Revert LLMRunFrame for quickstart

.github/workflows/publish.yaml

@@ -5,25 +5,25 @@ on:
     inputs:
       gitref:
         type: string
-        description: 'what git tag to build (e.g. v0.0.74)'
+        description: "what git tag to build (e.g. v0.0.74)"
         required: true
 
 jobs:
   build:
-    name: 'Build and upload wheels'
+    name: "Build and upload wheels"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
         with:
           ref: ${{ github.event.inputs.gitref }}
-
+      
       - name: Install uv
         uses: astral-sh/setup-uv@v3
         with:
-          version: 'latest'
+          version: "latest"
       - name: Set up Python
-        run: uv python install 3.12
+        run: uv python install 3.10
       - name: Install development dependencies
         run: uv sync --group dev
       - name: Build project
@@ -35,9 +35,9 @@ jobs:
           path: ./dist
 
   publish-to-pypi:
-    name: 'Publish to PyPI'
+    name: "Publish to PyPI"
     runs-on: ubuntu-latest
-    needs: [build]
+    needs: [ build ]
     environment:
       name: pypi
       url: https://pypi.org/p/pipecat-ai
@@ -56,12 +56,12 @@ jobs:
           print-hash: true
 
   publish-to-test-pypi:
-    name: 'Publish to Test PyPI'
+    name: "Publish to Test PyPI"
     runs-on: ubuntu-latest
-    needs: [build]
+    needs: [ build ]
     environment:
       name: testpypi
-      url: https://test.pypi.org/p/pipecat-ai
+      url: https://pypi.org/p/pipecat-ai
     permissions:
       id-token: write
     steps:
@@ -70,7 +70,7 @@ jobs:
         with:
           name: wheels
           path: ./dist
-      - name: Publish to Test PyPI
+      - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           verbose: true

.github/workflows/publish_test.yaml

@@ -4,7 +4,7 @@ on: workflow_dispatch
 
 jobs:
   build:
-    name: 'Build and upload wheels'
+    name: "Build and upload wheels"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
@@ -15,9 +15,9 @@ jobs:
       - name: Install uv
         uses: astral-sh/setup-uv@v3
         with:
-          version: 'latest'
+          version: "latest"
       - name: Set up Python
-        run: uv python install 3.12
+        run: uv python install 3.10
       - name: Install development dependencies
         run: uv sync --group dev
       - name: Build project
@@ -29,12 +29,12 @@ jobs:
           path: ./dist
 
   publish-to-test-pypi:
-    name: 'Publish to Test PyPI'
+    name: "Publish to Test PyPI"
     runs-on: ubuntu-latest
     needs: [build]
     environment:
       name: testpypi
-      url: https://test.pypi.org/p/pipecat-ai
+      url: https://pypi.org/p/pipecat-ai
     permissions:
       id-token: write
     steps:
@@ -43,7 +43,7 @@ jobs:
         with:
           name: wheels
           path: ./dist
-      - name: Publish to Test PyPI
+      - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           verbose: true

