CartesiaTTSService: reset context id when flushing audio

github: add coverage support

.github/workflows/android.yaml

@@ -0,0 +1,48 @@
+name: android
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - "examples/simple-chatbot/client/android/**"
+  pull_request:
+    branches:
+      - "**"
+    paths:
+      - "examples/simple-chatbot/client/android/**"
+  workflow_dispatch:
+    inputs:
+      sdk_git_ref:
+        type: string
+        description: "Which git ref of the app to build"
+
+concurrency:
+  group: build-android-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  sdk:
+    name: "Simple chatbot demo"
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ github.event.inputs.sdk_git_ref || github.ref }}
+
+      - name: "Install Java"
+        uses: actions/setup-java@v4
+        with:
+          distribution: 'temurin'
+          java-version: '17'
+
+      - name: Build demo app
+        working-directory: examples/simple-chatbot/client/android
+        run: ./gradlew :simple-chatbot-client:assembleDebug
+
+      - name: Upload demo APK
+        uses: actions/upload-artifact@v4
+        with:
+          name: Simple Chatbot Android Client
+          path: examples/simple-chatbot/client/android/simple-chatbot-client/build/outputs/apk/debug/simple-chatbot-client-debug.apk

.github/workflows/coverage.yaml

@@ -0,0 +1,54 @@
+name: coverage
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - "**"
+    paths-ignore:
+      - "docs/**"
+
+jobs:
+  coverage:
+    name: "Coverage"
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+      - name: Set up Python
+        id: setup_python
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.10"
+      - name: Cache virtual environment
+        uses: actions/cache@v3
+        with:
+          # We are hashing dev-requirements.txt and test-requirements.txt which
+          # contain all dependencies needed to run the tests.
+          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('dev-requirements.txt') }}-${{ hashFiles('test-requirements.txt') }}
+          path: .venv
+      - name: Install system packages
+        id: install_system_packages
+        run: |
+          sudo apt-get install -y portaudio19-dev
+      - name: Setup virtual environment
+        run: |
+          python -m venv .venv
+      - name: Install basic Python dependencies
+        run: |
+          source .venv/bin/activate
+          python -m pip install --upgrade pip
+          pip install -r dev-requirements.txt -r test-requirements.txt
+      - name: Run tests with coverage
+        run: |
+          source .venv/bin/activate
+          coverage run
+          coverage xml
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+          slug: pipecat-ai/pipecat

.github/workflows/tests.yaml

@@ -1,4 +1,4 @@
-name: test
+name: tests
 
 on:
   workflow_dispatch:
@@ -49,4 +49,4 @@ jobs:
       - name: Test with pytest
         run: |
           source .venv/bin/activate
-          pytest --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
+          pytest

.pre-commit-config.yaml

@@ -0,0 +1,7 @@
+repos:
+  - repo: local
+    hooks:
+      - id: ruff-format-hook
+        name: Check ruff formatting
+        entry: sh scripts/pre-commit.sh
+        language: system

