Upgraded `daily-python` to 0.19.4.
+
+- Updated `google` optional dependency to use `google-genai` version `1.24.0`.
+
+### Fixed
+
+- Fixed an issue where audio would get stuck in the queue when an interrupt occurs
+  during Azure TTS synthesis.
+
+- Fixed a race condition that occurs in Python 3.10+ where the task could miss
+  the `CancelledError` and continue running indefinitely, freezing the pipeline.
+
+- Fixed a `AWSNovaSonicLLMService` issue introduced in 0.0.72.
+
+### Deprecated
+
+- In `FishAudioTTSService`, deprecated `model` and replaced with
+  `reference_id`. This change is to better align with Fish Audio's variable
+  naming and to reduce confusion about what functionality the variable
+  controls.
+
+## [0.0.73] - 2025-06-26
+
+### Fixed
+
+- Fixed an issue introduced in 0.0.72 that would cause `ElevenLabsTTSService`,
+  `GladiaSTTService`, `NeuphonicTTSService` and `OpenAIRealtimeBetaLLMService`
+  to throw an error.
+
+## [0.0.72] - 2025-06-26
+
+### Added
+
+- Added logging and improved error handling to help diagnose and prevent potential
+  Pipeline freezes.
+
+- Added `WatchdogQueue`, `WatchdogPriorityQueue`, `WatchdogEvent` and
+  `WatchdogAsyncIterator`. These helper utilities reset watchdog timers
+  appropriately before they expire. When watchdog timers are disabled, the
+  utilities behave as standard counterparts without side effects.
+
+- Introduce task watchdog timers. Watchdog timers are used to detect if a
+  Pipecat task is taking longer than expected (by default 5 seconds). Watchdog
+  timers are disabled by default and can be enabled globally by passing
+  `enable_watchdog_timers` argument to `PipelineTask` constructor. It is
+  possible to change the default watchdog timer timeout by using the
+  `watchdog_timeout` argument. You can also log how long it takes to reset the
+  watchdog timers which is done with the `enable_watchdog_logging`. You can
+  control all these settings per each frame processor or even per task. That is,
+  you can set `enable_watchdog_timers`, `enable_watchdog_logging` and
+  `watchdog_timeout` when creating any frame processor through their constructor
+  arguments or when you create a task with `FrameProcessor.create_task()`. Note
+  that watchdog timers only work with Pipecat tasks and will not work if you use
+  `asycio.create_task()` or similar.
+
+- Added `lexicon_names` parameter to `AWSPollyTTSService.InputParams`.
+
+- Added reconnection logic and audio buffer management to `GladiaSTTService`.
+
+- The `TurnTrackingObserver` now ends a turn upon observing an `EndFrame` or
+  `CancelFrame`.
+
+- Added Polish support to `AWSTranscribeSTTService`.
+
+- Added new frames `FrameProcessorPauseFrame` and `FrameProcessorResumeFrame`
+  which allow pausing and resuming frame processing for a given frame
+  processor. These are control frames, so they are ordered. Pausing frame
+  processor will keep old frames in the internal queues until resume takes
+  place. Frames being pushed while a frame processor is paused will be pushed to
+  the queues. When frame processing is resumed all queued frames will be
+  processed in order. Also added `FrameProcessorPauseUrgentFrame` and
+  `FrameProcessorResumeUrgentFrame` which are system frames and therefore they
+  have high priority.
+
+- Added a property called `has_function_calls_in_progress` in
+  `LLMAssistantContextAggregator` that exposes whether a function call is in
+  progress.
+
+- Added `SambaNovaLLMService` which provides llm api integration with an
+  OpenAI-compatible interface.
+
+- Added `SambaNovaTTSService` which provides speech-to-text functionality using
+  SambaNovas's (whisper) API.
+
+- Add fundational examples for function calling and transcription
+  `14s-function-calling-sambanova.py`, `13g-sambanova-transcription.py`
+
+### Changed
+
+- `HeartbeatFrame`s are now control frames. This will make it easier to detect
+  pipeline freezes. Previously, heartbeat frames were system frames which meant
+  they were not get queued with other frames, making it difficult to detect
+  pipeline stalls.
+
+- Updated `OpenAIRealtimeBetaLLMService` to accept `language` in the
+  `InputAudioTranscription` class for all models.
+
+- Updated the default model for `OpenAIRealtimeBetaLLMService` to
+  `gpt-4o-realtime-preview-2025-06-03`.
+
+- The `PipelineParams` arg `allow_interruptions` now defaults to `True`.
+
+- `TavusTransport` and `TavusVideoService` now send audio to Tavus using WebRTC
+  audio tracks instead of `app-messages` over WebSocket. This should improve the
+  overall audio quality.
+
+- Upgraded `daily-python` to 0.19.3.
+
+### Fixed
+
+- Fixed an issue that would cause heartbeat frames to be sent before processors
+  were started.
+
+- Fixed an event loop blocking issue when using `SentryMetrics`.
+
+- Fixed an issue in `FastAPIWebsocketClient` to ensure proper disconnection
+  when the websocket is already closed.
+
+- Fixed an issue where the `UserStoppedSpeakingFrame` was not received if the
+  transport was not receiving new audio frames.
+
+- Fixed an edge case where if the user interrupted the bot but no new aggregation
+  was received, the bot would not resume speaking.
+
+- Fixed an issue with `TelnyxFrameSerializer` where it would throw an exception
+  when the user hung up the call.
+
+- Fixed an issue with `ElevenLabsTTSService` where the context was not being
+  closed.
+
+- Fixed function calling in `AWSNovaSonicLLMService`.
+
+- Fixed an issue that would cause multiple `PipelineTask.on_idle_timeout`
+  events to be triggered repeatedly.
+
+- Fixed an issue that was causing user and bot speech to not be synchronized
+  during recordings.
+
+- Fixed an issue where voice settings weren't applied to ElevenLabsTTSService.
+
+- Fixed an issue with `GroqTTSService` where it was not properly parsing the
+  WAV file header.
+
+- Fixed an issue with `GoogleSTTService` where it was constantly reconnecting
+  before starting to receive audio from the user.
+
+- Fixed an issue where `GoogleLLMService`'s TTFB value was incorrect.
+
+### Deprecated
+
+- `AudioBufferProcessor` parameter `user_continuos_stream` is deprecated.
+
+### Other
+
+- Rename `14e-function-calling-gemini.py` to `14e-function-calling-google.py`.
+
 ## [0.0.71] - 2025-06-10
 
 ### Added

CONTRIBUTING.md

@@ -41,36 +41,150 @@ We use Ruff for code linting and formatting. Please ensure your code passes all
 
 We follow Google-style docstrings with these specific conventions:
 
-- Class docstrings should fully document all parameters used in `__init__`
-- We don't require separate docstrings for `__init__` methods when parameters are documented in the class docstring
-- Property methods should have docstrings explaining their purpose and return value
+**Regular Classes:**
 
-Example of correctly documented class:
+- Class docstring describes the class purpose and key functionality
+- `__init__` method has its own docstring with complete `Args:` section documenting all parameters
+- All public methods must have docstrings with `Args:` and `Returns:` sections as appropriate
+
+**Dataclasses:**
+
+- Class docstring describes the purpose and documents all fields in a `Parameters:` section
+- No `__init__` docstring (auto-generated)
+
+**Properties:**
+
+- Must have docstrings with `Returns:` section
+
+**Abstract Methods:**
+
+- Must have docstrings explaining what subclasses should implement
+
+**`__init__.py` Files:**
+
+- **Skip docstrings** for pure import/re-export modules
+- **Add brief docstrings** for top-level packages or those with initialization logic
+
+**Enums:**
+
+- Class docstring describes the enumeration purpose
+- Use `Parameters:` section to document each enum value and its meaning
+- No `__init__` docstring (Enums don't have custom constructors)
+
+**Code Examples in Docstrings:**
+
+- Use `Examples:` as a section header for multiple examples
+- Use descriptive text followed by double colons (`::`) for each example
+- **Always include a blank line after the `::"`**
+- Indent all code consistently within each block
+- Separate multiple examples with blank lines for readability
+
+**Lists and Bullets in Docstrings:**
+
+- Use dashes (`-`) for bullet points, not asterisks (`*`)
+- **Add a blank line before bullet lists** when they follow a colon
+- Use section headers like "Supported features:" or "Behavior:" before lists
+- For complex nested information, consider using paragraph format instead
+
+**Deprecations:**
+
+- Use `warnings.warn()` in code for runtime deprecation warnings
+- Add `.. deprecated::` directive in docstrings for documentation visibility
+- Include version information and describe current status
+- Describe parameters in present tense, use directive to indicate deprecation status
+
+#### Examples:
 
 ```python
-class MyClass:
-    """Class description.
+# Regular class
+class MyService(BaseService):
+    """Description of what the service does.
 
-    Additional details about the class.
+    Provides detailed explanation of the service's functionality,
+    key features, and usage patterns.
 
-    Args:
-        param1: Description of first parameter.
-        param2: Description of second parameter.
+    Supported features:
+
+    - Feature one with detailed explanation
+    - Feature two with additional context
+    - Feature three for advanced use cases
     """
 
-    def __init__(self, param1, param2):
-        # No docstring required here as parameters are documented above
-        self.param1 = param1
-        self.param2 = param2
+    def __init__(self, param1: str, old_param: str = None, **kwargs):
+        """Initialize the service.
+
+        Args:
+            param1: Description of param1.
+            old_param: Controls legacy behavior.
+
+                .. deprecated:: 1.2.0
+                    This parameter no longer has any effect and will be removed in version 2.0.
+
+            **kwargs: Additional arguments passed to parent.
+        """
+        if old_param is not None:
+            import warnings
+            warnings.warn(
+                "Parameter 'old_param' is deprecated and will be removed in version 2.0.",
+                DeprecationWarning,
+            )
+        super().__init__(**kwargs)
 
     @property
-    def some_property(self) -> str:
-        """Get the formatted property value.
+    def sample_rate(self) -> int:
+        """Get the current sample rate.
 
         Returns:
-            A string representation of the property.
+            The sample rate in Hz.
         """
-        return f"Property: {self.param1}"
+        return self._sample_rate
+
+    async def process_data(self, data: str) -> bool:
+        """Process the provided data.
+
+        Args:
+            data: The data to process.
+
+        Returns:
+            True if processing succeeded.
+        """
+        pass
+
+# Dataclass with code examples
+@dataclass
+class MessageFrame:
+    """Frame containing messages in OpenAI format.
+
+    Supports both simple and content list message formats.
+
+    Example::
+
+        [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there!"}
+        ]
+
+    Parameters:
+        messages: List of messages in OpenAI format.
+    """
+
+    messages: List[dict]
+
+# Enum class
+class Status(Enum):
+    """Status codes for processing operations.
+
+    Parameters:
+        PENDING: Operation is queued but not started.
+        RUNNING: Operation is currently in progress.
+        COMPLETED: Operation finished successfully.
+        FAILED: Operation encountered an error.
+    """
+
+    PENDING = "pending"
+    RUNNING = "running"
+    COMPLETED = "completed"
+    FAILED = "failed"
 ```
 