CHANGELOG.md

@@ -7,507 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
-### Added
+## Added
-
-- The runner `--folder` argument now supports downloading files from
-  subdirectories.
-
-### Fixed
-
-- Fixed an issue where `RimeHttpTTSService` and `PiperTTSService` could generate
-  incorrectly 16-bit aligned audio frames, potentially leading to internal
-  errors or static audio.
-
-## [0.0.90] - 2025-10-10
-
-### Added
-
-- Added audio filter `KrispVivaFilter` using the Krisp VIVA SDK.
-
-- Added `--folder` argument to the runner, allowing files saved in that folder
-  to be downloaded from `http://HOST:PORT/file/FILE`.
-
-- Added `GeminiLiveVertexLLMService`, for accessing Gemini Live via Google
-  Vertex AI.
-
-- Added some new configuration options to `GeminiLiveLLMService`:
-
-  - `thinking`
-  - `enable_affective_dialog`
-  - `proactivity`
-
-  Note that these new configuration options require using a newer model than
-  the default, like "gemini-2.5-flash-native-audio-preview-09-2025". The last
-  two require specifying `http_options=HttpOptions(api_version="v1alpha")`.
-
-- Added `on_pipeline_error` event to `PipelineTask`. This event will get fired
-  when an `ErrorFrame` is pushed (use `FrameProcessor.push_error()`).
-
-  ```python
-  @task.event_handler("on_pipeline_error")
-  async def on_pipeline_error(task: PipelineTask, frame: ErrorFrame):
-      ...
-  ```
-
-- Added a `service_tier` `InputParam` to the `BaseOpenAILLMService`. This
-  parameter can influence the latency of the response. For example `"priority"`
-  will result in faster completions, but in exchange for a higher price.
-
-### Changed
-
-- Updated `GeminiLiveLLMService` to use the `google-genai` library rather than
-  use WebSockets directly.
-
-### Deprecated
-
-- `LivekitFrameSerializer` is now deprecated. Use `LiveKitTransport` instead.
-
-- `pipecat.service.openai_realtime` is now deprecated, use
-  `pipecat.services.openai.realtime` instead or
-  `pipecat.services.azure.realtime` for Azure Realtime.
-
-- `pipecat.service.aws_nova_sonic` is now deprecated, use
-  `pipecat.services.aws.nova_sonic` instead.
-
-- `GeminiMultimodalLiveLLMService` is now deprecated, use
-  `GeminiLiveLLMService`.
-
-### Fixed
-
-- Fixed a `GoogleVertexLLMService` issue that would generate an error if no
-  token information was returned.
-
-- `GeminiLiveLLMService` will now end gracefully (i.e. after the bot has
-  finished) upon receiving an `EndFrame`.
-
-- `GeminiLiveLLMService` will try to seamlessly reconnect when it loses its
-  connection.
-
-## [0.0.89] - 2025-10-07
-
-### Fixed
-
-- Reverted a change introduced in 0.0.88 that was causing pipelines to be frozen
-  when using interruption strategies and processors that block interruption
-  frames (e.g. `STTMuteFilter`).
-
-## [0.0.88] - 2025-10-07
-
-### Added
-
-- Added support for Nano Banana models to `GoogleLLMService`. For example, you
-  can now use the `gemini-2.5-flash-image` model to generate images.
-
-- Added `HumeTTSService` for text-to-speech synthesis using Hume AI's expressive
-  voice models. Provides high-quality, emotionally expressive speech synthesis
-  with support for various voice models. Includes example in
-  `examples/foundational/07ad-interruptible-hume.py`. Use with:
-  `uv pip install pipecat-ai[hume]`.
-
-### Changed
-
-- Updated default `GoogleLLMService` model to `gemini-2.5-flash`.
-
-### Deprecated
-
-- PlayHT is shutting down their API on December 31st, 2025. As a result,
-  `PlayHTTTSService` and `PlayHTHttpTTSService` are deprecated and will be
-  removed in a future version.
-
-### Fixed
-
-- Fixed an issue with `AWSNovaSonicLLMService` where the client wouldn't
-  connect due to a breaking change in the AWS dependency chain.
-
-- `PermissionError` is now caught if NLTK's `punkt_tab` can't be downloaded.
-
-- Fixed an issue that would cause wrong user/assistant context ordering when
-  using interruption strategies.
-
-- Fixed RTVI incoming message handling, broken in 0.0.87.
-
-## [0.0.87] - 2025-10-02
-
-### Added
-
-- Added `WebsocketSTTService` base class for websocket-based STT services.
-  Combines STT functionality with websocket connectivity, providing automatic
-  error handling and reconnection capabilities with exponential backoff.
-
-- Added `DeepgramFluxSTTService` for real-time speech recognition using
-  Deepgram's Flux WebSocket API. Flux understands conversational flow and
-  automatically handles turn-taking.
-
-- Added RTVI messages for user/bot audio levels and system logs.
-
-- Include OpenAI-based LLM services cached tokens to `MetricsFrame`.
-
-### Changed
-
-- Updated the default model for `AnthropicLLMService` to
-  `claude-sonnet-4-5-20250929`.
-
-### Deprecated
-
-- `DailyTransportMessageFrame` and `DailyTransportMessageUrgentFrame` are
-  deprecated, use `DailyOutputTransportMessageFrame` and
-  `DailyOutputTransportMessageUrgentFrame` respectively instead.
-
-- `LiveKitTransportMessageFrame` and `LiveKitTransportMessageUrgentFrame` are
-  deprecated, use `LiveKitOutputTransportMessageFrame` and
-  `LiveKitOutputTransportMessageUrgentFrame` respectively instead.
-
-- `TransportMessageFrame` and `TransportMessageUrgentFrame` are deprecated, use
-  `OutputTransportMessageFrame` and `OutputTransportMessageUrgentFrame`
-  respectively instead.
-
-- `InputTransportMessageUrgentFrame` is deprecated, use
-  `InputTransportMessageFrame` instead.
-
-- `DailyUpdateRemoteParticipantsFrame` is deprecated and will be removed in a
-  future version. Instead, create your own custom frame and handle it in the
-  `@transport.output().event_handler("on_after_push_frame")` event handler or a
-  custom processor.
-
-## Fixed
-
-- Fixed an issue in `AWSBedrockLLMService` where timeout exceptions weren't
-  being detected.
-
-- Fixed a `PipelineTask` issue that could prevent the application to exit if
-  `task.cancel()` was called when the task was already finished.
-
-- Fixed an issue where local SmartTurn was not being ran in a separate thread.
-
-## [0.0.86] - 2025-09-24
-
-### Added
-
-- Added `HeyGenTransport`. This is an integration for HeyGen Interactive
-  Avatar. A video service that handles audio streaming and requests HeyGen to
-  generate avatar video responses. (see https://www.heygen.com/). When used, the
-  Pipecat bot joins the same virtual room as the HeyGen Avatar and the user.
-
-- Added support to `TwilioFrameSerializer` for `region` and `edge` settings.
-
-- Added support for using universal `LLMContext` with:
-
-  - `LLMLogObserver`
-  - `GatedLLMContextAggregator` (formerly `GatedOpenAILLMContextAggregator`)
-  - `LangchainProcessor`
-  - `Mem0MemoryService`
-
-- Added `StrandsAgentProcessor` which allows you to use the Strands Agents
-  framework to build your voice agents.
-  See https://strandsagents.com
-
-- Added `ElevenLabsSTTService` for speech-to-text transcription.
-
-- Added a peer connection monitor to the `SmallWebRTCConnection` that
-  automatically disconnects if the connection fails to establish within
-  the timeout (1 minute by default).
-
-- Added memory cleanup improvements to reduce memory peaks.
-
-- Added `on_before_process_frame`, `on_after_process_frame`,
-  `on_before_push_frame` and `on_after_push_frame`. These are synchronous events
-  that get called before and after a frame is processed or pushed. Note that
-  these events are synchrnous so they should ideally perform lightweight tasks
-  in order to not block the pipeline. See
-  `examples/foundational/45-before-and-after-events.py`.
-
-- Added `on_before_leave` synchronous event to `DailyTransport`.
-
-- Added `on_before_disconnect` synchronous event to `LiveKitTransport`.
-
-- It is now possible to register synchronous event handlers. By default, all
-  event handlers are executed in a separate task. However, in some cases we want
-  to guarantee order of execution, for example, executing something before
-  disconnecting a transport.
-
-  ```python
-  self._register_event_handler("on_event_name", sync=True)
-  ```
-
-- Added support for global location in `GoogleVertexLLMService`. The service now
-  supports both regional locations (e.g., "us-east4") and the "global" location
-  for Vertex AI endpoints. When using "global" location, the service will use
-  `aiplatform.googleapis.com` as the API host instead of the regional format.
-
-- Added `on_pipeline_finished` event to `PipelineTask`. This event will get
-  fired when the pipeline is done running. This can be the result of a
-  `StopFrame`, `CancelFrame` or `EndFrame`.
-
-  ```python
-  @task.event_handler("on_pipeline_finished")
-  async def on_pipeline_finished(task: PipelineTask, frame: Frame):
-      ...
-  ```
-
-- Added support for new RTVI `send-text` event, along with the ability to toggle
-  the audio response off (skip tts) while handling the new context.
-
-### Changed
-
-- Updated `aiortc` to 1.13.0.
-
-- Updated `sentry` to 2.38.0.
-
-- `BaseOutputTransport` methods `write_audio_frame` and `write_video_frame` now
-  return a boolean to indicate if the transport implementation was able to write
-  the given frame or not.
-
-- Updated Silero VAD model to v6.
-
-- Updated `livekit` to 1.0.13.
-
-- `torch` and `torchaudio` are no longer required for running Smart Turn
-  locally. This avoids gigabytes of dependencies being installed.
-
-- Updated `websockets` dependency to support version 15.0. Removed deprecated
-  usage of `ConnectionClosed.code` and `ConnectionClosed.reason` attributes in
-  `AWSTranscribeSTTService` for compatibility.
-
-- Refactored `pyproject.toml` to reduce websockets dependency repetition using
-  self-referencing extras. All websockets-dependent services now reference a
-  shared `websockets-base` extra.
-
-### Deprecated
-
-- `GladiaSTTService`'s `confidence` arg is deprecated. `confidence` is no
-  longer needed to determine which transcription or translation frames to
-  emit.
-
-- `PipelineTask` events `on_pipeline_stopped`, `on_pipeline_ended` and
-  `on_pipeline_cancelled` are now deprecated. Use `on_pipeline_finished`
-  instead.
-
-- Support for the RTVI `append-to-context` event, in lieu of the new `send-text`
-  event and making way for future events like `send-image`.
-
-### Fixed
-
-- Fixed an issue where the pipeline could freeze if a task cancellation never
-  completed because a third-party library swallowed asyncio.CancelledError. We
-  now apply a timeout to task cancellations to prevent these freezes. If the
-  timeout is reached, the system logs warnings and leaves dangling tasks behind,
-  which can help diagnose where cancellation is being blocked.
-
-- Fixed an `AudioBufferProcessor` issues that was causing user audio to be
-  missing in stereo recordings causing bot and user overlaps.
-
-- Fixed a `BaseOutputTransport` issue that could produce large saved
-  `AudioBufferProcessor` files when using an audio mixer.
-
-- Fixed a `PipelineRunner` issue on Windows where setting up SIGINT and SIGTERM
-  was raising an exception.
-
-- Fixed an issue where multiple handlers for an event would not run in parallel.
-
-- Fixed `DailyTransport.sip_call_transfer()` to automatically use the session
-  ID from the `on_dialin_connected` event, when not explicitly provided. Now
-  supports cold transfers (from incoming dial-in calls) by automatically
-  tracking session IDs from connection events.
-
-- Fixed a memory leak in `SmallWebRTCTransport`. In `aiortc`, when you receive
-  a `MediaStreamTrack` (audio or video), frames are produced asynchronously. If
-  the code never consumes these frames, they are queued in memory, causing a
-  memory leak.
-
-- Fixed an issue in `AsyncAITTSService`, where `TTSTextFrames` were not being
-  pushed.
-
-- Fixed an issue that would cause `push_interruption_task_frame_and_wait()` to
-  not wait if a previous interruption had already happened.
-
-- Fixed a couple of bugs in `ServiceSwitcher`:
-
-  - Using multiple `ServiceSwitcher`s in a pipeline would result in an error.
-  - `ServiceSwitcherFrame`s (such as `ManuallySwitchServiceFrame`s) were having
-    an effect too early, essentially "jumping the queue" in terms of pipeline
-    frame ordering.
-
-- Fixed a self-cancellation deadlock in `UserIdleProcessor` when returning
-  `False` from an idle callback. The task now terminates naturally instead of
-  attempting to cancel itself.
-
-- Fixed an issue in `AudioBufferProcessor` where a recording is not created
-  when a bot speaks and user input is blocked.
-
-- Fixed a `FastAPIWebsocketTransport` and `SmallWebRTCTransport` issue where
-  `on_client_disconnected` would be triggered when the bot ends the
-  conversation. That is, `on_client_disconnected` should only be triggered when
-  the remote client actually disconnects.
-
-- Fixed an issue in `HeyGenVideoService` where the `BotStartedSpeakingFrame`
-  was blocked from moving through the Pipeline.
-
-## [0.0.85] - 2025-09-12
-
-### Added
-
-- `AzureSTTService` now pushes interim transcriptions.
-
-- Added `voice_cloning_key` to `GoogleTTSService` to support custom cloned
-  voices.
-
-- Added `speaking_rate` to `GoogleTTSService.InputParams` to control the
-  speaking rate.
-
-- Added a `speed` arg to `OpenAITTSService` to control the speed of the voice
-  response.
-
-- Added `FrameProcessor.push_interruption_task_frame_and_wait()`. Use this
-  method to programatically interrupt the bot from any part of the
-  pipeline. This guarantees that all the processors in the pipeline are
-  interrupted in order (from upstream to downstream). Internally, this works by
-  first pushing an `InterruptionTaskFrame` upstream until it reaches the
-  pipeline task. The pipeline task then generates an `InterruptionFrame`, which
-  flows downstream through all processors. Once the `InterruptionFrame` has
-  reaches the processor waiting for the interruption, the function returns and
-  execution continues after the call. Think of it as sending an upstream request
-  for interruption and waiting until the acknowledgment flows back downstream.
-
-- Added new base `TaskFrame` (which is a system frame). This is the base class
-  for all task frames (`EndTaskFrame`, `CancelTaskFrame`, etc.) that are meant
-  to be pushed upstream to reach the pipeline task.
-
-- Expanded support for universal `LLMContext` to the AWS Bedrock LLM service.
-  Using the universal `LLMContext` and associated `LLMContextAggregatorPair` is
-  a pre-requisite for using `LLMSwitcher` to switch between LLMs at runtime.
-
-- Added new fields to the development runner's `parse_telephony_websocket`
-  method in support of providing dynamic data to a bot.
-
-  - Twilio: Added a new `body` parameter, which parses the websocket message
-    for `customParameters`. Provide data via the `Parameter` nouns in your
-    TwiML to use this feature.
-  - Telnyx & Exotel: Both providers make the `to` and `from` phone numbers
-    available in the websocket messages. You can now access these numbers as
-    `call_data["to"]` and `call_data["from"]`.
-
-  Note: Each telephony provider offers different features. Refer to the
-  corresponding example in `pipecat-examples` to see how to pass custom data
-  to your bot.
-
-- Added `body` to the `WebsocketRunnerArguments` as an optional parameter.
-  Custom `body` information can be passed from the server into the bot file via
-  the `bot()` method using this new parameter.
-
-- Added video streaming support to `LiveKitTransport`.
-
-- Added `OpenAIRealtimeLLMService` and `AzureRealtimeLLMService` which provide
-  access to OpenAI Realtime.
-
-### Changed
-
-- `pipeline.tests.utils.run_test()` now allows passing `PipelineParams` instead
-  of individual parameters.
-
-### Removed
-
-- Remove `VisionImageRawFrame` in favor of context frames (`LLMContextFrame` or
-  `OpenAILLMContextFrame`).
-
-### Deprecated
-
-- `BotInterruptionFrame` is now deprecated, use `InterruptionTaskFrame` instead.
-
-- `StartInterruptionFrame` is now deprected, use `InterruptionFrame` instead.
-
-- Deprecate `VisionImageFrameAggregator` because `VisionImageRawFrame` has been
-  removed. See the `12*` examples for the new recommended replacement pattern.
-
-- `NoisereduceFilter` is now deprecated and will be removed in a future
-  version. Use other audio filters like `KrispFilter` or `AICFilter`.
-
-- Deprecated `OpenAIRealtimeBetaLLMService` and `AzureRealtimeBetaLLMService`.
-  Use `OpenAIRealtimeLLMService` and `AzureRealtimeLLMService`, respectively.
-  Each service will be removed in an upcoming version, 1.0.0.
-
-### Fixed
-
-- Fixed a `BaseOutputTransport` issue that caused incorrect detection of when
-  the bot stopped talking while using an audio mixer.
-
-- Fixed a `LiveKitTransport` issue where RTVI messages were not properly
-  encoded.
-
-- Add additional fixups to Mistral context messages to ensure they meet
-  Mistral-specific requirements, avoiding Mistral "invalid request" errors.
-
-- Fixed `DailyTransport` transcription handling to gracefully handle missing
-  `rawResponse` field in transcription messages, preventing KeyError crashes.
-
-## [0.0.84] - 2025-09-05
-
-### Added
-
-- Add the ability to send DTMF to `LiveKitTransport`.
-
-- Expanded support for universal `LLMContext` to the Anthropic LLM service.
-  Using the universal `LLMContext` and associated `LLMContextAggregatorPair` is
-  a pre-requisite for using `LLMSwitcher` to switch between LLMs at runtime.
-
-### Changed
-
-- Updated `daily-python` to 0.19.9.
-
-- Restored `DailyTransport`'s native DTMF support using Daily's `send_dtmf()`
-  method instead of generated audio tones.
-
-### Fixed
-
-- Fixed a `AWSBedrockLLMService` crash caused by an extra `await`.
-
-- Fixed a `OpenAIImageGenService` issue where it was not creating
-  `URLImageRawFrame` correctly.
-
-## [0.0.83] - 2025-09-03
-
-### Added
-
-- Added multilingual support for AsyncAI in `AsyncAITTSService` and `AsyncAIHttpTTSService`.
-
-  - New `languages`: `es`, `fr`, `de`, `it`.
-
-- Added new frames `InputTransportMessageUrgentFrame` and
-  `DailyInputTransportMessageUrgentFrame` for transport messages received from
-  external sources.
-
-- Added `UserSpeakingFrame`. This will be sent upstream and downstream while VAD
-  detects the user is speaking.
-
-- Expanded support for universal `LLMContext` to more LLM services. Using the
-  universal `LLMContext` and associated `LLMContextAggregatorPair` is a
-  pre-requisite for using `LLMSwitcher` to switch between LLMs at runtime.
-  Here are the newly-supported services:
-
-  - Azure
-  - Cerebras
-  - Deepseek
-  - Fireworks AI
-  - Google Vertex AI
-  - Grok
-  - Groq
-  - Mistral
-  - NVIDIA NIM
-  - Ollama
-  - OpenPipe
-  - OpenRouter
-  - Perplexity
-  - Qwen
-  - SambaNova
-  - Together.ai
-
-- Added support for WhatsApp User-initiated Calls.
-
-- Added new audio filter `AICFilter`, speech enhancement for improving VAD/STT
-  performance, no ONNX dependency.
-  See https://ai-coustics.com/sdk/
-
-- Added a timeout around cancel input tasks to prevent indefinite hangs when
-  cancellation is swallowed by third-party code.
 
 - Added `pipecat.extensions.ivr` for automated IVR system navigation with
   configurable goals and conversation handling. Supports DTMF input, verbal
@@ -542,34 +42,16 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   sending it through the transport. This makes sending DTMF generic across all
   output transports.
 
-- Added new config parameters to `GladiaSTTService`.
+- Added new config parameters to `GladiaSTTService`. 
   - PreProcessingConfig > `audio_enhancer` to enhance audio quality.
-  - CustomVocabularyItem > `pronunciations` and `language` to specify special
+  - CustomVocabularyItem > `pronunciations` and `language` to specify special pronunciations and in which language it will be pronounced.
-    pronunciations and in which language it will be pronounced.
 
-### Changed
+## Changed
-
-- `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` are also pushed
-  upstream.
-
-- `ParallelPipeline` now waits for `CancelFrame` to finish in all branches
-  before pushing it downstream.
-
-- Added `sip_codecs` to the `DailyRoomSipParams`.
-
-- Updated the `configure()` function in `pipecat.runner.daily` to include new
-  args to create SIP-enabled rooms. Additionally, added new args to control the
-  room and token expiration durations.
 