CHANGELOG.md

@@ -5,6 +5,409 @@ All notable changes to **Pipecat** will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Added
+
+- Added support for Groq's Whisper API through the new `GroqSTTService` and
+  OpenAI's Whisper API through the new `OpenAISTTService`. Introduced a new
+  base class `BaseWhisperSTTService` to handle common Whisper API
+  functionality.
+
+- Added `PerplexityLLMService` for Perplexity NIM API integration, with an
+  OpenAI-compatible interface. Also, added foundational example
+  `14n-function-calling-perplexity.py`.
+
+- Added `DailyTransport.update_remote_participants()`. This allows you to update remote participant's settings, like their permissions or which of their devices are enabled. Requires that the local participant have participant admin permission.
+
+### Changed
+
+- Improved error handling in `AzureTTSService` to properly detect and log
+  synthesis cancellation errors.
+
+- Enhanced `WhisperSTTService` with full language support and improved model
+  documentation.
+
+- Updated foundation example `14f-function-calling-groq.py` to use
+  `GroqSTTService` for transcription.
+
+- Updated `GroqLLMService` to use `llama-3.3-70b-versatile` as the default
+  model.
+
+- `RTVIObserver` doesn't handle `LLMSearchResponseFrame` frames anymore. For
+  now, to handle those frames you need to create a `GoogleRTVIObserver` instead.
+
+### Deprecated
+
+- `STTMuteFilter` constructor's `stt_service` parameter is now deprecated and
+  will be removed in a future version. The filter now manages mute state
+  internally instead of querying the STT service.
+
+- `RTVI.observer()` is now deprecated, instantiate an `RTVIObserver` directly
+  instead.
+
+- All RTVI frame processors (e.g. `RTVISpeakingProcessor`,
+  `RTVIBotLLMProcessor`) are now deprecated, instantiate an `RTVIObserver`
+  instead.
+
+### Fixed
+
+- Fixed a `CartesiaTTSService` issue that could cause audio overlapping in some
+  cases.
+
+- Fixed an issue that was causing `AudioBufferProcessor` to not record
+  synchronized audio.
+
+- Fixed an `RTVI` issue that was causing `bot-tts-text` messages to be sent
+  before being processed by the output transport.
+
+- Fixed an issue[#1192] in 11labs where we are trying to reconnect/disconnect the
+  websocket connection even when the connection is already closed.
+
+## [0.0.56] - 2025-02-06
+
+### Changed
+
+- Use `gemini-2.0-flash-001` as the default model for `GoogleLLMSerivce`.
+
+- Improved foundational examples 22b, 22c, and 22d to support function calling.
+  With these base examples, `FunctionCallInProgressFrame` and
+  `FunctionCallResultFrame` will no longer be blocked by the gates.
+
+### Fixed
+
+- Fixed a `TkLocalTransport` and `LocalAudioTransport` issues that was causing
+  errors on cleanup.
+
+- Fixed an issue that was causing `tests.utils` import to fail because of
+  logging setup.
+
+- Fixed a `SentryMetrics` issue that was preventing any metrics to be sent to
+  Sentry and also was preventing from metrics frames to be pushed to the pipeline.
+
+- Fixed an issue in `BaseOutputTransport` where incoming audio would not be
+  resampled to the desired output sample rate.
+
+- Fixed an issue with the `TwilioFrameSerializer` and `TelnyxFrameSerializer`
+  where `twilio_sample_rate` and `telnyx_sample_rate` were incorrectly
+  initialized to `audio_in_sample_rate`. Those values currently default to 8000
+  and should be set manually from the serializer constructor if a different
+  value is needed.
+
+### Other
+
+- Added a new `sentry-metrics` example.
+
+## [0.0.55] - 2025-02-05
+
+### Added
+
+- Added a new `start_metadata` field to `PipelineParams`. The provided metadata
+  will be set to the initial `StartFrame` being pushed from the `PipelineTask`.
+
+- Added new fields to `PipelineParams` to control audio input and output sample
+  rates for the whole pipeline. This allows controlling sample rates from a
+  single place instead of having to specify sample rates in each
+  service. Setting a sample rate to a service is still possible and will
+  override the value from `PipelineParams`.
+
+- Introduce audio resamplers (`BaseAudioResampler`). This is just a base class
+  to implement audio resamplers. Currently, two implementations are provided
+  `SOXRAudioResampler` and `ResampyResampler`. A new
+  `create_default_resampler()` has been added (replacing the now deprecated
+  `resample_audio()`).
+
+- It is now possible to specify the asyncio event loop that a `PipelineTask` and