 # Contributor Covenant Code of Conduct

README.md

@@ -51,19 +51,19 @@ You can connect to Pipecat from any platform using our official SDKs:
 
 ## 🧩 Available services
 
-| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
-| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                                                                                                                                                                                                                          |
-| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                                 |
-| Text-to-Speech      | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [FastPitch (NVIDIA)](https://docs.pipecat.ai/server/services/tts/fastpitch), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
-| Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
-| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
-| Serializers         | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         |
-| Video               | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
-| Memory              | [mem0](https://docs.pipecat.ai/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
-| Vision & Image      | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
-| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
-| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
+| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Parakeet (NVIDIA)](https://docs.pipecat.ai/server/services/stt/parakeet), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Ultravox](https://docs.pipecat.ai/server/services/stt/ultravox), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                       |
+| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
+| Text-to-Speech      | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [FastPitch (NVIDIA)](https://docs.pipecat.ai/server/services/tts/fastpitch), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts)                    |
+| Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       |
+| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
+| Serializers         | [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| Video               | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   |
+| Memory              | [mem0](https://docs.pipecat.ai/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+| Vision & Image      | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/fal), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
+| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
 
 📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
 

dev-requirements.txt

@@ -1,13 +1,20 @@
 build~=1.2.2
-coverage~=7.6.12
+coverage~=7.9.1
 grpcio-tools~=1.67.1
 pip-tools~=7.4.1
-pre-commit~=4.0.1
-pyright~=1.1.397
-pytest~=8.3.4
-pytest-asyncio~=0.25.3
+pre-commit~=4.2.0
+pyright~=1.1.402
+pytest~=8.4.1
+pytest-asyncio~=1.0.0
 pytest-aiohttp==1.1.0
-ruff~=0.11.1
-setuptools~=70.0.0
-setuptools_scm~=8.1.0
-python-dotenv~=1.0.1
+ruff~=0.12.1
+setuptools~=78.1.1
+setuptools_scm~=8.3.1
+python-dotenv~=1.1.1
+
+# For running examples
+uvicorn
+python-dotenv
+fastapi
+aiohttp
+aiortc

docs/api/conf.py

@@ -1,5 +1,6 @@
 import logging
 import sys
+from datetime import datetime
 from pathlib import Path
 
 # Configure logging
@@ -13,7 +14,8 @@ sys.path.insert(0, str(project_root / "src"))
 
 # Project information
 project = "pipecat-ai"
-copyright = "2024, Daily"
+current_year = datetime.now().year
+copyright = f"2024-{current_year}, Daily" if current_year > 2024 else "2024, Daily"
 author = "Daily"
 
 # General configuration
@@ -24,19 +26,20 @@ extensions = [
     "sphinx.ext.intersphinx",
 ]
 
+suppress_warnings = [
+    "autodoc.mocked_object",
+]
+
 # Napoleon settings
 napoleon_google_docstring = True
-napoleon_numpy_docstring = False
 napoleon_include_init_with_doc = True
 
 # AutoDoc settings
 autodoc_default_options = {
     "members": True,
     "member-order": "bysource",
-    "special-members": "__init__",
-    "undoc-members": True,
-    "exclude-members": "__weakref__",
-    "no-index": True,
+    "undoc-members": False,
+    "exclude-members": "__weakref__,model_config",
     "show-inheritance": True,
 }
 
@@ -71,20 +74,16 @@ autodoc_mock_imports = [
     "langchain",
     "lmnt",
     "noisereduce",
-    "openai",
     "openpipe",
     "simli",
     "soundfile",
+    "soniox",
     "pipecat_ai_krisp",
     "pyaudio",
     "_tkinter",
     "tkinter",
     "daily",
     "daily_python",
-    "pydantic.BaseModel",
-    "pydantic.Field",
-    "pydantic._internal._model_construction",
-    "pydantic._internal._fields",
     # Moondream dependencies
     "torch",
     "transformers",
@@ -145,85 +144,76 @@ autodoc_mock_imports = [
     "transformers.AutoFeatureExtractor",
     # Also add specific classes that are imported
     "AutoFeatureExtractor",
+    # Sentry dependencies
+    "sentry_sdk",
+    # AWS Nova Sonic dependencies
+    "aws_sdk_bedrock_runtime",
+    "aws_sdk_bedrock_runtime.client",
+    "aws_sdk_bedrock_runtime.config",
+    "aws_sdk_bedrock_runtime.models",
+    "smithy_aws_core",
+    "smithy_aws_core.credentials_resolvers",
+    "smithy_aws_core.credentials_resolvers.static",
+    "smithy_aws_core.identity",
+    "smithy_core",
+    "smithy_core.aio",
+    "smithy_core.aio.eventstream",
+    # MCP dependencies (you may already have these)
+    "mcp",
+    "mcp.client",
+    "mcp.client.session_group",
+    "mcp.client.sse",
+    "mcp.client.stdio",
+    "mcp.ClientSession",
+    "mcp.StdioServerParameters",
+    # gstreamer
+    "gi",
+    "gi.require_version",
+    "gi.repository",
+    # Protobuf mocks
+    "pipecat.frames.protobufs.frames_pb2",
+    "pipecat.serializers.protobuf",
+    "google.protobuf",
+    "google.protobuf.descriptor",
+    "google.protobuf.descriptor_pool",
+    "google.protobuf.runtime_version",
+    "google.protobuf.symbol_database",
+    "google.protobuf.internal.builder",
 ]
 
 # HTML output settings
 html_theme = "sphinx_rtd_theme"
 html_static_path = ["_static"]
-autodoc_typehints = "description"
+autodoc_typehints = "signature"  # Show type hints in the signature only, not in the docstring
 html_show_sphinx = False
 
 
-def verify_modules():
-    """Verify that required modules are available."""
-    required_modules = {
-        "services": [
-            "assemblyai",
-            "aws",
-            "cartesia",
-            "deepgram",
-            "google",
-            "lmnt",
-            "riva",
-            "simli",
-        ],
-        "serializers": ["livekit"],
-        "vad": ["silero", "vad_analyzer"],
-        "transports": {
-            "services": ["daily", "livekit"],
-            "local": ["audio", "tk"],
-            "network": ["fastapi_websocket", "websocket_server"],
-        },
-    }
+def import_core_modules():
+    """Import core pipecat modules for autodoc to discover."""
+    core_modules = [
+        "pipecat",
+        "pipecat.frames",
+        "pipecat.pipeline",
+        "pipecat.processors",
+        "pipecat.services",
+        "pipecat.transports",
+        "pipecat.audio",
+        "pipecat.adapters",
+        "pipecat.clocks",
+        "pipecat.metrics",
+        "pipecat.observers",
+        "pipecat.serializers",
+        "pipecat.sync",
+        "pipecat.transcriptions",
+        "pipecat.utils",
+    ]
 
-    # Skip importing modules that are in autodoc_mock_imports
-    skipped_modules = set(autodoc_mock_imports)
-
-    missing = []
-    for category, modules in required_modules.items():
-        if isinstance(modules, dict):
-            # Handle nested structure
-            for subcategory, submodules in modules.items():
-                for module in submodules:
-                    # Check if module is in autodoc_mock_imports
-                    if (
-                        f"pipecat.{category}.{subcategory}.{module}" in skipped_modules
-                        or module in skipped_modules
-                    ):
-                        logger.info(
-                            f"Skipping import of mocked module: pipecat.{category}.{subcategory}.{module}"
-                        )
-                        continue
-
-                    try:
-                        __import__(f"pipecat.{category}.{subcategory}.{module}")
-                        logger.info(
-                            f"Successfully imported pipecat.{category}.{subcategory}.{module}"
-                        )
-                    except (ImportError, TypeError, NameError) as e:
-                        missing.append(f"pipecat.{category}.{subcategory}.{module}")
-                        logger.warning(
-                            f"Optional module not available: pipecat.{category}.{subcategory}.{module} - {str(e)}"
-                        )
-        else:
-            # Handle flat structure
-            for module in modules:
-                # Check if module is in autodoc_mock_imports
-                if f"pipecat.{category}.{module}" in skipped_modules or module in skipped_modules:
-                    logger.info(f"Skipping import of mocked module: pipecat.{category}.{module}")
-                    continue
-
-                try:
-                    __import__(f"pipecat.{category}.{module}")
-                    logger.info(f"Successfully imported pipecat.{category}.{module}")
-                except (ImportError, TypeError, NameError) as e:
-                    missing.append(f"pipecat.{category}.{module}")
-                    logger.warning(
-                        f"Optional module not available: pipecat.{category}.{module} - {str(e)}"
-                    )
-
-    if missing:
-        logger.warning(f"Some optional modules are not available: {missing}")
+    for module_name in core_modules:
+        try:
+            __import__(module_name)
+            logger.info(f"Successfully imported {module_name}")
+        except ImportError as e:
+            logger.warning(f"Failed to import {module_name}: {e}")
 
 
 def clean_title(title: str) -> str:
@@ -235,36 +225,7 @@ def clean_title(title: str) -> str:
     parts = title.split(".")
     title = parts[-1]
 
-    # Special cases for service names and common acronyms
-    special_cases = {
-        "ai": "AI",
-        "aws": "AWS",
-        "api": "API",
-        "vad": "VAD",
-        "assemblyai": "AssemblyAI",
-        "deepgram": "Deepgram",
-        "elevenlabs": "ElevenLabs",
-        "openai": "OpenAI",
-        "openpipe": "OpenPipe",
-        "playht": "PlayHT",
-        "xtts": "XTTS",
-        "lmnt": "LMNT",
-    }
-
-    # Check if the entire title is a special case
-    if title.lower() in special_cases:
-        return special_cases[title.lower()]
-
-    # Otherwise, capitalize each word
-    words = title.split("_")
-    cleaned_words = []
-    for word in words:
-        if word.lower() in special_cases:
-            cleaned_words.append(special_cases[word.lower()])
-        else:
-            cleaned_words.append(word.capitalize())
-
-    return " ".join(cleaned_words)
+    return title
 
 
 def setup(app):
@@ -289,9 +250,8 @@ def setup(app):
 
     excludes = [
         str(project_root / "src/pipecat/pipeline/to_be_updated"),
-        str(project_root / "src/pipecat/processors/gstreamer"),
-        str(project_root / "src/pipecat/services/to_be_updated"),
-        str(project_root / "src/pipecat/vad"),  # deprecated
+        str(project_root / "src/pipecat/examples"),
+        str(project_root / "src/pipecat/tests"),
         "**/test_*.py",
         "**/tests/*.py",
     ]
@@ -332,5 +292,4 @@ def setup(app):
         logger.error(f"Error generating API documentation: {e}", exc_info=True)
 
 
-# Run module verification
-verify_modules()
+import_core_modules()

docs/api/index.rst

@@ -1,57 +1,17 @@
-Pipecat API Reference Docs
-==========================
+Pipecat API Reference
+=====================
 
-Welcome to Pipecat's API reference documentation!
+Welcome to the Pipecat API reference.
 