 - `pipecat.frames.frames.KeypadEntry` is deprecated and has been moved to
   `pipecat.audio.dtmf.types.KeypadEntry`.
 
-- Updated `RimeTTSService`'s flush_audio message to conform with Rime's official
+## Removed
-  API.
-
-- Updated the default model for `CerebrasLLMService` to GPT-OSS-120B.
-
-### Removed
 
 - Remove `StopInterruptionFrame`. This was a legacy frame that was not being
   used really anywhere and it didn't provide any useful meaning. It was only
@@ -581,41 +63,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 - Remove deprecated `DailyTransport.send_dtmf()`.
 
-### Deprecated
+## Deprecated
-
-- Transports have been re-organized.
-
-  ```
-  pipecat.transports.network.small_webrtc        -> pipecat.transports.smallwebrtc.transport
-  pipecat.transports.network.webrtc_connection   -> pipecat.transports.smallwebrtc.connection
-  pipecat.transports.network.websocket_client    -> pipecat.transports.websocket.client
-  pipecat.transports.network.websocket_server    -> pipecat.transports.websocket.server
-  pipecat.transports.network.fastapi_websocket   -> pipecat.transports.websocket.fastapi
-  pipecat.transports.services.daily              -> pipecat.transports.daily.transport
-  pipecat.transports.services.helpers.daily_rest -> pipecat.transports.daily.utils
-  pipecat.transports.services.livekit            -> pipecat.transports.livekit.transport
-  pipecat.transports.services.tavus              -> pipecat.transports.tavus.transport
-  ```
 
 - `pipecat.frames.frames.KeypadEntry` is deprecated use
   `pipecat.audio.dtmf.types.KeypadEntry` instead.
 
-### Fixed
+## Fixed
-
-- Fixed an issue where messages received from the transport were always being resent.
-
-- Fixed `SmallWebRTCTransport` to not use `mid` to decide if the transceiver should
-  be `sendrecv` or not.
-
-- Fixed an issue where Deepgram swallowed `asyncio.CancelledError` during
-  disconnect, preventing tasks from being cancelled.
 
 - Fixed an issue where `PipelineTask` was not cleaning up the observers.
 
-### Performance
-
-- Reduced latency and improved memory performance in `Mem0MemoryService`.
-
 ## [0.0.82] - 2025-08-28
 
 ### Added
@@ -1500,7 +956,7 @@ quality and critical bugs impacting `ParallelPipelines` functionality.**
 - Added `session_token` parameter to `AWSNovaSonicLLMService`.
 
 - Added Gemini Multimodal Live File API for uploading, fetching, listing, and
-  deleting files. See `26f-gemini-live-files-api.py` for example usage.
+  deleting files. See `26f-gemini-multimodal-live-files-api.py` for example usage.
 
 ### Changed
 
@@ -3506,7 +2962,7 @@ stt = DeepgramSTTService(..., live_options=LiveOptions(model="nova-2-general"))
 - Added the new modalities option and helper function to set Gemini output
   modalities.
 
-- Added `examples/foundational/26d-gemini-live-text.py` which is
+- Added `examples/foundational/26d-gemini-multimodal-live-text.py` which is
   using Gemini as TEXT modality and using another TTS provider for TTS process.
 
 ### Changed
@@ -3693,9 +3149,9 @@ stt = DeepgramSTTService(..., live_options=LiveOptions(model="nova-2-general"))
 - Added new foundational examples for `GeminiMultimodalLiveLLMService`:
 
   - `26-gemini-multimodal-live.py`
-  - `26a-gemini-live-transcription.py`
+  - `26a-gemini-multimodal-live-transcription.py`
-  - `26b-gemini-live-video.py`
+  - `26b-gemini-multimodal-live-video.py`
-  - `26c-gemini-live-video.py`
+  - `26c-gemini-multimodal-live-video.py`
 
 - Added `SimliVideoService`. This is an integration for Simli AI avatars.
   (see https://www.simli.com)

COMMUNITY_INTEGRATIONS.md

@@ -1,336 +0,0 @@
-# Community Integrations Guide
-
-Pipecat welcomes community-maintained integrations! As our ecosystem grows, we've established a process for any developer to create and maintain their own service integrations while ensuring discoverability for the Pipecat community.
-
-## Overview
-
-**What we support:** Community-maintained integrations that live in separate repositories and are maintained by their authors.
-
-**What we don't do:** The Pipecat team does not code review, test, or maintain community integrations. We provide guidance and list approved integrations for discoverability.
-
-**Why this approach:** This allows the community to move quickly while keeping the Pipecat core team focused on maintaining the framework itself.
-
-## Submitting your Integration
-
-To be listed as an official community integration, follow these steps:
-
-### Step 1: Build Your Integration
-
-Create your integration following the patterns and examples shown in the "Integration Patterns and Examples" section below.
-
-### Step 2: Set Up Your Repository
-
-Your repository must contain these components:
-
-- **Source code** - Complete implementation following Pipecat patterns
-- **Foundational example** - Single file example showing basic usage (see [Pipecat examples](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational))
-- **README.md** - Must include:
-
-  - Introduction and explanation of your integration
-  - Installation instructions
-  - Usage instructions with Pipecat Pipeline
-  - How to run your example
-  - Pipecat version compatibility (e.g., "Tested with Pipecat v0.0.86")
-  - Company attribution: If you work for the company providing the service, please mention this in your README. This helps build confidence that the integration will be actively maintained.
-
-- **LICENSE** - Permissive license (BSD-2 like Pipecat, or equivalent open source terms)
-- **Code documentation** - Source code with docstrings (we recommend following [Pipecat's docstring conventions](https://github.com/pipecat-ai/pipecat/blob/main/CONTRIBUTING.md#docstring-conventions))
-- **Changelog** - Maintain a changelog for version updates
-
-### Step 3: Join Discord
-
-Join our Discord: https://discord.gg/pipecat
-
-### Step 4: Submit for Listing
-
-Submit a pull request to add your integration to our [Community Integrations documentation page](https://docs.pipecat.ai/server/services/community-integrations).
-
-**To submit:**
-
-1. Fork the [Pipecat docs repository](https://github.com/pipecat-ai/docs)
-2. Edit the file `server/services/community-integrations.mdx`
-3. Add your integration to the appropriate service category table with:
-   - Service name
-   - Link to your repository
-   - Maintainer GitHub username(s)
-4. Include a link to your demo video (approx 30-60 seconds) in your PR description showing:
-   - Core functionality of your integration
-   - Handling of an interruption (if applicable to service type)
-5. Submit your pull request
-
-Once your PR is submitted, post in the `#community-integrations` Discord channel to let us know.
-
-## Integration Patterns and Examples
-
-### STT (Speech-to-Text) Services
-
-#### Websocket-based Services
-
-**Base class:** `STTService`
-
-**Examples:**
-
-- [DeepgramSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/deepgram/stt.py)
-- [SpeechmaticsSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/speechmatics/stt.py)
-
-#### File-based Services
-
-**Base class:** `SegmentedSTTService`
-
-**Examples:**
-
-- [RivaSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/riva/stt.py)
-- [FalSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/fal/stt.py)
-
-#### Key requirements:
-
-- STT services should push `InterimTranscriptionFrames` and `TranscriptionFrames`
-- If confidence values are available, filter for values >50% confidence
-
-### LLM (Large Language Model) Services
-
-#### OpenAI-Compatible Services
-
-**Base class:** `OpenAILLMService`
-
-**Examples:**
-
-- [AzureLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/azure/llm.py)
-- [GrokLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/grok/llm.py) - Shows overriding the base class where needed
-
-#### Non-OpenAI Compatible Services
-
-**Requires:** Full implementation
-
-**Examples:**
-
-- [AnthropicLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/anthropic/llm.py)
-- [GoogleLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/llm.py)
-
-#### Key requirements:
-
-- **Frame sequence:** Output must follow this frame sequence pattern:
-
-  - `LLMFullResponseStartFrame` - Signals the start of an LLM response
-  - `LLMTextFrame` - Contains LLM content, typically streamed as tokens
-  - `LLMFullResponseEndFrame` - Signals the end of an LLM response
-
-- **Context aggregation:** Implement context aggregation to collect user and assistant content:
-  - Aggregators come in pairs with a `user()` instance and `assistant()` instance
-  - Context must adhere to the `LLMContext` universal format
-  - Aggregators should handle adding messages, function calls, and images to the context
-
-### TTS (Text-to-Speech) Services
-
-#### AudioContextWordTTSService
-
-**Use for:** Websocket-based services supporting word/timestamp alignment
-
-**Example:**
-
-- [CartesiaTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/cartesia/tts.py)
-
-#### InterruptibleTTSService
-
-**Use for:** Websocket-based services without word/timestamp alignment, requiring disconnection on interruption
-
-**Example:**
-
-- [SarvamTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/sarvam/tts.py)
-
-#### WordTTSService
-
-**Use for:** HTTP-based services supporting word/timestamp alignment
-
-**Example:**
-
-- [ElevenLabsHttpTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/elevenlabs/tts.py)
-
-#### TTSService
-
-**Use for:** HTTP-based services without word/timestamp alignment
-
-**Example:**
-
-- [GoogleHttpTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/tts.py)
-
-#### Key requirements:
-
-- For websocket services, use asyncio WebSocket implementation (required for v13+ support)
-- Handle idle service timeouts with keepalives
-- TTSServices push both audio (`TTSRawAudioFrame`) and text (`TTSTextFrame`) frames
-
-### Telephony Serializers
-
-Pipecat supports telephony provider integration using websocket connections to exchange MediaStreams. These services use a FrameSerializer to serialize and deserialize inputs from the FastAPIWebsocketTransport.
-
-**Examples:**
-
-- [Twilio](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/serializers/twilio.py)
-- [Telnyx](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/serializers/telnyx.py)
-
-#### Key requirements:
-
-- Include hang-up functionality using the provider's native API, ideally using `aiohttp`
-- Support DTMF (dual-tone multi-frequency) events if the provider supports them:
-  - Deserialize DTMF events from the provider's protocol to `InputDTMFFrame`
-  - Use `KeypadEntry` enum for valid keypad entries (0-9, \*, #, A-D)
-  - Handle invalid DTMF digits gracefully by returning `None`
-
-### Image Generation Services
-
-**Base class:** `ImageGenService`
-
-**Examples:**
-
-- [FalImageGenService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/fal/image.py)
-- [GoogleImageGenService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/image.py)
-
-#### Key requirements:
-
-- Must implement `run_image_gen` method returning an `AsyncGenerator`
-
-### Vision Services
-
-Vision services process images and provide analysis such as descriptions, object detection, or visual question answering.
-
-**Base class:** `VisionService`
-
-**Example:**
-
-- [MoondreamVisionService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/moondream/vision.py)
-
-#### Key requirements:
-
-- Must implement `run_vision` method that takes an `LLMContext` and returns an `AsyncGenerator[Frame, None]`
-- The method processes the latest image in the context and yields frames with analysis results
-- Typically yields `TextFrame` objects containing descriptions or answers
-
-## Implementation Guidelines
-
-### Naming Conventions
-
-- **STT:** `VendorSTTService`
-- **LLM:** `VendorLLMService`
-- **TTS:**
-  - Websocket: `VendorTTSService`
-  - HTTP: `VendorHttpTTSService`
-- **Image:** `VendorImageGenService`
-- **Vision:** `VendorVisionService`
-- **Telephony:** `VendorFrameSerializer`
-
-### Metrics Support
-
-Enable metrics in your service:
-
-```python
-def can_generate_metrics(self) -> bool:
-    """Check if this service can generate processing metrics.
-
-    Returns:
-        True, as this service supports metrics.
-    """
-    return True
-```
-
-### Dynamic Settings Updates
-
-STT, LLM, and TTS services support `ServiceUpdateSettingsFrame` for dynamic configuration changes. The base STTService has an `_update_settings()` method that handles settings, and the private `_settings` `Dict` is used to store settings and provide access to the subclass.
-
-```python
-async def set_language(self, language: Language):
-    """Set the recognition language and reconnect.
-
-    Args:
-        language: The language to use for speech recognition.
-    """
-    logger.info(f"Switching STT language to: [{language}]")
-    self._settings["language"] = language
-    await self._disconnect()
-    await self._connect()
-```
-
-Note that, in this example, Deepgram requires the websocket connection be disconnected and reconnected to reinitialize the service with the new value. Consider if your service requires reconnection.
-
-### Sample Rate Handling
-
-Sample rates are set via PipelineParams and passed to each frame processor at initialization. The pattern is to _not_ set the sample rate value in the constructor of a given service. Instead, use the `start()` method to initialize sample rates from the frame:
-
-```python
-async def start(self, frame: StartFrame):
-    """Start the service."""
-    await super().start(frame)
-    self._settings["output_format"]["sample_rate"] = self.sample_rate
-    await self._connect()
-```
-
-Note that `self.sample_rate` is a `@property` set in the TTSService base class, which provides access to the private sample rate value obtained from the StartFrame.
-
-### Tracing Decorators
-
-Use Pipecat's tracing decorators:
-
-- **STT:** `@traced_stt` - decorate a function that handles `transcript`, `is_final`, `language` as args
-- **LLM:** `@traced_llm` - decorate the `_process_context()` method
-- **TTS:** `@traced_tts` - decorate the `run_tts()` method
-
-## Best Practices
-
-### Packaging and Distribution
-
-- Use [uv](https://docs.astral.sh/uv/) for packaging (encouraged)
-- Consider releasing to PyPI for easier installation
-- Follow semantic versioning principles
-- Maintain a changelog
-
-### HTTP Communication
-
-For REST-based communication, use aiohttp. Pipecat includes this as a required dependency, so using it prevents adding an additional dependency to your integration.
-
-### Error Handling
-
-- Wrap API calls in appropriate try/catch blocks
-- Handle rate limits and network failures gracefully
-- Provide meaningful error messages
-- When errors occur, raise exceptions AND push `ErrorFrame`s to notify the pipeline:
-
-```python
-from pipecat.frames.frames import ErrorFrame
-
-try:
-    # Your API call
-    result = await self._make_api_call()
-except Exception as e:
-    # Push error frame to pipeline
-    await self.push_error(ErrorFrame(error=f"{self} error: {e}"))
-    # Raise or handle as appropriate
-    raise
-```
-
-### Testing
-
-- Your foundational example serves as a valuable integration-level test
-- Unit tests are nice to have. As the Pipecat teams provides better guidance, we will encourage unit testing more
-
-## Disclaimer
-
-Community integrations are community-maintained and not officially supported by the Pipecat team. Users should evaluate these integrations independently. The Pipecat team reserves the right to remove listings that become unmaintained or problematic.
-
-## Staying Up to Date
-
-Pipecat evolves rapidly to support the latest AI technologies and patterns. While we strive to minimize breaking changes, they do occur as the framework matures.
-
-**We strongly recommend:**
-
-- Join our Discord at https://discord.gg/pipecat and monitor the `#announcements` channel for release notifications
-- Follow our changelog: https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md
-- Test your integration against new Pipecat releases promptly
-- Update your README with the last tested Pipecat version
-
-This helps ensure your integration remains compatible and your users have clear expectations about version support.
-
-## Questions?
-
-Join our Discord community at https://discord.gg/pipecat and post in the `#community-integrations` channel for guidance and support.
-
-For additional questions, you can also reach out to us at pipecat-ai@daily.co.