+  all the processors should run on by passing it as a new argument to the
+  `PipelineRunner`. This could allow running pipelines in multiple threads each
+  one with its own event loop.
+
+- Added a new `utils.TaskManager`. Instead of a global task manager we now have
+  a task manager per `PipelineTask`. In the previous version the task manager
+  was global, so running multiple simultaneous `PipelineTask`s could result in
+  dangling task warnings which were not actually true. In order, for all the
+  processors to know about the task manager, we pass it through the
+  `StartFrame`. This means that processors should create tasks when they receive
+  a `StartFrame` but not before (because they don't have a task manager yet).
+
+- Added `TelnyxFrameSerializer` to support Telnyx calls. A full running example
+  has also been added to `examples/telnyx-chatbot`.
+
+- Allow pushing silence audio frames before `TTSStoppedFrame`. This might be
+  useful for testing purposes, for example, passing bot audio to an STT service
+  which usually needs additional audio data to detect the utterance stopped.
+
+- `TwilioSerializer` now supports transport message frames. With this we can
+  create Twilio emulators.
+
+- Added a new transport: `WebsocketClientTransport`.
+
+- Added a `metadata` field to `Frame` which makes it possible to pass custom
+  data to all frames.
+
+- Added `test/utils.py` inside of pipecat package.
+
+### Changed
+
+- `GatedOpenAILLMContextAggregator` now require keyword arguments. Also, a new
+  `start_open` argument has been added to set the initial state of the gate.
+
+- Added `organization` and `project` level authentication to
+  `OpenAILLMService`.
+
+- Improved the language checking logic in `ElevenLabsTTSService` and
+  `ElevenLabsHttpTTSService` to properly handle language codes based on model
+  compatibility, with appropriate warnings when language codes cannot be
+  applied.
+
+- Updated `GoogleLLMContext` to support pushing `LLMMessagesUpdateFrame`s that
+  contain a combination of function calls, function call responses, system
+  messages, or just messages.
+
+- `InputDTMFFrame` is now based on `DTMFFrame`. There's also a new
+  `OutputDTMFFrame` frame.
+
+### Deprecated
+
+- `resample_audio()` is now deprecated, use `create_default_resampler()`
+  instead.
+
+### Removed
+
+- `AudioBufferProcessor.reset_audio_buffers()` has been removed, use
+  `AudioBufferProcessor.start_recording()` and
+  `AudioBufferProcessor.stop_recording()` instead.
+
+### Fixed
+
+- Fixed a `AudioBufferProcessor` that would cause crackling in some recordings.
+
+- Fixed an issue in `AudioBufferProcessor` where user callback would not be
+  called on task cancellation.
+
+- Fixed an issue in `AudioBufferProcessor` that would cause wrong silence
+  padding in some cases.
+
+- Fixed an issue where `ElevenLabsTTSService` messages would return a 1009
+  websocket error by increasing the max message size limit to 16MB.
+
+- Fixed a `DailyTransport` issue that would cause events to be triggered before
+  join finished.
+
+- Fixed a `PipelineTask` issue that was preventing processors to be cleaned up
+  after cancelling the task.
+
+- Fixed an issue where queuing a `CancelFrame` to a pipeline task would not
+  cause the task to finish. However, using `PipelineTask.cancel()` is still the
+  recommended way to cancel a task.
+
+### Other
+
+- Improved Unit Test `run_test()` to use `PipelineTask` and
+  `PipelineRunner`. There's now also some control around `StartFrame` and
+  `EndFrame`. The `EndTaskFrame` has been removed since it doesn't seem
+  necessary with this new approach.
+
+- Updated `twilio-chatbot` with a few new features: use 8000 sample rate and
+  avoid resampling, a new client useful for stress testing and testing locally
+  without the need to make phone calls. Also, added audio recording on both the
+  client and the server to make sure the audio sounds good.
+
+- Updated examples to use `task.cancel()` to immediately exit the example when a
+  participant leaves or disconnects, instead of pushing an `EndFrame`. Pushing
+  an `EndFrame` causes the bot to run through everything that is internally
+  queued (which could take some seconds). Note that using `task.cancel()` might
+  not always be the best option and pushing an `EndFrame` could still be
+  desirable to make sure all the pipeline is flushed.
+
+## [0.0.54] - 2025-01-27
+
+### Added
+
+- In order to create tasks in Pipecat frame processors it is now recommended to