-Pipecat is an open source framework for building voice and multimodal assistants.
-It provides a flexible pipeline architecture for connecting various AI services,
-audio processing, and transport layers.
+Use the navigation on the left to browse modules, or search using the search box.
+
+**New to Pipecat?** Check out the `main documentation <https://docs.pipecat.ai>`_ for tutorials, guides, and client SDK information.
 
 Quick Links
 -----------
 
 * `GitHub Repository <https://github.com/pipecat-ai/pipecat>`_
-* `Website <https://pipecat.ai>`_
-
-API Reference
--------------
-
-Core Components
-~~~~~~~~~~~~~~~
-
-* :mod:`Frames <pipecat.frames>`
-* :mod:`Processors <pipecat.processors>`
-* :mod:`Pipeline <pipecat.pipeline>`
-
-Audio Processing
-~~~~~~~~~~~~~~~~
-
-* :mod:`Audio <pipecat.audio>`
-
-Services
-~~~~~~~~
-
-* :mod:`Services <pipecat.services>`
-
-Transport & Serialization
-~~~~~~~~~~~~~~~~~~~~~~~~~
-
-* :mod:`Transports <pipecat.transports>`
-   * :mod:`Local <pipecat.transports.local>`
-   * :mod:`Network <pipecat.transports.network>`
-   * :mod:`Services <pipecat.transports.services>`
-* :mod:`Serializers <pipecat.serializers>`
-
-Utilities
-~~~~~~~~~
-
-* :mod:`Adapters <pipecat.adapters>`
-* :mod:`Clocks <pipecat.clocks>`
-* :mod:`Metrics <pipecat.metrics>`
-* :mod:`Observers <pipecat.observers>`
-* :mod:`Sync <pipecat.sync>`
-* :mod:`Transcriptions <pipecat.transcriptions>`
-* :mod:`Utils <pipecat.utils>`
+* `Join our Community <https://discord.gg/pipecat>`_
 
 .. toctree::
    :maxdepth: 3
@@ -71,11 +31,4 @@ Utilities
    Sync <api/pipecat.sync>
    Transcriptions <api/pipecat.transcriptions>
    Transports <api/pipecat.transports>
-   Utils <api/pipecat.utils>
-
-Indices and tables
-==================
-
-* :ref:`genindex`
-* :ref:`modindex`
-* :ref:`search`
+   Utils <api/pipecat.utils>

docs/api/requirements.txt

@@ -42,9 +42,12 @@ pipecat-ai[openai]
 pipecat-ai[qwen]
 pipecat-ai[remote-smart-turn]
 # pipecat-ai[riva] # Mocked
+pipecat-ai[sambanova]
 pipecat-ai[silero]
 pipecat-ai[simli]
 pipecat-ai[soundfile]
+pipecat-ai[soniox]
+pipecat-ai[speechmatics]
 pipecat-ai[tavus]
 pipecat-ai[together]
 # pipecat-ai[ultravox] # Mocked

dot-env.template

@@ -107,4 +107,17 @@ MINIMAX_API_KEY=...
 MINIMAX_GROUP_ID=...
 
 # Sarvam AI
-SARVAM_API_KEY=...
+SARVAM_API_KEY=...
+
+# Soniox
+SONIOX_API_KEY=
+
+# Speechmatics
+SPEECHMATICS_API_KEY=...
+
+
+# SambaNova
+SAMBANOVA_API_KEY=...
+
+# Sentry
+SENTRY_DSN=...

examples/aws-strands/README.md

@@ -0,0 +1,60 @@
+# AWS Strands Examples
+
+This folder contains two Python examples demonstrating how to use Pipecat with the AWS Strands agent.
+
+## Overview
+
+These examples show how to delegate complex, multi-step tasks to a Strands agent, which can reason step-by-step and call tools to accomplish user requests.
+
+These examples are intentionally simplified for demonstration, using mock API calls. They work best if you ask it:
+
+> What's the weather where the Golden Gate Bridge is?
+
+## Example Scripts
+
+### `black-box.py`
+
+A minimal example that demonstrates how to use the Strands agent with Pipecat. The agent can handle multi-step queries by calling tools, but does not explain its reasoning out loud.
+
+### `explain-thinking.py`
+
+An enhanced example where the Strands agent explains each step of its reasoning in clear, simple language as it works through a multi-step task.
+
+## Quick Start
+
+1. **Clone the repository and navigate to this example:**
+
+   ```bash
+   git clone https://github.com/pipecat-ai/pipecat.git
+   cd pipecat/examples/aws-strands
+   ```
+
+2. **Set up a virtual environment:**
+
+   ```bash
+   python -m venv venv
+   source venv/bin/activate  # On Windows: venv\Scripts\activate
+   ```
+
+3. **Install dependencies:**
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+4. **Configure environment variables:**
+
+   Copy the provided `env.example` file to `.env` and fill in the necessary credentials:
+
+   ```bash
+   cp env.example .env
+   # Then edit .env with your preferred editor
+   ```
+
+5. **Run an example:**
+
+   ```bash
+   python black-box.py
+   # or
+   python explain-thinking.py
+   ```

examples/aws-strands/black-box.py

@@ -0,0 +1,206 @@
+#
+# Copyright (c) 2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import asyncio
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+from strands import Agent, tool
+from strands.models import BedrockModel
+
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.llm_service import FunctionCallParams
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+"""This example demonstrates how to use the Strands agent with Pipecat.
+
+You can delegate complex, multi-step tasks to the Strands agent, which can cycle through LLM-based reasoning and tool calls to accomplish the task.
+
+Try asking: "What's the weather where the Golden Gate Bridge is?"
+"""
+
+# Strands agent tools
+
+
+@tool
+def get_location_name_from_landmark(landmark: str) -> str:
+    """
+    Get the location name from a landmark.
+
+    Args:
+        landmark (str): The name of the landmark, e.g. "Golden Gate Bridge".
+    """
+    # Simulate fetching location
+    return "San Francisco, CA"
+
+
+@tool
+def get_lat_long_from_location_name(location: str) -> dict:
+    """
+    Get the latitude and longitude for a location name.
+
+    Args:
+        location (str): The city and state, e.g. "San Francisco, CA".
+    """
+    # Simulate fetching lat/long from a geocoding service
+    return {"lat": 37.7749, "long": -122.4194}
+
+
+@tool
+def get_current_weather_from_lat_long(lat: float, long: float) -> dict:
+    """
+    Get the current weather for a specific latitude and longitude.
+
+    Args:
+        lat (float): The latitude of the location.
+        long (float): The longitude of the location.
+    """
+    # Simulate fetching weather data from a weather service
+    return {"conditions": "nice", "temperature": "75"}
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    logger.info(f"Starting bot")
+
+    strands_agent = Agent(
+        model=BedrockModel(
+            model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0", max_tokens=64000
+        ),
+        tools=[
+            get_location_name_from_landmark,
+            get_lat_long_from_location_name,
+            get_current_weather_from_lat_long,
+        ],
+        system_prompt="""
+        You are a helpful personal assistant who can look up information about places and weather.
+
+        Your key capabilities:
+        1. Look up where landmarks are located.
+        2. Find latitude and longitude for a location.
+        3. Look up the current weather for a specific latitude and longitude.
+
+        Explain each step of your reasoning in clear, simple, and concise language. Your responses will be converted to audio, so avoid special characters and numbered lists.
+        """,
+    )
+
+    async def handle_location_or_weather_related_queries(params: FunctionCallParams, query: str):
+        """
+        Handle location or weather related queries.
+
+        Args:
+            query (str): The user's query, e.g. "What's the weather where the Golden Gate Bridge is?".
+        """
+        # Run in a background thread
+        # (Otherwise the agent blocks the event loop; one effect of that is that we don't hear
+        # "let me check on that" until the agent finishes)
+        loop = asyncio.get_running_loop()
+        result = await loop.run_in_executor(None, strands_agent, query)
+        await params.result_callback(result.message)
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    llm.register_direct_function(handle_location_or_weather_related_queries)
+
+    @llm.event_handler("on_function_calls_started")
+    async def on_function_calls_started(service, function_calls):
+        await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
+
+    tools = ToolsSchema(standard_tools=[handle_location_or_weather_related_queries])
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way. Start by suggesting that the user ask about the weather where the Golden Gate Bridge is.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages, tools)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            stt,
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/aws-strands/env.example

@@ -0,0 +1,8 @@
+OPENAI_API_KEY=
+CARTESIA_API_KEY=
+DEEPGRAM_API_KEY=
+DAILY_API_KEY=
+DAILY_SAMPLE_ROOM_URL=
+AWS_SECRET_ACCESS_KEY=
+AWS_ACCESS_KEY_ID=
+AWS_REGION=