CONTRIBUTING.md

@@ -1,9 +1,5 @@
 ## Contributing to Pipecat
 
-**Want to add a new service integration?**
-We encourage community-maintained integrations! Please see our [Community Integration Guide](COMMUNITY_INTEGRATIONS.md) for the process and requirements.
-
-**Want to contribute to Pipecat core?**
 We welcome contributions of all kinds! Your help is appreciated. Follow these steps to get involved:
 
 1. **Fork this repository**: Start by forking the Pipecat Documentation repository to your GitHub account.

README.md

@@ -2,8 +2,7 @@
  <img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
 </div></h1>
 
-[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![codecov](https://codecov.io/gh/pipecat-ai/pipecat/graph/badge.svg?token=LNVUIVO4Y9)](https://codecov.io/gh/pipecat-ai/pipecat) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/pipecat-ai/pipecat)
+[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![codecov](https://codecov.io/gh/pipecat-ai/pipecat/graph/badge.svg?token=LNVUIVO4Y9)](https://codecov.io/gh/pipecat-ai/pipecat) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat)
-[![](https://getmanta.ai/api/badges?text=Manta%20Graph&link=manta)](https://getmanta.ai/pipecat)
 
 # 🎙️ Pipecat: Real-Time Voice & Multimodal AI Agents
 
@@ -20,6 +19,8 @@
 - **Business Agents** – customer intake, support bots, guided flows
 - **Complex Dialog Systems** – design logic with structured conversations
 
+🧭 Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
+
 ## 🧠 Why Pipecat?
 
 - **Voice-first**: Integrates speech recognition, text-to-speech, and conversation handling
@@ -27,35 +28,6 @@
 - **Composable Pipelines**: Build complex behavior from modular components
 - **Real-Time**: Ultra-low latency interaction with different transports (e.g. WebSockets or WebRTC)
 
-## 🌐 Pipecat Ecosystem
-
-### 📱 Client SDKs
-
-Building client applications? You can connect to Pipecat from any platform using our official SDKs:
-
-<a href="https://docs.pipecat.ai/client/js/introduction">JavaScript</a> | <a href="https://docs.pipecat.ai/client/react/introduction">React</a> | <a href="https://docs.pipecat.ai/client/react-native/introduction">React Native</a> |
-<a href="https://docs.pipecat.ai/client/ios/introduction">Swift</a> | <a href="https://docs.pipecat.ai/client/android/introduction">Kotlin</a> | <a href="https://docs.pipecat.ai/client/c++/introduction">C++</a> | <a href="https://github.com/pipecat-ai/pipecat-esp32">ESP32</a>
-
-### 🧭 Structured conversations
-
-Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
-
-### 🪄 Beautiful UIs
-
-Want to build beautiful and engaging experiences? Checkout the [Voice UI Kit](https://github.com/pipecat-ai/voice-ui-kit), a collection of components, hooks and templates for building voice AI applications quickly.
-
-### 🔍 Debugging
-
-Looking for help debugging your pipeline and processors? Check out [Whisker](https://github.com/pipecat-ai/whisker), a real-time Pipecat debugger.
-
-### 🖥️ Terminal
-
-Love terminal applications? Check out [Tail](https://github.com/pipecat-ai/tail), a terminal dashboard for Pipecat.
-
-### 📺️ Pipecat TV Channel
-
-Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.youtube.com/playlist?list=PLzU2zoMTQIHjqC3v4q2XVSR3hGSzwKFwH) channel.
-
 ## 🎬 See it in action
 
 <p float="left">
@@ -66,20 +38,31 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
     <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/moondream-chatbot/image.png" width="400" /></a>
 </p>
 
+## 📱 Client SDKs
+
+You can connect to Pipecat from any platform using our official SDKs:
+
+| Platform | SDK Repo                                                                       | Description                      |
+| -------- | ------------------------------------------------------------------------------ | -------------------------------- |
+| Web      | [pipecat-client-web](https://github.com/pipecat-ai/pipecat-client-web)         | JavaScript and React client SDKs |
+| iOS      | [pipecat-client-ios](https://github.com/pipecat-ai/pipecat-client-ios)         | Swift SDK for iOS                |
+| Android  | [pipecat-client-android](https://github.com/pipecat-ai/pipecat-client-android) | Kotlin SDK for Android           |
+| C++      | [pipecat-client-cxx](https://github.com/pipecat-ai/pipecat-client-cxx)         | C++ client SDK                   |
+
 ## 🧩 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), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [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)                                                                                                                    |
+| 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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [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), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [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      | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [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), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [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) |
+| Text-to-Speech      | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [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), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [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), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [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               | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [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), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
+| 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)
@@ -146,11 +129,7 @@ You can get started with Pipecat running on your local machine, then move your a
 2. Install development and testing dependencies:
 
    ```bash
-   uv sync --group dev --all-extras \
+   uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp --no-extra local
-     --no-extra gstreamer \
-     --no-extra krisp \
-     --no-extra local \
-     --no-extra ultravox # (ultravox not fully supported on macOS)
    ```
 
 3. Install the git pre-commit hooks:
@@ -159,6 +138,23 @@ You can get started with Pipecat running on your local machine, then move your a
    uv run pre-commit install
    ```
 
+### Python 3.13+ Compatibility
+
+Some features require PyTorch, which doesn't yet support Python 3.13+. Install using:
+
+```bash
+uv sync --group dev --all-extras \
+  --no-extra gstreamer \
+  --no-extra krisp \
+  --no-extra local \
+  --no-extra local-smart-turn \
+  --no-extra mlx-whisper \
+  --no-extra moondream \
+  --no-extra ultravox
+```
+
+> **Tip:** For full compatibility, use Python 3.12: `uv python pin 3.12`
+
 > **Note**: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors.
 