examples/aws-strands/explain-thinking.py

@@ -0,0 +1,249 @@
+#
+# Copyright (c) 2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import asyncio
+import os
+import threading
+import time
+
+from dotenv import load_dotenv
+from loguru import logger
+from strands import Agent, tool
+from strands.models import BedrockModel
+
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.llm_service import FunctionCallParams
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+"""This example demonstrates how to use the Strands agent with Pipecat in a way where the agent explains its reasoning step-by-step.
+
+You can delegate complex, multi-step tasks to the Strands agent, which can cycle through LLM-based reasoning and tool calls to accomplish the task.
+
+Try asking: "What's the weather where the Golden Gate Bridge is?"
+"""
+
+
+# Strands agent tools
+
+
+@tool
+def get_location_name_from_landmark(landmark: str) -> str:
+    """
+    Get the location name from a landmark.
+
+    Args:
+        landmark (str): The name of the landmark, e.g. "Golden Gate Bridge".
+    """
+    # Simulate fetching location (slowly)
+    time.sleep(3)
+    return "San Francisco, CA"
+
+
+@tool
+def get_lat_long_from_location_name(location: str) -> dict:
+    """
+    Get the latitude and longitude for a location name.
+
+    Args:
+        location (str): The city and state, e.g. "San Francisco, CA".
+    """
+    # Simulate fetching lat/long from a geocoding service (slowly)
+    time.sleep(3)
+    return {"lat": 37.7749, "long": -122.4194}
+
+
+@tool
+def get_current_weather_from_lat_long(lat: float, long: float) -> dict:
+    """
+    Get the current weather for a specific latitude and longitude.
+
+    Args:
+        lat (float): The latitude of the location.
+        long (float): The longitude of the location.
+    """
+    # Simulate fetching weather data from a weather service (slowly)
+    time.sleep(3)
+    return {"conditions": "nice", "temperature": "75"}
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    logger.info(f"Starting bot")
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    next_strands_message_is_last = False
+    strands_messages_queue = asyncio.Queue()
+
+    def strands_callback_handler(**kwargs):
+        """
+        Handle events from the Strands agent.
+        """
+        nonlocal next_strands_message_is_last
+        if "event" in kwargs:
+            event_obj = kwargs["event"]
+            if event_obj and "messageStop" in event_obj:
+                message_stop = event_obj["messageStop"]
+                if message_stop and "stopReason" in message_stop:
+                    stop_reason = message_stop["stopReason"]
+                    if stop_reason == "end_turn":
+                        next_strands_message_is_last = True
+        elif "message" in kwargs:
+            message_obj = kwargs["message"]
+            if message_obj and "content" in message_obj and "role" in message_obj:
+                role = message_obj["role"]
+                content = message_obj["content"]
+                if role == "assistant" and isinstance(content, list):
+                    for content_obj in content:
+                        if isinstance(content_obj, dict) and "text" in content_obj:
+                            message = content_obj["text"]
+                            if not next_strands_message_is_last:
+                                strands_messages_queue.put_nowait(message)
+
+    async def process_strands_messages():
+        while True:
+            message = await strands_messages_queue.get()
+            await tts.queue_frame(TTSSpeakFrame(message))
+            strands_messages_queue.task_done()
+
+    asyncio.create_task(process_strands_messages())
+
+    strands_agent = Agent(
+        model=BedrockModel(
+            model_id="us.anthropic.claude-3-7-sonnet-20250219-v1:0", max_tokens=64000
+        ),
+        tools=[
+            get_location_name_from_landmark,
+            get_lat_long_from_location_name,
+            get_current_weather_from_lat_long,
+        ],
+        system_prompt="""
+        You are a helpful personal assistant who can look up information about places and weather.
+
+        Your key capabilities:
+        1. Look up where landmarks are located.
+        2. Find latitude and longitude for a location.
+        3. Look up the current weather for a specific latitude and longitude.
+
+        Explain each step of your reasoning in clear, simple, and concise language. Your responses will be converted to audio, so avoid special characters and numbered lists.
+        """,
+        callback_handler=strands_callback_handler,
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    async def handle_location_or_weather_related_queries(params: FunctionCallParams, query: str):
+        """
+        Handle location or weather related queries.
+
+        Args:
+            query (str): The user's query, e.g. "What's the weather where the Golden Gate Bridge is?".
+        """
+        # Run in a background thread
+        # (Otherwise the agent blocks the event loop; one effect of that is that we don't hear
+        # the agent's "thinking" messages until the agent finishes)
+        loop = asyncio.get_running_loop()
+        result = await loop.run_in_executor(None, strands_agent, query)
+        await params.result_callback(result.message)
+
+    llm.register_direct_function(handle_location_or_weather_related_queries)
+
+    @llm.event_handler("on_function_calls_started")
+    async def on_function_calls_started(service, function_calls):
+        await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
+
+    tools = ToolsSchema(standard_tools=[handle_location_or_weather_related_queries])
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way. Start by suggesting that the user ask about the weather where the Golden Gate Bridge is.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages, tools)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            stt,
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/aws-strands/requirements.txt

@@ -2,4 +2,5 @@ fastapi
 uvicorn
 python-dotenv
 pipecat-ai[webrtc,daily,deepgram,cartesia]
-pipecat-ai-small-webrtc-prebuilt
+pipecat-ai-small-webrtc-prebuilt
+strands-agents

examples/bot-ready-signalling/client/react-native/package-lock.json

@@ -4364,9 +4364,9 @@
       }
     },
     "node_modules/brace-expansion": {
-      "version": "1.1.11",
-      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.11.tgz",
-      "integrity": "sha512-iCuPHDFgrHX7H2vEI/5xpz07zSHB00TpugqhmYtVmMO6518mCuRMoOYFldEBl0g187ufozdaHgWKcYFb61qGiA==",
+      "version": "1.1.12",
+      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.12.tgz",
+      "integrity": "sha512-9T9UjW3r0UW5c1Q7GTwllptXwhvYmEzFhzMfZ9H7FQWt+uZePjZPjBP/W1ZEyZ1twGWom5/56TF4lPcqjnDHcg==",
       "dependencies": {
         "balanced-match": "^1.0.0",
         "concat-map": "0.0.1"
@@ -6081,9 +6081,9 @@
       }
     },
     "node_modules/glob/node_modules/brace-expansion": {
-      "version": "2.0.1",
-      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.1.tgz",
-      "integrity": "sha512-XnAIvQ8eM+kC6aULx6wuQiwVsnzsi9d3WxzV3FpWTGA19F621kwdbsAcFKXgKUHZWsy+mY6iL1sHTxWEFCytDA==",
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.2.tgz",
+      "integrity": "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==",
       "dependencies": {
         "balanced-match": "^1.0.0"
       }

examples/chatbot-audio-recording/bot.py

@@ -133,7 +133,8 @@ async def main():
             params=PipelineParams(
                 audio_in_sample_rate=16000,
                 audio_out_sample_rate=16000,
-                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
             ),
         )
 

examples/daily-custom-tracks/bot.py

@@ -71,6 +71,8 @@ async def main():
             params=PipelineParams(
                 audio_in_sample_rate=16000,
                 audio_out_sample_rate=16000,
+                enable_metrics=True,
+                enable_usage_metrics=True,
             ),
         )
 

examples/daily-multi-translation/bot.py

@@ -148,10 +148,8 @@ async def main():
             params=PipelineParams(
                 audio_in_sample_rate=16000,
                 audio_out_sample_rate=16000,
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
             observers=[TranscriptionLogObserver()],
         )

examples/daily-multi-translation/requirements.txt

@@ -2,4 +2,4 @@ aiofiles
 python-dotenv
 fastapi[all]
 uvicorn
-pipecat-ai[daily,deepgram,openai,silero,cartesia]
+pipecat-ai[daily,deepgram,openai,silero,cartesia,soundfile]

examples/deployment/flyio-example/bot.py

@@ -75,7 +75,13 @@ async def main(room_url: str, token: str):
         ]
     )
 
-    task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
 
     @transport.event_handler("on_first_participant_joined")
     async def on_first_participant_joined(transport, participant):

examples/deployment/modal-example/client/javascript/package.json

@@ -15,7 +15,7 @@
     "vite": "^6.3.5"
   },
   "dependencies": {
-    "@pipecat-ai/client-js": "^0.3.5",
-    "@pipecat-ai/daily-transport": "^0.3.10"
+    "@pipecat-ai/client-js": "^1.0.0",
+    "@pipecat-ai/daily-transport": "^1.0.0"
   }
 }

examples/deployment/modal-example/client/javascript/src/app.js

@@ -5,7 +5,7 @@
  */
 
 /**
- * RTVI Client Implementation
+ * Pipecat Client Implementation
  *
  * This client connects to an RTVI-compatible bot server using WebRTC (via Daily).
  * It handles audio/video streaming and manages the connection lifecycle.
@@ -16,7 +16,7 @@
  * - Browser with WebRTC support
  */
 
-import { RTVIClient, RTVIEvent } from '@pipecat-ai/client-js';
+import { PipecatClient, RTVIEvent } from '@pipecat-ai/client-js';
 import { DailyTransport } from '@pipecat-ai/daily-transport';
 
 /**
@@ -26,7 +26,7 @@ import { DailyTransport } from '@pipecat-ai/daily-transport';
 class ChatbotClient {
   constructor() {
     // Initialize client state
-    this.rtviClient = null;
+    this.pcClient = null;
     this.setupDOMElements();
     this.initializeClientAndTransport();
     this.setupEventListeners();
@@ -59,7 +59,7 @@ class ChatbotClient {
     this.disconnectBtn.addEventListener('click', () => this.disconnect());
 
     // Populate device selector
-    this.rtviClient.getAllMics().then((mics) => {
+    this.pcClient.getAllMics().then((mics) => {
       console.log('Available mics:', mics);
       mics.forEach((device) => {
         const option = document.createElement('option');
@@ -71,16 +71,16 @@ class ChatbotClient {
     this.deviceSelector.addEventListener('change', (event) => {
       const selectedDeviceId = event.target.value;
       console.log('Selected device ID:', selectedDeviceId);
-      this.rtviClient.updateMic(selectedDeviceId);
+      this.pcClient.updateMic(selectedDeviceId);
     });
 
     // Handle mic mute/unmute toggle
     const micToggleBtn = document.getElementById('mic-toggle-btn');
 
     micToggleBtn.addEventListener('click', () => {
-      let micEnabled = this.rtviClient.isMicEnabled;
+      let micEnabled = this.pcClient.isMicEnabled;
       micToggleBtn.textContent = micEnabled ? 'Unmute Mic' : 'Mute Mic';
-      this.rtviClient.enableMic(!micEnabled);
+      this.pcClient.enableMic(!micEnabled);
       // Add logic to mute/unmute the mic
       if (micEnabled) {
         console.log('Mic muted');
@@ -93,23 +93,12 @@ class ChatbotClient {
   }
 
   /**
-   * Set up the RTVI client and Daily transport
+   * Set up the Pipecat client and Daily transport
    */
   async initializeClientAndTransport() {
-    // Initialize the RTVI client with a DailyTransport and our configuration
-    this.rtviClient = new RTVIClient({
+    // Initialize the Pipecat client with a DailyTransport and our configuration
+    this.pcClient = new PipecatClient({
       transport: new DailyTransport(),
-      params: {
-        // REPLACE WITH YOUR MODAL URL ENDPOINT
-        baseUrl:
-          'https://<Modal workspace>--pipecat-modal-bot-launcher.modal.run',
-        endpoints: {
-          connect: '/connect',
-        },
-        requestData: {
-          bot_name: 'openai',
-        },
-      },
       enableMic: true, // Enable microphone for user input
       enableCam: false,
       callbacks: {
@@ -176,8 +165,8 @@ class ChatbotClient {
     // Set up listeners for media track events
     this.setupTrackListeners();
 
-    await this.rtviClient.initDevices();
-    window.client = this.rtviClient;
+    await this.pcClient.initDevices();
+    window.client = this.pcClient;
   }
 
   /**
@@ -212,10 +201,10 @@ class ChatbotClient {
    * This is called when the bot is ready or when the transport state changes to ready
    */
   setupMediaTracks() {
-    if (!this.rtviClient) return;
+    if (!this.pcClient) return;
 
     // Get current tracks from the client
-    const tracks = this.rtviClient.tracks();
+    const tracks = this.pcClient.tracks();
 
     // Set up any available bot tracks
     if (tracks.bot?.audio) {
@@ -231,10 +220,10 @@ class ChatbotClient {
    * This handles new tracks being added during the session
    */
   setupTrackListeners() {
-    if (!this.rtviClient) return;
+    if (!this.pcClient) return;
 
     // Listen for new tracks starting
-    this.rtviClient.on(RTVIEvent.TrackStarted, (track, participant) => {
+    this.pcClient.on(RTVIEvent.TrackStarted, (track, participant) => {
       // Only handle non-local (bot) tracks
       if (!participant?.local) {
         if (track.kind === 'audio') {
@@ -253,7 +242,7 @@ class ChatbotClient {
     });
 
     // Listen for tracks stopping
-    this.rtviClient.on(RTVIEvent.TrackStopped, (track, participant) => {
+    this.pcClient.on(RTVIEvent.TrackStopped, (track, participant) => {
       if (participant.local) {
         this.log('Local mic muted');
         return;
@@ -311,21 +300,27 @@ class ChatbotClient {
 
   /**
    * Initialize and connect to the bot
-   * This sets up the RTVI client, initializes devices, and establishes the connection
+   * This sets up the Pipecat client, initializes devices, and establishes the connection
    */
   async connect() {
     try {
       const botSelector = document.getElementById('bot-selector');
       const selectedBot = botSelector.value;
-      this.rtviClient.params.requestData.bot_name = selectedBot;
 
       // Initialize audio/video devices
       this.log('Initializing devices...');
-      await this.rtviClient.initDevices();
+      await this.pcClient.initDevices();
 
       // Connect to the bot
       this.log(`Connecting to bot: ${selectedBot}`);
-      await this.rtviClient.connect();
+      await this.pcClient.connect({
+        // REPLACE WITH YOUR MODAL URL ENDPOINT
+        endpoint:
+          'https://<your-workspace>--pipecat-modal-fastapi-app.modal.run/connect',
+        requestData: {
+          bot_name: selectedBot,
+        },
+      });
 
       this.log('Connection complete');
     } catch (error) {
@@ -336,9 +331,9 @@ class ChatbotClient {
       this.updateStatus('Error');
 
       // Clean up if there's an error
-      if (this.rtviClient) {
+      if (this.pcClient) {
         try {
-          await this.rtviClient.disconnect();
+          await this.pcClient.disconnect();
         } catch (disconnectError) {
           this.log(`Error during disconnect: ${disconnectError.message}`);
         }
@@ -350,10 +345,10 @@ class ChatbotClient {
    * Disconnect from the bot and clean up media resources
    */
   async disconnect() {
-    if (this.rtviClient) {
+    if (this.pcClient) {
       try {
-        // Disconnect the RTVI client
-        await this.rtviClient.disconnect();
+        // Disconnect the Pipecat client
+        await this.pcClient.disconnect();
 
         // Clean up audio
         if (this.botAudio.srcObject) {

examples/deployment/modal-example/server/app.py

@@ -301,7 +301,7 @@ def fastapi_app():
         allow_headers=["*"],
     )
 
-    # Include the endpoints from endpoints.py
+    # Include the endpoints from this file
     web_app.include_router(router)
 
     return web_app

examples/deployment/modal-example/server/requirements.txt

@@ -1,2 +1,3 @@
 python-dotenv==1.0.1
-modal==0.71.3
+modal==1.0.5
+fastapi[all]

examples/deployment/modal-example/server/src/bot_gemini.py

@@ -170,7 +170,6 @@ async def run_bot(room_url: str, token: str):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/deployment/modal-example/server/src/bot_openai.py

@@ -198,7 +198,6 @@ async def run_bot(room_url: str, token: str):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/deployment/modal-example/server/src/bot_vllm.py

@@ -211,7 +211,6 @@ async def run_bot(room_url: str, token: str):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/deployment/pipecat-cloud-daily-pstn-server/nextjs-webhook-server/package-lock.json

@@ -8,7 +8,7 @@
       "name": "my-daily-app",
       "version": "0.1.0",
       "dependencies": {
-        "axios": "^1.6.0",
+        "axios": "^1.11.0",
         "next": "^14.0.0",
         "pino": "^8.15.0",
         "react": "^18.2.0",
@@ -215,10 +215,9 @@
       }
     },
     "node_modules/@next/env": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/env/-/env-14.2.26.tgz",
-      "integrity": "sha512-vO//GJ/YBco+H7xdQhzJxF7ub3SUwft76jwaeOyVVQFHCi5DCnkP16WHB+JBylo4vOKPoZBlR94Z8xBxNBdNJA==",
-      "license": "MIT"
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/env/-/env-14.2.30.tgz",
+      "integrity": "sha512-KBiBKrDY6kxTQWGzKjQB7QirL3PiiOkV7KW98leHFjtVRKtft76Ra5qSA/SL75xT44dp6hOcqiiJ6iievLOYug=="
     },
     "node_modules/@next/eslint-plugin-next": {
       "version": "14.2.25",
@@ -231,13 +230,12 @@
       }
     },
     "node_modules/@next/swc-darwin-arm64": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-14.2.26.tgz",
-      "integrity": "sha512-zDJY8gsKEseGAxG+C2hTMT0w9Nk9N1Sk1qV7vXYz9MEiyRoF5ogQX2+vplyUMIfygnjn9/A04I6yrUTRTuRiyQ==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-14.2.30.tgz",
+      "integrity": "sha512-EAqfOTb3bTGh9+ewpO/jC59uACadRHM6TSA9DdxJB/6gxOpyV+zrbqeXiFTDy9uV6bmipFDkfpAskeaDcO+7/g==",
       "cpu": [
         "arm64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "darwin"
@@ -247,13 +245,12 @@
       }
     },
     "node_modules/@next/swc-darwin-x64": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-14.2.26.tgz",
-      "integrity": "sha512-U0adH5ryLfmTDkahLwG9sUQG2L0a9rYux8crQeC92rPhi3jGQEY47nByQHrVrt3prZigadwj/2HZ1LUUimuSbg==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-14.2.30.tgz",
+      "integrity": "sha512-TyO7Wz1IKE2kGv8dwQ0bmPL3s44EKVencOqwIY69myoS3rdpO1NPg5xPM5ymKu7nfX4oYJrpMxv8G9iqLsnL4A==",
       "cpu": [
         "x64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "darwin"
@@ -263,13 +260,12 @@
       }
     },
     "node_modules/@next/swc-linux-arm64-gnu": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-14.2.26.tgz",
-      "integrity": "sha512-SINMl1I7UhfHGM7SoRiw0AbwnLEMUnJ/3XXVmhyptzriHbWvPPbbm0OEVG24uUKhuS1t0nvN/DBvm5kz6ZIqpg==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-14.2.30.tgz",
+      "integrity": "sha512-I5lg1fgPJ7I5dk6mr3qCH1hJYKJu1FsfKSiTKoYwcuUf53HWTrEkwmMI0t5ojFKeA6Vu+SfT2zVy5NS0QLXV4Q==",
       "cpu": [
         "arm64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "linux"
@@ -279,13 +275,12 @@
       }
     },
     "node_modules/@next/swc-linux-arm64-musl": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-14.2.26.tgz",
-      "integrity": "sha512-s6JaezoyJK2DxrwHWxLWtJKlqKqTdi/zaYigDXUJ/gmx/72CrzdVZfMvUc6VqnZ7YEvRijvYo+0o4Z9DencduA==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-14.2.30.tgz",
+      "integrity": "sha512-8GkNA+sLclQyxgzCDs2/2GSwBc92QLMrmYAmoP2xehe5MUKBLB2cgo34Yu242L1siSkwQkiV4YLdCnjwc/Micw==",
       "cpu": [
         "arm64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "linux"
@@ -295,13 +290,12 @@
       }
     },
     "node_modules/@next/swc-linux-x64-gnu": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-14.2.26.tgz",
-      "integrity": "sha512-FEXeUQi8/pLr/XI0hKbe0tgbLmHFRhgXOUiPScz2hk0hSmbGiU8aUqVslj/6C6KA38RzXnWoJXo4FMo6aBxjzg==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-14.2.30.tgz",
+      "integrity": "sha512-8Ly7okjssLuBoe8qaRCcjGtcMsv79hwzn/63wNeIkzJVFVX06h5S737XNr7DZwlsbTBDOyI6qbL2BJB5n6TV/w==",
       "cpu": [
         "x64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "linux"
@@ -311,13 +305,12 @@
       }
     },
     "node_modules/@next/swc-linux-x64-musl": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-14.2.26.tgz",
-      "integrity": "sha512-BUsomaO4d2DuXhXhgQCVt2jjX4B4/Thts8nDoIruEJkhE5ifeQFtvW5c9JkdOtYvE5p2G0hcwQ0UbRaQmQwaVg==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-14.2.30.tgz",
+      "integrity": "sha512-dBmV1lLNeX4mR7uI7KNVHsGQU+OgTG5RGFPi3tBJpsKPvOPtg9poyav/BYWrB3GPQL4dW5YGGgalwZ79WukbKQ==",
       "cpu": [
         "x64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "linux"
@@ -327,13 +320,12 @@
       }
     },
     "node_modules/@next/swc-win32-arm64-msvc": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-14.2.26.tgz",
-      "integrity": "sha512-5auwsMVzT7wbB2CZXQxDctpWbdEnEW/e66DyXO1DcgHxIyhP06awu+rHKshZE+lPLIGiwtjo7bsyeuubewwxMw==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-14.2.30.tgz",
+      "integrity": "sha512-6MMHi2Qc1Gkq+4YLXAgbYslE1f9zMGBikKMdmQRHXjkGPot1JY3n5/Qrbg40Uvbi8//wYnydPnyvNhI1DMUW1g==",
       "cpu": [
         "arm64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "win32"
@@ -343,13 +335,12 @@
       }
     },
     "node_modules/@next/swc-win32-ia32-msvc": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-14.2.26.tgz",
-      "integrity": "sha512-GQWg/Vbz9zUGi9X80lOeGsz1rMH/MtFO/XqigDznhhhTfDlDoynCM6982mPCbSlxJ/aveZcKtTlwfAjwhyxDpg==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-14.2.30.tgz",
+      "integrity": "sha512-pVZMnFok5qEX4RT59mK2hEVtJX+XFfak+/rjHpyFh7juiT52r177bfFKhnlafm0UOSldhXjj32b+LZIOdswGTg==",
       "cpu": [
         "ia32"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "win32"
@@ -359,13 +350,12 @@
       }
     },
     "node_modules/@next/swc-win32-x64-msvc": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-14.2.26.tgz",
-      "integrity": "sha512-2rdB3T1/Gp7bv1eQTTm9d1Y1sv9UuJ2LAwOE0Pe2prHKe32UNscj7YS13fRB37d0GAiGNR+Y7ZcW8YjDI8Ns0w==",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-14.2.30.tgz",
+      "integrity": "sha512-4KCo8hMZXMjpTzs3HOqOGYYwAXymXIy7PEPAXNEcEOyKqkjiDlECumrWziy+JEF0Oi4ILHGxzgQ3YiMGG2t/Lg==",
       "cpu": [
         "x64"
       ],
-      "license": "MIT",
       "optional": true,
       "os": [
         "win32"
@@ -620,11 +610,10 @@
       }
     },
     "node_modules/@typescript-eslint/typescript-estree/node_modules/brace-expansion": {
-      "version": "2.0.1",
-      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.1.tgz",
-      "integrity": "sha512-XnAIvQ8eM+kC6aULx6wuQiwVsnzsi9d3WxzV3FpWTGA19F621kwdbsAcFKXgKUHZWsy+mY6iL1sHTxWEFCytDA==",
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.2.tgz",
+      "integrity": "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==",
       "dev": true,
-      "license": "MIT",
       "dependencies": {
         "balanced-match": "^1.0.0"
       }
@@ -1176,13 +1165,13 @@
       }
     },
     "node_modules/axios": {
-      "version": "1.8.4",
-      "resolved": "https://registry.npmjs.org/axios/-/axios-1.8.4.tgz",
-      "integrity": "sha512-eBSYY4Y68NNlHbHBMdeDmKNtDgXWhQsJcGqzO3iLUM0GraQFSS9cVgPX5I9b3lbdFKyYoAEGAZF1DwhTaljNAw==",
+      "version": "1.11.0",
+      "resolved": "https://registry.npmjs.org/axios/-/axios-1.11.0.tgz",
+      "integrity": "sha512-1Lx3WLFQWm3ooKDYZD1eXmoGO9fxYQjrycfHFC8P0sCfQVXyROp0p9PFWBehewBOdCwHc+f/b8I0fMto5eSfwA==",
       "license": "MIT",
       "dependencies": {
         "follow-redirects": "^1.15.6",
-        "form-data": "^4.0.0",
+        "form-data": "^4.0.4",
         "proxy-from-env": "^1.1.0"
       }
     },
@@ -1224,11 +1213,10 @@
       "license": "MIT"
     },
     "node_modules/brace-expansion": {
-      "version": "1.1.11",
-      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.11.tgz",
-      "integrity": "sha512-iCuPHDFgrHX7H2vEI/5xpz07zSHB00TpugqhmYtVmMO6518mCuRMoOYFldEBl0g187ufozdaHgWKcYFb61qGiA==",
+      "version": "1.1.12",
+      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.12.tgz",
+      "integrity": "sha512-9T9UjW3r0UW5c1Q7GTwllptXwhvYmEzFhzMfZ9H7FQWt+uZePjZPjBP/W1ZEyZ1twGWom5/56TF4lPcqjnDHcg==",
       "dev": true,
-      "license": "MIT",
       "dependencies": {
         "balanced-match": "^1.0.0",
         "concat-map": "0.0.1"
@@ -2448,14 +2436,15 @@
       }
     },
     "node_modules/form-data": {
-      "version": "4.0.2",
-      "resolved": "https://registry.npmjs.org/form-data/-/form-data-4.0.2.tgz",
-      "integrity": "sha512-hGfm/slu0ZabnNt4oaRZ6uREyfCj6P4fT/n6A1rGV+Z0VdGXjfOhVUpkn6qVQONHGIFwmveGXyDs75+nr6FM8w==",
+      "version": "4.0.4",
+      "resolved": "https://registry.npmjs.org/form-data/-/form-data-4.0.4.tgz",
+      "integrity": "sha512-KrGhL9Q4zjj0kiUt5OO4Mr/A/jlI2jDYs5eHBpYHPcBEVSiipAvn2Ko2HnPe20rmcuuvMHNdZFp+4IlGTMF0Ow==",
       "license": "MIT",
       "dependencies": {
         "asynckit": "^0.4.0",
         "combined-stream": "^1.0.8",
         "es-set-tostringtag": "^2.1.0",
+        "hasown": "^2.0.2",
         "mime-types": "^2.1.12"
       },
       "engines": {
@@ -2614,11 +2603,10 @@
       }
     },
     "node_modules/glob/node_modules/brace-expansion": {
-      "version": "2.0.1",
-      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.1.tgz",
-      "integrity": "sha512-XnAIvQ8eM+kC6aULx6wuQiwVsnzsi9d3WxzV3FpWTGA19F621kwdbsAcFKXgKUHZWsy+mY6iL1sHTxWEFCytDA==",
+      "version": "2.0.2",
+      "resolved": "https://registry.npmjs.org/brace-expansion/-/brace-expansion-2.0.2.tgz",
+      "integrity": "sha512-Jt0vHyM+jmUBqojB7E1NIYadt0vI0Qxjxd2TErW94wDz+E2LAm5vKMXXwg6ZZBTHPuUlDgQHKXvjGBdfcF1ZDQ==",
       "dev": true,
-      "license": "MIT",
       "dependencies": {
         "balanced-match": "^1.0.0"
       }
@@ -3613,12 +3601,11 @@
       "license": "MIT"
     },
     "node_modules/next": {
-      "version": "14.2.26",
-      "resolved": "https://registry.npmjs.org/next/-/next-14.2.26.tgz",
-      "integrity": "sha512-b81XSLihMwCfwiUVRRja3LphLo4uBBMZEzBBWMaISbKTwOmq3wPknIETy/8000tr7Gq4WmbuFYPS7jOYIf+ZJw==",
-      "license": "MIT",
+      "version": "14.2.30",
+      "resolved": "https://registry.npmjs.org/next/-/next-14.2.30.tgz",
+      "integrity": "sha512-+COdu6HQrHHFQ1S/8BBsCag61jZacmvbuL2avHvQFbWa2Ox7bE+d8FyNgxRLjXQ5wtPyQwEmk85js/AuaG2Sbg==",
       "dependencies": {
-        "@next/env": "14.2.26",
+        "@next/env": "14.2.30",
         "@swc/helpers": "0.5.5",
         "busboy": "1.6.0",
         "caniuse-lite": "^1.0.30001579",
@@ -3633,15 +3620,15 @@
         "node": ">=18.17.0"
       },
       "optionalDependencies": {
-        "@next/swc-darwin-arm64": "14.2.26",
-        "@next/swc-darwin-x64": "14.2.26",
-        "@next/swc-linux-arm64-gnu": "14.2.26",
-        "@next/swc-linux-arm64-musl": "14.2.26",
-        "@next/swc-linux-x64-gnu": "14.2.26",
-        "@next/swc-linux-x64-musl": "14.2.26",
-        "@next/swc-win32-arm64-msvc": "14.2.26",
-        "@next/swc-win32-ia32-msvc": "14.2.26",
-        "@next/swc-win32-x64-msvc": "14.2.26"
+        "@next/swc-darwin-arm64": "14.2.30",
+        "@next/swc-darwin-x64": "14.2.30",
+        "@next/swc-linux-arm64-gnu": "14.2.30",
+        "@next/swc-linux-arm64-musl": "14.2.30",
+        "@next/swc-linux-x64-gnu": "14.2.30",
+        "@next/swc-linux-x64-musl": "14.2.30",
+        "@next/swc-win32-arm64-msvc": "14.2.30",
+        "@next/swc-win32-ia32-msvc": "14.2.30",
+        "@next/swc-win32-x64-msvc": "14.2.30"
       },
       "peerDependencies": {
         "@opentelemetry/api": "^1.1.0",