 ### Running tests
@@ -175,6 +171,54 @@ Run a specific test suite:
 uv run pytest tests/test_name.py
 ```
 
+### Setting up your editor
+
+This project uses strict [PEP 8](https://peps.python.org/pep-0008/) formatting via [Ruff](https://github.com/astral-sh/ruff).
+
+#### Emacs
+
+You can use [use-package](https://github.com/jwiegley/use-package) to install [emacs-lazy-ruff](https://github.com/christophermadsen/emacs-lazy-ruff) package and configure `ruff` arguments:
+
+```elisp
+(use-package lazy-ruff
+  :ensure t
+  :hook ((python-mode . lazy-ruff-mode))
+  :config
+  (setq lazy-ruff-format-command "ruff format")
+  (setq lazy-ruff-check-command "ruff check --select I"))
+```
+
+`ruff` was installed in the `venv` environment described before, so you should be able to use [pyvenv-auto](https://github.com/ryotaro612/pyvenv-auto) to automatically load that environment inside Emacs.
+
+```elisp
+(use-package pyvenv-auto
+  :ensure t
+  :defer t
+  :hook ((python-mode . pyvenv-auto-run)))
+```
+
+#### Visual Studio Code
+
+Install the
+[Ruff](https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff) extension. Then edit the user settings (_Ctrl-Shift-P_ `Open User Settings (JSON)`) and set it as the default Python formatter, and enable formatting on save:
+
+```json
+"[python]": {
+    "editor.defaultFormatter": "charliermarsh.ruff",
+    "editor.formatOnSave": true
+}
+```
+
+#### PyCharm
+
+`ruff` was installed in the `venv` environment described before, now to enable autoformatting on save, go to `File` -> `Settings` -> `Tools` -> `File Watchers` and add a new watcher with the following settings:
+
+1. **Name**: `Ruff formatter`
+2. **File type**: `Python`
+3. **Working directory**: `$ContentRoot$`
+4. **Arguments**: `format $FilePath$`
+5. **Program**: `$PyInterpreterDirectory$/ruff`
+
 ## 🤝 Contributing
 
 We welcome contributions from the community! Whether you're fixing bugs, improving documentation, or adding new features, here's how you can help:

SECURITY.md

@@ -1,5 +0,0 @@
-# Security Policy
-
-## Reporting a Vulnerability
-
-Please email `disclosures@daily.co`.

docs/api/conf.py

@@ -50,7 +50,6 @@ autodoc_mock_imports = [
     # Krisp - has build issues on some platforms
     "pipecat_ai_krisp",
     "krisp",
-    "krisp_audio",
     # System-specific GUI libraries
     "_tkinter",
     "tkinter",

env.example

@@ -1,6 +1,3 @@
-# AI-COUSTICS
-AICOUSTICS_LICENSE_KEY=...
-
 # Anthropic
 ANTHROPIC_API_KEY=...
 
@@ -58,9 +55,6 @@ GOOGLE_CLOUD_PROJECT_ID=...
 GOOGLE_TEST_CREDENTIALS=...
 GOOGLE_VERTEX_TEST_CREDENTIALS=...
 
-# Hume
-HUME_API_KEY=...
-
 # LMNT
 LMNT_API_KEY=...
 LMNT_VOICE_ID=...
@@ -69,8 +63,8 @@ LMNT_VOICE_ID=...
 PERPLEXITY_API_KEY=...
 
 # PlayHT
-PLAYHT_USER_ID=...
+PLAY_HT_USER_ID=...
-PLAYHT_API_KEY=...
+PLAY_HT_API_KEY=...
 
 # OpenAI
 OPENAI_API_KEY=...
@@ -90,9 +84,6 @@ SIMLI_FACE_ID=...
 # Krisp
 KRISP_MODEL_PATH=...
 
-# Krisp Viva
-KRISP_VIVA_MODEL_PATH=...
-
 # DeepSeek
 DEEPSEEK_API_KEY=...
 
@@ -152,18 +143,3 @@ SENTRY_DSN=...
 
 # Heygen
 HEYGEN_API_KEY=...
-
-# Mistral
-MISTRAL_API_KEY=...
-
-# NVIDIA
-NVIDIA_API_KEY=...
-
-# Qwen
-QWEN_API_KEY=...
-
-# WhatsApp
-WHATSAPP_TOKEN=
-WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=
-WHATSAPP_PHONE_NUMBER_ID=
-WHATSAPP_APP_SECRET=

examples/foundational/01-say-one-thing-piper.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.piper.tts import PiperTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

examples/foundational/01-say-one-thing-rime.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.rime.tts import RimeHttpTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

examples/foundational/01-say-one-thing.py

@@ -17,8 +17,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

examples/foundational/01b-livekit-audio.py

@@ -11,13 +11,13 @@ import sys
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
 from pipecat.runner.livekit import configure
 from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
+from pipecat.transports.services.livekit import LiveKitParams, LiveKitTransport
 
 load_dotenv(override=True)
 
@@ -50,7 +50,7 @@ async def main():
     async def on_first_participant_joined(transport, participant_id):
         await asyncio.sleep(1)
         await task.queue_frame(
-            TTSSpeakFrame(
+            TextFrame(
                 "Hello there! How are you doing today? Would you like to talk about the weather?"
             )
         )

examples/foundational/01c-fastpitch.py

@@ -17,8 +17,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.riva.tts import FastPitchTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

examples/foundational/02-llm-say-one-thing.py

@@ -9,18 +9,21 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.frames.frames import EndFrame, LLMContextFrame
+from pipecat.frames.frames import EndFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -60,7 +63,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Register an event handler so we can play the audio when the client joins
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):
-        await task.queue_frames([LLMContextFrame(LLMContext(messages)), EndFrame()])
+        await task.queue_frames([OpenAILLMContextFrame(OpenAILLMContext(messages)), EndFrame()])
 
     runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
 

examples/foundational/03-still-frame.py

@@ -18,7 +18,7 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.fal.image import FalImageGenService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

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

@@ -17,7 +17,7 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.google.image import GoogleImageGenService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

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

@@ -17,22 +17,18 @@ from fastapi.responses import RedirectResponse
 from loguru import logger
 from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.smallwebrtc.connection import IceServer, SmallWebRTCConnection
+from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
-from pipecat.transports.smallwebrtc.transport import SmallWebRTCTransport
+from pipecat.transports.network.webrtc_connection import IceServer, SmallWebRTCConnection
 
 load_dotenv(override=True)
 
@@ -60,8 +56,7 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
         params=TransportParams(
             audio_in_enabled=True,
             audio_out_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+            vad_analyzer=SileroVADAnalyzer(),
-            turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
         ),
     )
 
@@ -81,8 +76,8 @@ async def run_example(webrtc_connection: SmallWebRTCConnection):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -12,20 +12,16 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.daily import configure
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.daily.transport import DailyParams, DailyTransport
+from pipecat.transports.services.daily import DailyLogLevel, DailyParams, DailyTransport
 
 load_dotenv(override=True)
 
@@ -45,10 +41,10 @@ async def main():
                 audio_in_enabled=True,
                 audio_out_enabled=True,
                 transcription_enabled=True,
-                vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+                vad_analyzer=SileroVADAnalyzer(),
-                turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
             ),
         )
+        transport.set_log_level(DailyLogLevel.Info)
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
@@ -64,8 +60,8 @@ async def main():
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -12,27 +12,23 @@ import sys
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import (
-    InterruptionFrame,
+    BotInterruptionFrame,
+    TextFrame,
     TranscriptionFrame,
-    TTSSpeakFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.livekit import configure
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
+from pipecat.transports.services.livekit import LiveKitParams, LiveKitTransport
 
 load_dotenv(override=True)
 
@@ -50,8 +46,7 @@ async def main():
         params=LiveKitParams(
             audio_in_enabled=True,
             audio_out_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+            vad_analyzer=SileroVADAnalyzer(),
-            turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
         ),
     )
 
@@ -74,8 +69,8 @@ async def main():
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [
@@ -103,7 +98,7 @@ async def main():
     async def on_first_participant_joined(transport, participant_id):
         await asyncio.sleep(1)
         await task.queue_frame(
-            TTSSpeakFrame(
+            TextFrame(
                 "Hello there! How are you doing today? Would you like to talk about the weather?"
             )
         )
@@ -120,7 +115,7 @@ async def main():
 
         await task.queue_frames(
             [
-                InterruptionFrame(),
+                BotInterruptionFrame(),
                 UserStartedSpeakingFrame(),
                 TranscriptionFrame(
                     user_id=participant_id,

examples/foundational/05-sync-speech-and-image.py

@@ -14,7 +14,6 @@ from loguru import logger
 from pipecat.frames.frames import (
     DataFrame,
     Frame,
-    LLMContextFrame,
     LLMFullResponseStartFrame,
     TextFrame,
 )
@@ -22,8 +21,10 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
@@ -32,7 +33,7 @@ from pipecat.services.cartesia.tts import CartesiaHttpTTSService
 from pipecat.services.fal.image import FalImageGenService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -155,7 +156,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 }
             ]
             frames.append(MonthFrame(month=month))
-            frames.append(LLMContextFrame(LLMContext(messages)))
+            frames.append(OpenAILLMContextFrame(OpenAILLMContext(messages)))
 
         task = PipelineTask(
             pipeline,

examples/foundational/05a-local-sync-speech-and-image.py

@@ -15,7 +15,6 @@ from loguru import logger
 
 from pipecat.frames.frames import (
     Frame,
-    LLMContextFrame,
     OutputAudioRawFrame,
     TextFrame,
     TTSAudioRawFrame,
@@ -25,8 +24,10 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.sync_parallel_pipeline import SyncParallelPipeline
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.processors.aggregators.sentence import SentenceAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.cartesia.tts import CartesiaHttpTTSService
@@ -139,7 +140,7 @@ async def main():
             )
 
             task = PipelineTask(pipeline)
-            await task.queue_frame(LLMContextFrame(LLMContext(messages)))
+            await task.queue_frame(OpenAILLMContextFrame(OpenAILLMContext(messages)))
             await task.stop_when_done()
 
             await runner.run(task)

examples/foundational/06-listen-and-respond.py

@@ -9,10 +9,7 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import Frame, LLMRunFrame, MetricsFrame
 from pipecat.metrics.metrics import (
     LLMUsageMetricsData,
@@ -23,8 +20,7 @@ from pipecat.metrics.metrics import (
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -32,8 +28,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -65,20 +61,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -104,8 +97,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,10 +10,7 @@ from dotenv import load_dotenv
 from loguru import logger
 from PIL import Image
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import (
     BotStartedSpeakingFrame,
     BotStoppedSpeakingFrame,
@@ -24,8 +21,7 @@ from pipecat.frames.frames import (
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -33,7 +29,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -70,7 +66,7 @@ class ImageSyncAggregator(FrameProcessor):
                 )
             )
 
-        await self.push_frame(frame, direction)
+        await self.push_frame(frame)
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -83,8 +79,7 @@ transport_params = {
         video_out_enabled=True,
         video_out_width=1024,
         video_out_height=1024,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
@@ -92,8 +87,7 @@ transport_params = {
         video_out_enabled=True,
         video_out_width=1024,
         video_out_height=1024,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -117,8 +111,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     image_sync_aggregator = ImageSyncAggregator(
         os.path.join(os.path.dirname(__file__), "assets", "speaking.png"),

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

@@ -9,24 +9,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaHttpTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -75,8 +68,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

examples/foundational/07-interruptible.py

@@ -9,24 +9,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -37,20 +33,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -74,8 +67,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -13,11 +13,10 @@ from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response import (
     LLMUserAggregatorParams,
 )
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
@@ -26,8 +25,8 @@ 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.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -124,8 +123,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(
+    context_aggregator = llm.create_context_aggregator(
         context,
         user_params=LLMUserAggregatorParams(aggregation_timeout=0.005),
     )

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

@@ -9,19 +9,15 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response import (
     LLMUserAggregatorParams,
 )
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
@@ -30,8 +26,8 @@ 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.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -42,20 +38,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -113,8 +106,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(
+    context_aggregator = llm.create_context_aggregator(
         context,
         user_params=LLMUserAggregatorParams(aggregation_timeout=0.005),
     )

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 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.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -35,20 +31,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -74,8 +67,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

examples/foundational/07ab-interruptible-inworld-http.py

@@ -11,24 +11,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.inworld.tts import InworldTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -74,6 +67,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             voice_id="Ashley",
             model="inworld-tts-1",
             streaming=streaming,  # True: real-time chunks, False: complete audio then playback
+            params=InworldTTSService.InputParams(
+                temperature=0.8,
+            ),
         )
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
@@ -85,8 +81,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

examples/foundational/07ac-interruptible-asyncai-http.py

@@ -11,24 +11,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.asyncai.tts import AsyncAIHttpTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,20 +36,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -80,8 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

examples/foundational/07ac-interruptible-asyncai.py

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.asyncai.tts import AsyncAITTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -76,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

examples/foundational/07ad-interruptible-aicoustics.py

@@ -1,169 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-
-import datetime
-import os
-import wave
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.filters.aic_filter import AICFilter
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
-from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-
-# Create audio buffer processor so we can hear the audio fitler results.
-audiobuffer = AudioBufferProcessor(
-    num_channels=2,  # 1 for mono, 2 for stereo (user left, bot right)
-    enable_turn_audio=False,  # Enable per-turn audio recording
-)
-
-
-def _create_aic_filter() -> AICFilter:
-    license_key = os.getenv("AICOUSTICS_LICENSE_KEY", "")
-
-    return AICFilter(
-        license_key=license_key,
-        enhancement_level=1.0,
-    )
-
-
-# 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(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-        audio_in_filter=_create_aic_filter(),
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-        audio_in_filter=_create_aic_filter(),
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-        audio_in_filter=_create_aic_filter(),
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    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
-    )
-
-    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 = LLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            stt,  # STT
-            context_aggregator.user(),  # User responses
-            llm,  # LLM
-            tts,  # TTS
-            transport.output(),  # Transport bot output
-            audiobuffer,  # write audio data to a file
-            context_aggregator.assistant(),  # Assistant spoken responses
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        await audiobuffer.start_recording()
-        # Kick off the conversation.
-        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([LLMRunFrame()])
-
-    @audiobuffer.event_handler("on_audio_data")
-    async def on_audio_data(buffer, audio, sample_rate, num_channels):
-        # Save or process the composite audio
-        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-        filename = f"./conversation_{timestamp}.wav"