examples/deployment/pipecat-cloud-daily-pstn-server/nextjs-webhook-server/package.json

@@ -9,7 +9,7 @@
     "lint": "next lint"
   },
   "dependencies": {
-    "axios": "^1.6.0",
+    "axios": "^1.11.0",
     "next": "^14.0.0",
     "pino": "^8.15.0",
     "react": "^18.2.0",

examples/deployment/pipecat-cloud-daily-pstn-server/nextjs-webhook-server/pages/api/dial.js

@@ -103,7 +103,7 @@ export default async function handler(req, res) {
       const sip_config = {
         display_name: From,
         sip_mode: 'dial-in',
-        num_endpoints: call_transfer !== null ? 2 : 1,
+        num_endpoints: (call_transfer !== undefined && call_transfer !== null) ? 2 : 1,
         codecs: {"audio": ["OPUS"]},
       };
       daily_room_properties.sip = sip_config;

examples/deployment/pipecat-cloud-example/bot.py

@@ -67,10 +67,8 @@ async def main(transport: DailyTransport):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 
@@ -92,7 +90,7 @@ async def main(transport: DailyTransport):
         logger.info("Participant left: {}", participant)
         await task.cancel()
 
-    runner = PipelineRunner()
+    runner = PipelineRunner(handle_sigint=False, force_gc=True)
 
     await runner.run(task)
 

examples/fal-smart-turn/README.md

@@ -44,7 +44,7 @@ Try the hosted version of the demo here: https://pcc-smart-turn.vercel.app/.
 4. Run the server:
 
    ```bash
-   LOCAL=1 python server.py
+   LOCAL_RUN=1 python server.py
    ```
 
 ### Run the client

examples/fal-smart-turn/client/package.json

@@ -9,9 +9,9 @@
     "lint": "next lint"
   },
   "dependencies": {
-    "@pipecat-ai/client-js": "^0.3.5",
-    "@pipecat-ai/client-react": "^0.3.5",
-    "@pipecat-ai/daily-transport": "^0.3.10",
+    "@pipecat-ai/client-js": "^1.0.0",
+    "@pipecat-ai/client-react": "^1.0.0",
+    "@pipecat-ai/daily-transport": "^1.0.0",
     "next": "15.3.1",
     "react": "^19.0.0",
     "react-dom": "^19.0.0"

examples/fal-smart-turn/client/src/app/layout.tsx

@@ -1,5 +1,5 @@
 import './globals.css';
-import { RTVIProvider } from '@/providers/RTVIProvider';
+import { PipecatProvider } from '@/providers/PipecatProvider';
 
 export const metadata = {
   title: 'Pipecat React Client',
@@ -20,7 +20,7 @@ export default function RootLayout({
         <link rel="icon" href="/favicon.svg" type="image/svg+xml" />
       </head>
       <body>
-        <RTVIProvider>{children}</RTVIProvider>
+        <PipecatProvider>{children}</PipecatProvider>
       </body>
     </html>
   );

examples/fal-smart-turn/client/src/app/page.tsx

@@ -1,22 +1,22 @@
 'use client';
 
 import {
-  RTVIClientAudio,
-  RTVIClientVideo,
-  useRTVIClientTransportState,
+  PipecatClientAudio,
+  PipecatClientVideo,
+  usePipecatClientTransportState,
 } from '@pipecat-ai/client-react';
 import { ConnectButton } from '../components/ConnectButton';
 import { StatusDisplay } from '../components/StatusDisplay';
 import { DebugDisplay } from '../components/DebugDisplay';
 
 function BotVideo() {
-  const transportState = useRTVIClientTransportState();
+  const transportState = usePipecatClientTransportState();
   const isConnected = transportState !== 'disconnected';
 
   return (
     <div className="bot-container">
       <div className="video-container">
-        {isConnected && <RTVIClientVideo participant="bot" fit="cover" />}
+        {isConnected && <PipecatClientVideo participant="bot" fit="cover" />}
       </div>
     </div>
   );
@@ -35,7 +35,7 @@ export default function Home() {
       </div>
 
       <DebugDisplay />
-      <RTVIClientAudio />
+      <PipecatClientAudio />
     </div>
   );
 }

examples/fal-smart-turn/client/src/components/ConnectButton.tsx

@@ -1,11 +1,17 @@
 import {
-  useRTVIClient,
-  useRTVIClientTransportState,
+  usePipecatClient,
+  usePipecatClientTransportState,
 } from '@pipecat-ai/client-react';
 
+// Get the API base URL from environment variables
+// Default to "/api" if not specified
+// "/api" is the default for Next.js API routes and used
+// for the Pipecat Cloud deployed agent
+const API_BASE_URL = process.env.NEXT_PUBLIC_API_BASE_URL || '/api';
+
 export function ConnectButton() {
-  const client = useRTVIClient();
-  const transportState = useRTVIClientTransportState();
+  const client = usePipecatClient();
+  const transportState = usePipecatClientTransportState();
   const isConnected = ['connected', 'ready'].includes(transportState);
 
   const handleClick = async () => {
@@ -18,7 +24,10 @@ export function ConnectButton() {
       if (isConnected) {
         await client.disconnect();
       } else {
-        await client.connect();
+        await client.connect({
+          endpoint: `${API_BASE_URL}/connect`,
+          requestData: { foo: 'bar' },
+        });
       }
     } catch (error) {
       console.error('Connection error:', error);

examples/fal-smart-turn/client/src/components/DebugDisplay.tsx

@@ -6,7 +6,7 @@ import {
   TranscriptData,
   BotLLMTextData,
 } from '@pipecat-ai/client-js';
-import { useRTVIClient, useRTVIClientEvent } from '@pipecat-ai/client-react';
+import { usePipecatClient, useRTVIClientEvent } from '@pipecat-ai/client-react';
 import './DebugDisplay.css';
 
 interface SmartTurnResultData {
@@ -20,7 +20,7 @@ interface SmartTurnResultData {
 
 export function DebugDisplay() {
   const debugLogRef = useRef<HTMLDivElement>(null);
-  const client = useRTVIClient();
+  const client = usePipecatClient();
 
   const log = useCallback((message: string) => {
     if (!debugLogRef.current) return;

examples/fal-smart-turn/client/src/components/StatusDisplay.tsx

@@ -1,7 +1,7 @@
-import { useRTVIClientTransportState } from '@pipecat-ai/client-react';
+import { usePipecatClientTransportState } from '@pipecat-ai/client-react';
 
 export function StatusDisplay() {
-  const transportState = useRTVIClientTransportState();
+  const transportState = usePipecatClientTransportState();
 
   return (
     <div className="status">

examples/fal-smart-turn/client/src/providers/PipecatProvider.tsx

@@ -0,0 +1,28 @@
+'use client';
+
+import { PipecatClient } from '@pipecat-ai/client-js';
+import { DailyTransport } from '@pipecat-ai/daily-transport';
+import { PipecatClientProvider } from '@pipecat-ai/client-react';
+import { PropsWithChildren, useEffect, useState } from 'react';
+
+export function PipecatProvider({ children }: PropsWithChildren) {
+  const [client, setClient] = useState<PipecatClient | null>(null);
+
+  useEffect(() => {
+    const pcClient = new PipecatClient({
+      transport: new DailyTransport(),
+      enableMic: true,
+      enableCam: false,
+    });
+
+    setClient(pcClient);
+  }, []);
+
+  if (!client) {
+    return null;
+  }
+
+  return (
+    <PipecatClientProvider client={client}>{children}</PipecatClientProvider>
+  );
+}

examples/fal-smart-turn/client/src/providers/RTVIProvider.tsx

@@ -1,43 +0,0 @@
-'use client';
-
-import { RTVIClient } from '@pipecat-ai/client-js';
-import { DailyTransport } from '@pipecat-ai/daily-transport';
-import { RTVIClientProvider } from '@pipecat-ai/client-react';
-import { PropsWithChildren, useEffect, useState } from 'react';
-
-// Get the API base URL from environment variables
-// Default to "/api" if not specified
-// "/api" is the default for Next.js API routes and used
-// for the Pipecat Cloud deployed agent
-const API_BASE_URL = process.env.NEXT_PUBLIC_API_BASE_URL || '/api';
-
-console.log('Using API base URL:', API_BASE_URL);
-
-export function RTVIProvider({ children }: PropsWithChildren) {
-  const [client, setClient] = useState<RTVIClient | null>(null);
-
-  useEffect(() => {
-    const transport = new DailyTransport();
-
-    const rtviClient = new RTVIClient({
-      transport,
-      params: {
-        baseUrl: API_BASE_URL,
-        endpoints: {
-          connect: '/connect',
-        },
-        requestData: { foo: 'bar' },
-      },
-      enableMic: true,
-      enableCam: false,
-    });
-
-    setClient(rtviClient);
-  }, []);
-
-  if (!client) {
-    return null;
-  }
-
-  return <RTVIClientProvider client={client}>{children}</RTVIClientProvider>;
-}

examples/fal-smart-turn/server/bot.py

@@ -45,7 +45,7 @@ from pipecat.transports.services.daily import DailyParams, DailyTransport
 load_dotenv(override=True)
 
 # Check if we're in local development mode
-LOCAL = os.getenv("LOCAL")
+LOCAL = os.getenv("LOCAL_RUN")
 
 logger.remove()
 logger.add(sys.stderr, level="DEBUG")
@@ -192,7 +192,6 @@ async def main(transport: DailyTransport):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/foundational/03b-still-frame-imagen.py

@@ -47,7 +47,10 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
 
     task = PipelineTask(
         Pipeline([imagegen, transport.output()]),
-        params=PipelineParams(enable_metrics=True),
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
     )
 
     # Register an event handler so we can play the audio when the client joins

examples/foundational/04-transports-small-webrtc.py

@@ -93,10 +93,8 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/04a-transports-daily.py

@@ -20,7 +20,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.transports.services.daily import DailyLogLevel, DailyParams, DailyTransport
 
 load_dotenv(override=True)
 
@@ -43,6 +43,7 @@ async def main():
                 vad_analyzer=SileroVADAnalyzer(),
             ),
         )
+        transport.set_log_level(DailyLogLevel.Info)
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -75,10 +76,8 @@ async def main():
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
         )
 

examples/foundational/04b-transports-livekit.py

@@ -158,7 +158,8 @@ async def main():
             ],
         ),
         params=PipelineParams(
-            allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
+            enable_metrics=True,
+            enable_usage_metrics=True,
         ),
     )
 

examples/foundational/06a-image-sync.py

@@ -133,10 +133,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07-interruptible-cartesia-http.py

@@ -84,10 +84,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07-interruptible.py

@@ -83,10 +83,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07a-interruptible-speechmatics.py

@@ -0,0 +1,153 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import (
+    LLMUserAggregatorParams,
+)
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.base_llm import BaseOpenAILLMService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.services.speechmatics.stt import SpeechmaticsSTTService
+from pipecat.transcriptions.language import Language
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    """Run example using Speechmatics STT.
+
+    This example will use diarization within our STT service and output the words spoken by
+    each individual speaker and wrap them with XML tags for the LLM to process. Note the
+    instructions in the system context for the LLM. This greatly improves the conversation
+    experience by allowing the LLM to understand who is speaking in a multi-party call.
+
+    If you do not wish to use diarization, then set the `enable_speaker_diarization` parameter
+    to `False` or omit it altogether. The `text_format` will only be used if diarization is enabled.
+
+    By default, this example will use our ENHANCED operating point, which is optimized for
+    high accuracy. You can change this by setting the `operating_point` parameter to a different
+    value.
+
+    For more information on operating points, see the Speechmatics documentation:
+    https://docs.speechmatics.com/rt-api-ref
+    """
+    logger.info(f"Starting bot")
+
+    stt = SpeechmaticsSTTService(
+        api_key=os.getenv("SPEECHMATICS_API_KEY"),
+        language=Language.EN,
+        enable_speaker_diarization=True,
+        text_format="<{speaker_id}>{text}</{speaker_id}>",
+    )
+
+    tts = ElevenLabsTTSService(
+        api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+        voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+        model="eleven_turbo_v2_5",
+    )
+
+    llm = OpenAILLMService(
+        api_key=os.getenv("OPENAI_API_KEY"),
+        params=BaseOpenAILLMService.InputParams(temperature=0.75),
+    )
+
+    messages = [
+        {
+            "role": "system",
+            "content": (
+                "You are a helpful British assistant called Alfred. "
+                "Your goal is to demonstrate your capabilities in a succinct way. "
+                "Your output will be converted to audio so don't include special characters in your answers. "
+                "Always include punctuation in your responses. "
+                "Give very short replies - do not give longer replies unless strictly necessary. "
+                "Respond to what the user said in a concise, funny, creative and helpful way. "
+                "Use `<Sn/>` tags to identify different speakers - do not use tags in your replies."
+            ),
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(
+        context,
+        user_params=LLMUserAggregatorParams(aggregation_timeout=0.005),
+    )
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,  # STT
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Say a short hello to the user."})
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/foundational/07aa-interruptible-soniox.py

@@ -0,0 +1,109 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.services.soniox.stt import SonioxSTTService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    logger.info(f"Starting bot")
+
+    stt = SonioxSTTService(
+        api_key=os.getenv("SONIOX_API_KEY"),
+    )
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/foundational/07b-interruptible-langchain.py

@@ -113,10 +113,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07c-interruptible-deepgram-vad.py

@@ -87,10 +87,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07c-interruptible-deepgram.py

@@ -81,10 +81,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07d-interruptible-elevenlabs-http.py

@@ -35,7 +35,7 @@ transport_params = {
         audio_out_enabled=True,
         vad_analyzer=SileroVADAnalyzer(),
     ),
-    "twilio": lambda: TransportParams(
+    "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         vad_analyzer=SileroVADAnalyzer(),
@@ -88,10 +88,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
         )
 

examples/foundational/07d-interruptible-elevenlabs.py

@@ -84,10 +84,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07e-interruptible-playht-http.py

@@ -84,10 +84,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07e-interruptible-playht.py

@@ -86,10 +86,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07f-interruptible-azure.py

@@ -90,10 +90,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07g-interruptible-openai.py

@@ -84,11 +84,9 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             audio_out_sample_rate=24000,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07h-interruptible-openpipe.py

@@ -89,10 +89,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07i-interruptible-xtts.py

@@ -87,10 +87,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
         )
 

examples/foundational/07j-interruptible-gladia.py

@@ -92,10 +92,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07k-interruptible-lmnt.py

@@ -80,10 +80,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07l-interruptible-groq.py