-
-        # Create the WAV file
-        with wave.open(filename, "wb") as wf:
-            wf.setnchannels(num_channels)
-            wf.setsampwidth(2)  # 16-bit audio
-            wf.setframerate(sample_rate)
-            wf.writeframes(audio)
-
-        logger.info(f"Saved recording to {filename}")
-
-    @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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/07ae-interruptible-hume.py

@@ -1,138 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
-from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-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(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-    tts = HumeTTSService(
-        api_key=os.getenv("HUME_API_KEY"),
-        # Replace with your Hume voice ID
-        voice_id="f898a92e-685f-43fa-985b-a46920f0650b",
-    )
-
-    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 = LLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
-
-    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            rtvi,
-            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,
-            audio_out_sample_rate=HUME_SAMPLE_RATE,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-        observers=[RTVIObserver(rtvi)],
-    )
-
-    @rtvi.event_handler("on_client_ready")
-    async def on_client_ready(rtvi):
-        await rtvi.set_bot_ready()
-
-    @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([LLMRunFrame()])
-
-    @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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

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

@@ -15,24 +15,26 @@ from langchain_core.runnables.history import RunnableWithMessageHistory
 from langchain_openai import ChatOpenAI
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMMessagesUpdateFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response import (
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+)
+from pipecat.processors.aggregators.openai_llm_context import (
+    OpenAILLMContext,
+)
 from pipecat.processors.frameworks.langchain import LangchainProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -53,20 +55,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -101,18 +100,19 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     )
     lc = LangchainProcessor(history_chain)
 
-    context = LLMContext()
+    context = OpenAILLMContext()
-    context_aggregator = LLMContextAggregatorPair(context)
+    tma_in = LLMUserContextAggregator(context=context)
+    tma_out = LLMAssistantContextAggregator(context=context)
 
     pipeline = Pipeline(
         [
             transport.input(),  # Transport user input
             stt,
-            context_aggregator.user(),  # User responses
+            tma_in,  # User responses
             lc,  # Langchain
             tts,  # TTS
             transport.output(),  # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses
+            tma_out,  # Assistant spoken responses
         ]
     )
 
@@ -129,7 +129,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
-        # An `LLMContextFrame` will be picked up by the LangchainProcessor using
+        # An `OpenAILLMContextFrame` will be picked up by the LangchainProcessor using
         # only the content of the last message to inject it in the prompt defined
         # above. So no role is required here.
         messages = [({"content": "Please briefly introduce yourself to the user."})]

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

@@ -1,118 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import LLMRunFrame
-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_universal import (
-    LLMContext,
-    LLMContextAggregatorPair,
-)
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.deepgram.flux.stt import DeepgramFluxSTTService
-from pipecat.services.deepgram.tts import DeepgramTTSService
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-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,
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = DeepgramFluxSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-    tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-2-andromeda-en")
-
-    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 = LLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
-
-    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,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @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([LLMRunFrame()])
-
-    @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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

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

@@ -12,24 +12,23 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.frames.frames import (
-    InterruptionFrame,
     LLMRunFrame,
+    StartInterruptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.deepgram.tts import DeepgramTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -72,8 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [
@@ -98,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     @stt.event_handler("on_speech_started")
     async def on_speech_started(stt, *args, **kwargs):
-        await task.queue_frames([InterruptionFrame(), UserStartedSpeakingFrame()])
+        await task.queue_frames([StartInterruptionFrame(), UserStartedSpeakingFrame()])
 
     @stt.event_handler("on_utterance_end")
     async def on_utterance_end(stt, *args, **kwargs):

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.deepgram.tts import DeepgramTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -73,8 +66,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -11,24 +11,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
-from pipecat.services.elevenlabs.stt import ElevenLabsSTTService
+from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.elevenlabs.tts import ElevenLabsHttpTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,20 +36,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -63,10 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     # Create an HTTP session
     async with aiohttp.ClientSession() as session:
-        stt = ElevenLabsSTTService(
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            aiohttp_session=session,
-        )
 
         tts = ElevenLabsHttpTTSService(
             api_key=os.getenv("ELEVENLABS_API_KEY", ""),
@@ -83,8 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -76,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.playht.tts import PlayHTHttpTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -76,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,16 +10,12 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -27,8 +23,8 @@ from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.playht.tts import PlayHTTTSService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -78,8 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.azure.llm import AzureLLMService
 from pipecat.services.azure.stt import AzureSTTService
 from pipecat.services.azure.tts import AzureTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -82,8 +75,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.openai.stt import OpenAISTTService
 from pipecat.services.openai.tts import OpenAITTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -76,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -11,24 +11,20 @@ import time
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openpipe.llm import OpenPipeLLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -81,8 +74,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -11,24 +11,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.xtts.tts import XTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -79,8 +72,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -10,16 +10,12 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -28,8 +24,8 @@ from pipecat.services.gladia.stt import GladiaSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,20 +36,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -85,8 +78,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.lmnt.tts import LmntTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -72,8 +65,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,25 +10,21 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response import LLMUserAggregatorParams
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.groq.llm import GroqLLMService
 from pipecat.services.groq.stt import GroqSTTService
 from pipecat.services.groq.tts import GroqTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -75,8 +68,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(
+    context_aggregator = llm.create_context_aggregator(
         context, user_params=LLMUserAggregatorParams(aggregation_timeout=0.05)
     )
 

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

@@ -1,177 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesAppendFrame, LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
-from pipecat.processors.frameworks.strands_agents import StrandsAgentsProcessor
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.aws.stt import AWSTranscribeSTTService
-from pipecat.services.aws.tts import AWSPollyTTSService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-# Strands agent setup
-try:
-    from strands import Agent, tool
-    from strands.models import BedrockModel
-except ImportError:
-    logger.warning("Strands not installed. Please install with: pip install strands-agents")
-    Agent = None
-    BedrockModel = None
-
-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(),
-    ),
-}
-
-
-def build_agent(model_id: str, max_tokens: int):
-    """Create and configure a Strands agent for NAB customer service coaching.
-
-    Args:
-        model_id: The AWS Bedrock model ID to use
-        max_tokens: Maximum tokens for the model
-
-    Returns:
-        Configured Strands Agent
-    """
-
-    @tool
-    def check_weather(location: str) -> str:
-        if location.lower() == "san francisco":
-            return "The weather in San Francisco is sunny and 30 degrees."
-        elif location.lower() == "sydney":
-            return "The weather in Sydney is cloudy and 20 degrees."
-        else:
-            return "I'm not sure about the weather in that location."
-
-    agent = Agent(
-        model=BedrockModel(
-            model_id=model_id,
-            max_tokens=max_tokens,
-        ),
-        tools=[check_weather],
-        system_prompt="You are a helpful assistant that can check the weather in a given location.",
-    )
-
-    return agent
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = AWSTranscribeSTTService()
-
-    tts = AWSPollyTTSService(
-        region="us-west-2",  # only specific regions support generative TTS
-        voice_id="Joanna",
-        params=AWSPollyTTSService.InputParams(engine="generative", rate="1.1"),
-    )
-
-    # Create Strands agent processor
-    try:
-        agent = build_agent(model_id="us.anthropic.claude-3-5-haiku-20241022-v1:0", max_tokens=8000)
-        llm = StrandsAgentsProcessor(agent=agent)
-        logger.info("Successfully created Strands agent for NAB customer service coaching")
-    except Exception as e:
-        logger.error(f"Failed to create Strands agent: {e}")
-        raise ValueError(
-            "Unable to create Strands processor. Please ensure you have properly "
-            "installed strands-agents and configured your AWS credentials."
-        )
-
-    # Setup context aggregators for message handling
-    context = LLMContext()
-    context_aggregator = LLMContextAggregatorPair(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            stt,  # Speech-to-text
-            context_aggregator.user(),  # User responses
-            llm,  # Strands Agents processor
-            tts,  # Text-to-speech
-            transport.output(),  # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @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(
-            [
-                LLMMessagesAppendFrame(
-                    messages=[
-                        {
-                            "role": "user",
-                            "content": f"Greet the user and introduce yourself.",
-                        }
-                    ],
-                    run_llm=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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

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

@@ -8,24 +8,20 @@
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.aws.llm import AWSBedrockLLMService
 from pipecat.services.aws.stt import AWSTranscribeSTTService
 from pipecat.services.aws.tts import AWSPollyTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -36,20 +32,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -78,8 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

examples/foundational/07n-interruptible-gemini-image.py

@@ -1,151 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-"""
-A conversational AI bot using Gemini for both LLM, STT and TTS.
-
-This example demonstrates how to use Gemini's image generation capabilities.
-
-Features showcased:
-- Gemini LLM for conversation and image generation
-- Google TTS and STT
-
-Run with:
-    python examples/foundational/07n-interruptible-gemini-image.py
-
-Make sure to set your environment variables:
-    export GOOGLE_API_KEY=your_api_key_here
-"""
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.google.llm import GoogleLLMService
-from pipecat.services.google.stt import GoogleSTTService
-from pipecat.services.google.tts import GoogleTTSService
-from pipecat.transcriptions.language import Language
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-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,
-        video_out_enabled=True,
-        video_out_width=1024,
-        video_out_height=1024,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        video_out_enabled=True,
-        video_out_width=1024,
-        video_out_height=1024,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = GoogleSTTService(
-        params=GoogleSTTService.InputParams(languages=Language.EN_US),
-        credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
-    )
-
-    tts = GoogleTTSService(
-        voice_id="en-US-Chirp3-HD-Charon",
-        params=GoogleTTSService.InputParams(language=Language.EN_US),
-        credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
-    )
-
-    llm = GoogleLLMService(
-        api_key=os.getenv("GOOGLE_API_KEY"),
-        model="gemini-2.5-flash-image",
-    )
-
-    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 = LLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),  # Transport user input
-            stt,  # STT
-            context_aggregator.user(),  # User responses
-            llm,  # LLM
-            tts,  # Gemini TTS
-            transport.output(),  # Transport bot output
-            context_aggregator.assistant(),  # Assistant spoken responses
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        # Kick off the conversation with a styled introduction
-        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([LLMRunFrame()])
-
-    @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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

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

@@ -28,16 +28,12 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.google.llm import GoogleLLMService
@@ -45,8 +41,8 @@ from pipecat.services.google.stt import GoogleSTTService
 from pipecat.services.google.tts import GeminiTTSService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -57,20 +53,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -113,8 +106,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,16 +10,12 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.google.llm import GoogleLLMService
@@ -27,8 +23,8 @@ from pipecat.services.google.stt import GoogleSTTService
 from pipecat.services.google.tts import GoogleTTSService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -85,8 +78,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.assemblyai.stt import AssemblyAISTTService
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -78,8 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -1,129 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.filters.krisp_viva_filter import KrispVivaFilter
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import LLMRunFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.deepgram.tts import DeepgramTTSService
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-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(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-        audio_in_filter=KrispVivaFilter(),
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-        audio_in_filter=KrispVivaFilter(),
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-        audio_in_filter=KrispVivaFilter(),
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-    tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
-
-    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 = LLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
-
-    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,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @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([LLMRunFrame()])
-
-    @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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

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

@@ -11,24 +11,20 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.filters.krisp_filter import KrispFilter
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.deepgram.tts import DeepgramTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,22 +35,19 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
         audio_in_filter=KrispFilter(),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
         audio_in_filter=KrispFilter(),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
         audio_in_filter=KrispFilter(),
     ),
 }
@@ -76,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -11,24 +11,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.rime.tts import RimeHttpTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,20 +36,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -81,8 +74,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.rime.tts import RimeTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -75,8 +68,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.nim.llm import NimLLMService
 from pipecat.services.riva.stt import RivaSTTService
 from pipecat.services.riva.tts import RivaTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -72,8 +65,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -12,17 +12,14 @@ from dotenv import load_dotenv
 from google.genai.types import Content, Part
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import (
     Frame,
     InputAudioRawFrame,
-    InterruptionFrame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
     LLMRunFrame,
+    StartInterruptionFrame,
     TextFrame,
     TranscriptionFrame,
     UserStartedSpeakingFrame,
@@ -31,8 +28,7 @@ from pipecat.frames.frames import (
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.frame_processor import FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -40,8 +36,8 @@ from pipecat.services.google.llm import GoogleLLMService
 from pipecat.services.google.tts import GoogleTTSService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -97,8 +93,9 @@ class UserAudioCollector(FrameProcessor):
         elif isinstance(frame, UserStoppedSpeakingFrame):
             self._user_speaking = False
             self._context.add_audio_frames_message(audio_frames=self._audio_frames)
-            await self._user_context_aggregator.push_frame(LLMRunFrame())
+            await self._user_context_aggregator.push_frame(
-
+                self._user_context_aggregator.get_context_frame()
+            )
         elif isinstance(frame, InputAudioRawFrame):
             if self._user_speaking:
                 self._audio_frames.append(frame)
@@ -154,7 +151,7 @@ class TranscriptExtractor(FrameProcessor):
         await self.push_frame(frame, direction)
 
 
-class TranscriptionContextFixup(FrameProcessor):
+class TanscriptionContextFixup(FrameProcessor):
     def __init__(self, context):
         super().__init__()
         self._context = context
@@ -185,7 +182,9 @@ class TranscriptionContextFixup(FrameProcessor):
 
         if isinstance(frame, MagicDemoTranscriptionFrame):
             self._transcript = frame.text
-        elif isinstance(frame, LLMFullResponseEndFrame) or isinstance(frame, InterruptionFrame):
+        elif isinstance(frame, LLMFullResponseEndFrame) or isinstance(
+            frame, StartInterruptionFrame
+        ):
             self.swap_user_audio()
             self.add_transcript_back_to_inference_output()
             self._transcript = ""
@@ -200,20 +199,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -245,11 +241,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
     audio_collector = UserAudioCollector(context, context_aggregator.user())
     pull_transcript_out_of_llm_output = TranscriptExtractor(context)
-    fixup_context_messages = TranscriptionContextFixup(context)
+    fixup_context_messages = TanscriptionContextFixup(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.fish.tts import FishAudioTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -76,8 +69,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,10 +10,7 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,8 +19,8 @@ from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.ultravox.stt import UltravoxSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -47,20 +44,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 

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

@@ -11,24 +11,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.neuphonic.tts import NeuphonicHttpTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,20 +36,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -80,8 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.neuphonic.tts import NeuphonicTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -75,8 +68,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -10,24 +10,20 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.fal.stt import FalSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -39,20 +35,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -78,8 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -11,16 +11,12 @@ import sys
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -39,8 +35,7 @@ async def main():
         LocalAudioTransportParams(
             audio_in_enabled=True,
             audio_out_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+            vad_analyzer=SileroVADAnalyzer(),
-            turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
         )
     )
 
@@ -60,8 +55,8 @@ async def main():
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -11,16 +11,12 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -28,8 +24,8 @@ from pipecat.services.minimax.tts import MiniMaxHttpTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -41,20 +37,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -82,8 +75,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -11,15 +11,11 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -27,8 +23,8 @@ from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.sarvam.tts import SarvamHttpTTSService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,20 +36,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -80,8 +73,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             },
         ]
 
-        context = LLMContext(messages)
+        context = OpenAILLMContext(messages)
-        context_aggregator = LLMContextAggregatorPair(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [

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

@@ -12,24 +12,20 @@ import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.services.sarvam.tts import SarvamTTSService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -41,20 +37,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -78,8 +71,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

examples/foundational/08-bots-arguing.py

@@ -6,16 +6,18 @@ from typing import Tuple
 import aiohttp
 from dotenv import load_dotenv
 
-from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, LLMContextFrame, TextFrame
+from pipecat.frames.frames import AudioFrame, EndFrame, ImageFrame, TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.processors.aggregators import SentenceAggregator
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.runner.daily import configure
 from pipecat.services.azure import AzureLLMService, AzureTTSService
 from pipecat.services.elevenlabs import ElevenLabsTTSService
 from pipecat.services.fal import FalImageGenService
-from pipecat.transports.daily.transport import DailyTransport
+from pipecat.transports.services.daily import DailyTransport
 
 load_dotenv(override=True)
 
@@ -81,7 +83,7 @@ async def main():
             sentence_aggregator = SentenceAggregator()
             pipeline = Pipeline([llm, sentence_aggregator, tts1], source_queue, sink_queue)
 
-            await source_queue.put(LLMContextFrame(LLMContext(messages)))
+            await source_queue.put(OpenAILLMContextFrame(OpenAILLMContext(messages)))
             await source_queue.put(EndFrame())
             await pipeline.run_pipeline()
 

examples/foundational/09-mirror.py

@@ -22,7 +22,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

examples/foundational/09a-local-mirror.py

@@ -24,8 +24,8 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport, maybe_capture_participant_camera
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
 from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 

examples/foundational/10-wake-phrase.py

@@ -9,16 +9,12 @@ import os
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 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.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.processors.filters.wake_check_filter import WakeCheckFilter
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
@@ -26,8 +22,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -38,20 +34,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -77,8 +70,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     hey_robot_filter = WakeCheckFilter(["hey robot", "hey, robot"])
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

examples/foundational/11-sound-effects.py

@@ -10,13 +10,9 @@ import wave
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import (
     Frame,
-    LLMContextFrame,
     LLMFullResponseEndFrame,
     OutputAudioRawFrame,
     TTSSpeakFrame,
@@ -24,8 +20,10 @@ from pipecat.frames.frames import (
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import (
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+    OpenAILLMContext,
+    OpenAILLMContextFrame,
+)
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.processors.logger import FrameLogger
 from pipecat.runner.types import RunnerArguments
@@ -34,8 +32,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -73,7 +71,7 @@ class InboundSoundEffectWrapper(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, LLMContextFrame):
+        if isinstance(frame, OpenAILLMContextFrame):
             await self.push_frame(sounds["ding2.wav"])
             # In case anything else downstream needs it
             await self.push_frame(frame, direction)
@@ -88,20 +86,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -125,8 +120,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages)
+    context = OpenAILLMContext(messages)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
     out_sound = OutboundSoundEffectWrapper()
     in_sound = InboundSoundEffectWrapper()
     fl = FrameLogger("LLM Out")

examples/foundational/12-describe-video.py

@@ -10,23 +10,13 @@ from typing import Optional
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
-from pipecat.frames.frames import (
-    Frame,
-    LLMContextFrame,
-    TextFrame,
-    TTSSpeakFrame,
-    UserImageRawFrame,
-    UserImageRequestFrame,
-)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.user_response import UserResponseAggregator
+from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
@@ -38,14 +28,12 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.moondream.vision import MoondreamService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
 
 class UserImageRequester(FrameProcessor):
-    """Converts incoming text into requests for user images."""
-
     def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
@@ -58,32 +46,9 @@ class UserImageRequester(FrameProcessor):
 
         if self._participant_id and isinstance(frame, TextFrame):
             await self.push_frame(
-                UserImageRequestFrame(self._participant_id, context=frame.text),
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
-                FrameDirection.UPSTREAM,
             )
-        else:
+        await self.push_frame(frame, direction)
-            await self.push_frame(frame, direction)
-
-
-class UserImageProcessor(FrameProcessor):
-    """Converts incoming user images into context frames."""
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, UserImageRawFrame):
-            if frame.request and frame.request.context:
-                context = LLMContext()
-                context.add_image_frame_message(
-                    image=frame.image,
-                    text=frame.request.context,
-                    size=frame.size,
-                    format=frame.format,
-                )
-                frame = LLMContextFrame(context)
-                await self.push_frame(frame)
-        else:
-            await self.push_frame(frame, direction)
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -94,15 +59,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -115,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Initialize the image requester without setting the participant ID yet
     image_requester = UserImageRequester()
 
-    image_processor = UserImageProcessor()
+    vision_aggregator = VisionImageFrameAggregator()
 
     # If you run into weird description, try with use_cpu=True
     moondream = MoondreamService()
@@ -133,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             stt,
             user_response,
             image_requester,
-            image_processor,
+            vision_aggregator,
             moondream,
             tts,
             transport.output(),
@@ -156,7 +119,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me about what I see."))
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):

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

@@ -10,23 +10,13 @@ from typing import Optional
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
-from pipecat.frames.frames import (
-    Frame,
-    LLMContextFrame,
-    TextFrame,
-    TTSSpeakFrame,
-    UserImageRawFrame,
-    UserImageRequestFrame,
-)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.user_response import UserResponseAggregator
+from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
@@ -38,14 +28,12 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.google.llm import GoogleLLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
 
 class UserImageRequester(FrameProcessor):
-    """Converts incoming text into requests for user images."""
-
     def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
@@ -58,32 +46,9 @@ class UserImageRequester(FrameProcessor):
 
         if self._participant_id and isinstance(frame, TextFrame):
             await self.push_frame(
-                UserImageRequestFrame(self._participant_id, context=frame.text),
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
-                FrameDirection.UPSTREAM,
             )
-        else:
+        await self.push_frame(frame, direction)
-            await self.push_frame(frame, direction)
-
-
-class UserImageProcessor(FrameProcessor):
-    """Converts incoming user images into context frames."""
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, UserImageRawFrame):
-            if frame.request and frame.request.context:
-                context = LLMContext()
-                context.add_image_frame_message(
-                    image=frame.image,
-                    text=frame.request.context,
-                    size=frame.size,
-                    format=frame.format,
-                )
-                frame = LLMContextFrame(context)
-                await self.push_frame(frame)
-        else:
-            await self.push_frame(frame, direction)
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -94,15 +59,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -115,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Initialize the image requester without setting the participant ID yet
     image_requester = UserImageRequester()
 
-    image_processor = UserImageProcessor()
+    vision_aggregator = VisionImageFrameAggregator()
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
@@ -133,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             stt,
             user_response,
             image_requester,
-            image_processor,
+            vision_aggregator,
             google,
             tts,
             transport.output(),
@@ -160,7 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me about what I see."))
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):

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

@@ -10,23 +10,13 @@ from typing import Optional
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
-from pipecat.frames.frames import (
-    Frame,
-    LLMContextFrame,
-    TextFrame,
-    TTSSpeakFrame,
-    UserImageRawFrame,
-    UserImageRequestFrame,
-)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.user_response import UserResponseAggregator
+from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
@@ -38,14 +28,12 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
 
 class UserImageRequester(FrameProcessor):
-    """Converts incoming text into requests for user images."""
-
     def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
@@ -58,32 +46,9 @@ class UserImageRequester(FrameProcessor):
 
         if self._participant_id and isinstance(frame, TextFrame):
             await self.push_frame(
-                UserImageRequestFrame(self._participant_id, context=frame.text),
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
-                FrameDirection.UPSTREAM,
             )
-        else:
+        await self.push_frame(frame, direction)
-            await self.push_frame(frame, direction)
-
-
-class UserImageProcessor(FrameProcessor):
-    """Converts incoming user images into context frames."""
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, UserImageRawFrame):
-            if frame.request and frame.request.context:
-                context = LLMContext()
-                context.add_image_frame_message(
-                    image=frame.image,
-                    text=frame.request.context,
-                    size=frame.size,
-                    format=frame.format,
-                )
-                frame = LLMContextFrame(context)
-                await self.push_frame(frame)
-        else:
-            await self.push_frame(frame, direction)
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -94,15 +59,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -115,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Initialize the image requester without setting the participant ID yet
     image_requester = UserImageRequester()
 
-    image_processor = UserImageProcessor()
+    vision_aggregator = VisionImageFrameAggregator()