@@ -85,7 +85,6 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/foundational/07m-interruptible-aws.py

@@ -87,10 +87,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07n-interruptible-google.py

@@ -61,7 +61,12 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
     )
 
-    llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
+    llm = GoogleLLMService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        model="gemini-2.5-flash",
+        # turn on thinking if you want it
+        # params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),)
+    )
 
     messages = [
         {
@@ -88,10 +93,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07o-interruptible-assemblyai.py

@@ -86,10 +86,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07p-interruptible-krisp.py

@@ -84,10 +84,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07q-interruptible-rime-http.py

@@ -89,10 +89,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
         )
 

examples/foundational/07q-interruptible-rime.py

@@ -83,10 +83,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07r-interruptible-riva-nim.py

@@ -80,10 +80,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07s-interruptible-google-audio-in.py

@@ -8,8 +8,8 @@ import argparse
 import os
 from dataclasses import dataclass
 
-import google.ai.generativelanguage as glm
 from dotenv import load_dotenv
+from google.genai.types import Content, Part
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
@@ -164,9 +164,7 @@ class TanscriptionContextFixup(FrameProcessor):
             and last_part.inline_data
             and last_part.inline_data.mime_type == "audio/wav"
         ):
-            self._context.messages[-2] = glm.Content(
-                role="user", parts=[glm.Part(text=self._transcript)]
-            )
+            self._context.messages[-2] = Content(role="user", parts=[Part(text=self._transcript)])
 
     def add_transcript_back_to_inference_output(self):
         if not self._transcript:
@@ -216,7 +214,12 @@ transport_params = {
 async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
     logger.info(f"Starting bot")
 
-    llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
+    llm = GoogleLLMService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        model="gemini-2.5-flash",
+        # turn on thinking if you want it
+        # params=GoogleLLMService.InputParams(extra={"thinking_config": {"thinking_budget": 4096}}),
+    )
 
     tts = GoogleTTSService(
         voice_id="en-US-Chirp3-HD-Charon",
@@ -258,7 +261,6 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/foundational/07t-interruptible-fish.py

@@ -84,10 +84,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07u-interruptible-ultravox.py

@@ -77,8 +77,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
+            enable_usage_metrics=True,
         ),
     )
 

examples/foundational/07v-interruptible-neuphonic-http.py

@@ -7,6 +7,7 @@
 import argparse
 import os
 
+import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
@@ -50,62 +51,63 @@ transport_params = {
 async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
     logger.info(f"Starting bot")
 
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+    # Create an HTTP session
+    async with aiohttp.ClientSession() as session:
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
-    tts = NeuphonicHttpTTSService(
-        api_key=os.getenv("NEUPHONIC_API_KEY"),
-        voice_id="fc854436-2dac-4d21-aa69-ae17b54e98eb",  # Emily
-    )
+        tts = NeuphonicHttpTTSService(
+            api_key=os.getenv("NEUPHONIC_API_KEY"),
+            voice_id="fc854436-2dac-4d21-aa69-ae17b54e98eb",  # Emily
+            aiohttp_session=session,
+        )
 
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
 
-    messages = [
-        {
-            "role": "system",
-            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
-        },
-    ]
-
-    context = OpenAILLMContext(messages)
-    context_aggregator = llm.create_context_aggregator(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            stt,
-            context_aggregator.user(),  # User responses
-            llm,  # LLM
-            tts,  # TTS
-            transport.output(),  # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
         ]
-    )
 
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
-        ),
-    )
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
 
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        # Kick off the conversation.
-        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
 
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info(f"Client disconnected")
-        await task.cancel()
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                enable_metrics=True,
+                enable_usage_metrics=True,
+            ),
+        )
 
-    runner = PipelineRunner(handle_sigint=handle_sigint)
+        @transport.event_handler("on_client_connected")
+        async def on_client_connected(transport, client):
+            logger.info(f"Client connected")
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
 
-    await runner.run(task)
+        @transport.event_handler("on_client_disconnected")
+        async def on_client_disconnected(transport, client):
+            logger.info(f"Client disconnected")
+            await task.cancel()
+
+        runner = PipelineRunner(handle_sigint=handle_sigint)
+
+        await runner.run(task)
 
 
 if __name__ == "__main__":

examples/foundational/07v-interruptible-neuphonic.py

@@ -83,10 +83,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07w-interruptible-fal.py

@@ -86,10 +86,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07x-interruptible-local.py

@@ -70,10 +70,8 @@ async def main():
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/07y-interruptible-minimax.py

@@ -90,10 +90,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
         )
 

examples/foundational/07z-interruptible-sarvam.py

@@ -89,10 +89,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
             ),
         )
 

examples/foundational/10-wake-phrase.py

@@ -85,7 +85,13 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         ]
     )
 
-    task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):

examples/foundational/12a-describe-video-gemini-flash.py

@@ -101,7 +101,10 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
 
     task = PipelineTask(
         pipeline,
-        params=PipelineParams(allow_interruptions=True),
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
     )
 
     @transport.event_handler("on_client_connected")

examples/foundational/12b-describe-video-gpt-4o.py

@@ -101,7 +101,10 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
 
     task = PipelineTask(
         pipeline,
-        params=PipelineParams(allow_interruptions=True),
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
     )
 
     @transport.event_handler("on_client_connected")

examples/foundational/12c-describe-video-anthropic.py

@@ -101,7 +101,10 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
 
     task = PipelineTask(
         pipeline,
-        params=PipelineParams(allow_interruptions=True),
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
     )
 
     @transport.event_handler("on_client_connected")

examples/foundational/13e-whisper-mlx.py

@@ -84,7 +84,7 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         pipeline,
         params=PipelineParams(
             enable_metrics=True,
-            report_only_initial_ttfb=False,
+            enable_usage_metrics=True,
         ),
     )
 

examples/foundational/13g-sambanova-transcription.py

@@ -0,0 +1,108 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+import time
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import Frame, TranscriptionFrame, UserStoppedSpeakingFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.sambanova.stt import SambaNovaSTTService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+
+STOP_SECS = 2.0
+
+
+class TranscriptionLogger(FrameProcessor):
+    """Measures transcription latency.
+
+    Uses the (intentionally) long STOP_SECS parameter to give the transcription time to finish,
+    then outputs the timing between when the VAD first classified audio input as not-speech and
+    the delivery of the last transcription frame.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._last_transcription_time = time.time()
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, UserStoppedSpeakingFrame):
+            logger.debug(
+                f"Transcription latency: {(STOP_SECS - (time.time() - self._last_transcription_time)):.2f}"
+            )
+
+        if isinstance(frame, TranscriptionFrame):
+            self._last_transcription_time = time.time()
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=STOP_SECS)),
+    ),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    logger.info(f"Starting bot")
+
+    stt = SambaNovaSTTService(
+        model="Whisper-Large-v3",
+        api_key=os.getenv("SAMBANOVA_API_KEY"),
+    )
+
+    tl = TranscriptionLogger()
+
+    pipeline = Pipeline([transport.input(), stt, tl])
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/foundational/13h-speechmatics-transcription.py

@@ -0,0 +1,89 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import Frame, TranscriptionFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.speechmatics.stt import SpeechmaticsSTTService
+from pipecat.transcriptions.language import Language
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+
+class TranscriptionLogger(FrameProcessor):
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, TranscriptionFrame):
+            print(f"Transcription: {frame.text}")
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+transport_params = {
+    "daily": lambda: DailyParams(audio_in_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_in_enabled=True),
+    "webrtc": lambda: TransportParams(audio_in_enabled=True),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    """Run example using Speechmatics STT.
+
+    This example will use diarization within our STT service and output the words spoken by
+    each individual speaker and wrap them with XML tags.
+
+    If you do not wish to use diarization, then set the `enable_speaker_diarization` parameter
+    to `False` or omit it altogether. The `text_format` will only be used if diarization is enabled.
+
+    By default, this example will use our ENHANCED operating point, which is optimized for
+    high accuracy. You can change this by setting the `operating_point` parameter to a different
+    value.
+
+    For more information on operating points, see the Speechmatics documentation:
+    https://docs.speechmatics.com/rt-api-ref
+    """
+    logger.info(f"Starting bot")
+
+    stt = SpeechmaticsSTTService(
+        api_key=os.getenv("SPEECHMATICS_API_KEY"),
+        language=Language.EN,
+        enable_speaker_diarization=True,
+        text_format="<{speaker_id}>{text}</{speaker_id}>",
+    )
+
+    tl = TranscriptionLogger()
+
+    pipeline = Pipeline([transport.input(), stt, tl])
+
+    task = PipelineTask(pipeline)
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/foundational/13i-soniox-transcription.py

@@ -0,0 +1,81 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import Frame, TranscriptionFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.soniox.stt import SonioxSTTService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
+
+load_dotenv(override=True)
+
+
+class TranscriptionLogger(FrameProcessor):
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, TranscriptionFrame):
+            print(f"Transcription: {frame.text}")
+
+
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        vad_analyzer=SileroVADAnalyzer(),
+    ),
+}
+
+
+async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    logger.info(f"Starting bot")
+
+    stt = SonioxSTTService(
+        api_key=os.getenv("SONIOX_API_KEY"),
+    )
+
+    tl = TranscriptionLogger()
+
+    pipeline = Pipeline([transport.input(), stt, tl])
+
+    task = PipelineTask(pipeline)
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+
+    @transport.event_handler("on_client_closed")
+    async def on_client_closed(transport, client):
+        logger.info(f"Client closed connection")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=False)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.examples.run import main
+
+    main(run_example, transport_params=transport_params)

examples/foundational/14-function-calling.py

@@ -134,10 +134,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
         ),
     )
 

examples/foundational/14a-function-calling-anthropic.py

@@ -127,8 +127,8 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
+            enable_usage_metrics=True,
         ),
     )
 

examples/foundational/14b-function-calling-anthropic-video.py

@@ -172,8 +172,8 @@ If you need to use a tool, simply use the tool. Do not tell the user the tool yo
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
+            enable_usage_metrics=True,
         ),
     )
 

examples/foundational/14c-function-calling-together.py

@@ -16,7 +16,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -116,7 +116,13 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         ]
     )
 
-    task = PipelineTask(pipeline)
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):

examples/foundational/14d-function-calling-video.py

@@ -17,7 +17,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.examples.run import get_transport_client_id, maybe_capture_participant_camera
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -158,7 +158,13 @@ indicate you should use the get_image tool are:
         ]
     )
 
-    task = PipelineTask(pipeline)
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):

examples/foundational/14e-function-calling-google.py

@@ -183,7 +183,6 @@ indicate you should use the get_image tool are:
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/foundational/14f-function-calling-groq.py

@@ -121,7 +121,6 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),

examples/foundational/14g-function-calling-grok.py

@@ -111,7 +111,6 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     task = PipelineTask(
         pipeline,
         params=PipelineParams(
-            allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,
         ),