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
@@ -133,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             stt,
             user_response,
             image_requester,
-            image_processor,
+            vision_aggregator,
             openai,
             tts,
             transport.output(),
@@ -160,7 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me about what I see."))
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):

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

@@ -10,23 +10,13 @@ from typing import Optional
 from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import Frame, TextFrame, TTSSpeakFrame, UserImageRequestFrame
-from pipecat.frames.frames import (
-    Frame,
-    LLMContextFrame,
-    TextFrame,
-    TTSSpeakFrame,
-    UserImageRawFrame,
-    UserImageRequestFrame,
-)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.user_response import UserResponseAggregator
+from pipecat.processors.aggregators.vision_image_frame import VisionImageFrameAggregator
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
@@ -38,14 +28,12 @@ from pipecat.services.anthropic.llm import AnthropicLLMService
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
 
 class UserImageRequester(FrameProcessor):
-    """Converts incoming text into requests for user images."""
-
     def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
@@ -58,32 +46,9 @@ class UserImageRequester(FrameProcessor):
 
         if self._participant_id and isinstance(frame, TextFrame):
             await self.push_frame(
-                UserImageRequestFrame(self._participant_id, context=frame.text),
+                UserImageRequestFrame(self._participant_id), FrameDirection.UPSTREAM
-                FrameDirection.UPSTREAM,
             )
-        else:
+        await self.push_frame(frame, direction)
-            await self.push_frame(frame, direction)
-
-
-class UserImageProcessor(FrameProcessor):
-    """Converts incoming user images into context frames."""
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, UserImageRawFrame):
-            if frame.request and frame.request.context:
-                context = LLMContext()
-                context.add_image_frame_message(
-                    image=frame.image,
-                    text=frame.request.context,
-                    size=frame.size,
-                    format=frame.format,
-                )
-                frame = LLMContextFrame(context)
-                await self.push_frame(frame)
-        else:
-            await self.push_frame(frame, direction)
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -94,15 +59,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -115,7 +78,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     # Initialize the image requester without setting the participant ID yet
     image_requester = UserImageRequester()
 
-    image_processor = UserImageProcessor()
+    vision_aggregator = VisionImageFrameAggregator()
 
     stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
@@ -133,7 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
             stt,
             user_response,
             image_requester,
-            image_processor,
+            vision_aggregator,
             anthropic,
             tts,
             transport.output(),
@@ -160,7 +123,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         image_requester.set_participant_id(client_id)
 
         # Welcome message
-        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me about what I see."))
+        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me what I see."))
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):

examples/foundational/12d-describe-video-aws.py

@@ -1,192 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-from typing import Optional
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import (
-    Frame,
-    LLMContextFrame,
-    TextFrame,
-    TTSSpeakFrame,
-    UserImageRawFrame,
-    UserImageRequestFrame,
-)
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.processors.aggregators.user_response import UserResponseAggregator
-from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import (
-    create_transport,
-    get_transport_client_id,
-    maybe_capture_participant_camera,
-)
-from pipecat.services.aws.llm import AWSBedrockLLMService
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-
-load_dotenv(override=True)
-
-
-class UserImageRequester(FrameProcessor):
-    """Converts incoming text into requests for user images."""
-
-    def __init__(self, participant_id: Optional[str] = None):
-        super().__init__()
-        self._participant_id = participant_id
-
-    def set_participant_id(self, participant_id: str):
-        self._participant_id = participant_id
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if self._participant_id and isinstance(frame, TextFrame):
-            await self.push_frame(
-                UserImageRequestFrame(self._participant_id, context=frame.text),
-                FrameDirection.UPSTREAM,
-            )
-        else:
-            await self.push_frame(frame, direction)
-
-
-class UserImageProcessor(FrameProcessor):
-    """Converts incoming user images into context frames."""
-
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, UserImageRawFrame):
-            if frame.request and frame.request.context:
-                # Note: AWS Bedrock does not yet support the universal LLMContext
-                context = LLMContext()
-                context.add_image_frame_message(
-                    image=frame.image,
-                    text=frame.request.context,
-                    size=frame.size,
-                    format=frame.format,
-                )
-                frame = LLMContextFrame(context)
-                await self.push_frame(frame)
-        else:
-            await self.push_frame(frame, direction)
-
-
-# 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,
-        video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    user_response = UserResponseAggregator()
-
-    # Initialize the image requester without setting the participant ID yet
-    image_requester = UserImageRequester()
-
-    image_processor = UserImageProcessor()
-
-    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-    # AWS for vision analysis
-    aws = AWSBedrockLLMService(
-        aws_region="us-west-2",
-        model="us.anthropic.claude-3-7-sonnet-20250219-v1:0",
-        # Note: usually, prefer providing latency="optimized" param.
-        # Here we can't because AWS Bedrock doesn't support it for Claude 3.7,
-        # which we need for image input.
-        params=AWSBedrockLLMService.InputParams(temperature=0.8),
-    )
-
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
-        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-    )
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            stt,
-            user_response,
-            image_requester,
-            image_processor,
-            aws,
-            tts,
-            transport.output(),
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected: {client}")
-
-        await maybe_capture_participant_camera(transport, client)
-
-        # Set the participant ID in the image requester
-        client_id = get_transport_client_id(transport, client)
-        image_requester.set_participant_id(client_id)
-
-        # Welcome message
-        await task.queue_frame(TTSSpeakFrame("Hi there! Feel free to ask me about what I see."))
-
-    @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=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/13-whisper-transcription.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.whisper.stt import WhisperSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -31,9 +31,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

examples/foundational/13a-whisper-local.py

@@ -32,9 +32,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 async def main():
     transport = LocalAudioTransport(

examples/foundational/13b-deepgram-transcription.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService, Language, LiveOptions
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -31,9 +31,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

examples/foundational/13c-gladia-transcription.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.gladia import GladiaSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -31,9 +31,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

examples/foundational/13c-gladia-translation.py

@@ -25,8 +25,8 @@ from pipecat.services.gladia.config import (
 from pipecat.services.gladia.stt import GladiaSTTService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -40,9 +40,6 @@ class TranscriptionLogger(FrameProcessor):
         elif isinstance(frame, TranslationFrame):
             print(f"Translation ({frame.language}): {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

examples/foundational/13d-assemblyai-transcription.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.assemblyai.stt import AssemblyAISTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -31,9 +31,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

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

@@ -20,8 +20,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.whisper.stt import MLXModel, WhisperSTTServiceMLX
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -52,9 +52,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             self._last_transcription_time = time.time()
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

examples/foundational/13f-cartesia-transcription.py

@@ -18,8 +18,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.stt import CartesiaSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -31,9 +31,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

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

@@ -21,8 +21,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.sambanova.stt import SambaNovaSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -53,9 +53,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             self._last_transcription_time = time.time()
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

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

@@ -19,8 +19,8 @@ from pipecat.runner.utils import create_transport
 from pipecat.services.speechmatics.stt import SpeechmaticsSTTService
 from pipecat.transcriptions.language import Language
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -32,9 +32,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets

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

@@ -19,8 +19,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.soniox.stt import SonioxSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -32,9 +32,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 transport_params = {
     "daily": lambda: DailyParams(

examples/foundational/13j-azure-transcription.py

@@ -19,8 +19,8 @@ from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.azure.stt import AzureSTTService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -32,9 +32,6 @@ class TranscriptionLogger(FrameProcessor):
         if isinstance(frame, TranscriptionFrame):
             print(f"Transcription: {frame.text}")
 
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
 
 transport_params = {
     "daily": lambda: DailyParams(

examples/foundational/13k-elevenlabs-transcription.py

@@ -1,89 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-import aiohttp
-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.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.elevenlabs.stt import ElevenLabsSTTService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-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}")
-
-        # Push all frames through
-        await self.push_frame(frame, direction)
-
-
-# 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()),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()
-    ),
-    "webrtc": lambda: TransportParams(audio_in_enabled=True, vad_analyzer=SileroVADAnalyzer()),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    async with aiohttp.ClientSession() as session:
-        stt = ElevenLabsSTTService(
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            aiohttp_session=session,
-        )
-
-        tl = TranscriptionLogger()
-
-        pipeline = Pipeline([transport.input(), stt, tl])
-
-        task = PipelineTask(
-            pipeline,
-            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-        )
-
-        @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=runner_args.handle_sigint)
-
-        await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/14-function-calling.py

@@ -11,16 +11,12 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -28,8 +24,8 @@ 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.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -49,20 +45,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -124,8 +117,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -12,16 +12,12 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.anthropic.llm import AnthropicLLMService
@@ -29,8 +25,8 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.llm_service import FunctionCallParams
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -51,20 +47,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -119,8 +112,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     messages = [{"role": "user", "content": "Say 'hello' to start the conversation."}]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -13,16 +13,12 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
     create_transport,
@@ -34,7 +30,7 @@ from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.llm_service import FunctionCallParams
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -77,15 +73,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -103,7 +97,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     llm = AnthropicLLMService(
         api_key=os.getenv("ANTHROPIC_API_KEY"),
         model="claude-3-7-sonnet-latest",
-        params=AnthropicLLMService.InputParams(enable_prompt_caching=True),
+        enable_prompt_caching_beta=True,
     )
     llm.register_function("get_weather", get_weather)
     llm.register_function("get_image", get_image)
@@ -166,8 +160,8 @@ If you need to use a tool, simply use the tool. Do not tell the user the tool yo
         {"role": "user", "content": "Start the conversation by introducing yourself."},
     ]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -12,16 +12,12 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -29,8 +25,8 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.llm_service import FunctionCallParams
 from pipecat.services.together.llm import TogetherLLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -46,20 +42,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -110,8 +103,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -13,16 +13,12 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
     create_transport,
@@ -34,7 +30,7 @@ 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.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -77,15 +73,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -155,8 +149,8 @@ indicate you should use the get_image tool are:
         {"role": "system", "content": system_prompt},
     ]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -13,16 +13,12 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import (
     create_transport,
@@ -34,7 +30,7 @@ from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.google.llm import GoogleLLMService
 from pipecat.services.llm_service import FunctionCallParams
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -81,15 +77,13 @@ transport_params = {
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
         video_in_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -176,8 +170,8 @@ indicate you should use the get_image tool are:
         {"role": "user", "content": "Say hello."},
     ]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(context)
+    context_aggregator = llm.create_context_aggregator(context)
 
     pipeline = Pipeline(
         [

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

@@ -12,17 +12,13 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
-from pipecat.audio.turn.smart_turn.base_smart_turn import SmartTurnParams
-from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import LocalSmartTurnAnalyzerV3
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.processors.aggregators.llm_response import LLMUserAggregatorParams
-from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.cartesia.tts import CartesiaTTSService
@@ -30,8 +26,8 @@ from pipecat.services.groq.llm import GroqLLMService
 from pipecat.services.groq.stt import GroqSTTService
 from pipecat.services.llm_service import FunctionCallParams
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.transports.services.daily import DailyParams
 
 load_dotenv(override=True)
 
@@ -47,20 +43,17 @@ transport_params = {
     "daily": lambda: DailyParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "twilio": lambda: FastAPIWebsocketParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
     "webrtc": lambda: TransportParams(
         audio_in_enabled=True,
         audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.2)),
+        vad_analyzer=SileroVADAnalyzer(),
-        turn_analyzer=LocalSmartTurnAnalyzerV3(params=SmartTurnParams()),
     ),
 }
 
@@ -108,8 +101,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = LLMContext(messages, tools)
+    context = OpenAILLMContext(messages, tools)
-    context_aggregator = LLMContextAggregatorPair(
+    context_aggregator = llm.create_context_aggregator(
         context, user_params=LLMUserAggregatorParams(aggregation_timeout=0.05)
     )