+  use `FrameProcessor.create_task()` (which uses the new
+  `utils.asyncio.create_task()`). It takes care of uncaught exceptions, task
+  cancellation handling and task management. To cancel or wait for a task there
+  is `FrameProcessor.cancel_task()` and `FrameProcessor.wait_for_task()`. All of
+  Pipecat processors have been updated accordingly. Also, when a pipeline runner
+  finishes, a warning about dangling tasks might appear, which indicates if any
+  of the created tasks was never cancelled or awaited for (using these new
+  functions).
+
+- It is now possible to specify the period of the `PipelineTask` heartbeat
+  frames with `heartbeats_period_secs`.
+
+- Added `DailyMeetingTokenProperties` and `DailyMeetingTokenParams` Pydantic models
+  for meeting token creation in `get_token` method of `DailyRESTHelper`.
+
+- Added `enable_recording` and `geo` parameters to `DailyRoomProperties`.
+
+- Added `RecordingsBucketConfig` to `DailyRoomProperties` to upload recordings to a custom AWS bucket.
+
+### Changed
+
+- Enhanced `UserIdleProcessor` with retry functionality and control over idle
+  monitoring via new callback signature `(processor, retry_count) -> bool`.
+  Updated the `17-detect-user-idle.py` to show how to use the `retry_count`.
+
+- Add defensive error handling for `OpenAIRealtimeBetaLLMService`'s audio
+  truncation. Audio truncation errors during interruptions now log a warning
+  and allow the session to continue instead of throwing an exception.
+
+- Modified `TranscriptProcessor` to use TTS text frames for more accurate assistant
+  transcripts. Assistant messages are now aggregated based on bot speaking boundaries
+  rather than LLM context, providing better handling of interruptions and partial
+  utterances.
+
+- Updated foundational examples `28a-transcription-processor-openai.py`,
+  `28b-transcript-processor-anthropic.py`, and
+  `28c-transcription-processor-gemini.py` to use the updated
+  `TranscriptProcessor`.
+
+### Fixed
+
+- Fixed an `GeminiMultimodalLiveLLMService` issue that was preventing the user
+  to push initial LLM assistant messages (using `LLMMessagesAppendFrame`).
+
+- Added missing `FrameProcessor.cleanup()` calls to `Pipeline`,
+  `ParallelPipeline` and `UserIdleProcessor`.
+
+- Fixed a type error when using `voice_settings` in `ElevenLabsHttpTTSService`.
+
+- Fixed an issue where `OpenAIRealtimeBetaLLMService` function calling resulted
+  in an error.
+
+- Fixed an issue in `AudioBufferProcessor` where the last audio buffer was not
+  being processed, in cases where the `_user_audio_buffer` was smaller than the
+  buffer size.
+
+### Performance
+
+- Replaced audio resampling library `resampy` with `soxr`. Resampling a 2:21s
+  audio file from 24KHz to 16KHz took 1.41s with `resampy` and 0.031s with
+  `soxr` with similar audio quality.
+
+### Other
+
+- Added initial unit test infrastructure.
+
+## [0.0.53] - 2025-01-18
+
+### Added
+
+- Added `ElevenLabsHttpTTSService` which uses EleveLabs' HTTP API instead of the
+  websocket one.
+
+- Introduced pipeline frame observers. Observers can view all the frames that go
+  through the pipeline without the need to inject processors in the
+  pipeline. This can be useful, for example, to implement frame loggers or
+  debuggers among other things. The example
+  `examples/foundational/30-observer.py` shows how to add an observer to a
+  pipeline for debugging.
+
+- Introduced heartbeat frames. The pipeline task can now push periodic
+  heartbeats down the pipeline when `enable_heartbeats=True`. Heartbeats are
+  system frames that are supposed to make it all the way to the end of the
+  pipeline. When a heartbeat frame is received the traversing time (i.e. the
+  time it took to go through the whole pipeline) will be displayed (with TRACE
+  logging) otherwise a warning will be shown. The example
+  `examples/foundational/31-heartbeats.py` shows how to enable heartbeats and
+  forces warnings to be displayed.
+
+- Added `LLMTextFrame` and `TTSTextFrame` which should be pushed by LLM and TTS
+  services respectively instead of `TextFrame`s.
+
+- Added `OpenRouter` for OpenRouter integration with an OpenAI-compatible
+  interface. Added foundational example `14m-function-calling-openrouter.py`.
+
+- Added a new `WebsocketService` based class for TTS services, containing
+  base functions and retry logic.
+
+- Added `DeepSeekLLMService` for DeepSeek integration with an OpenAI-compatible
+  interface. Added foundational example `14l-function-calling-deepseek.py`.
+
+- Added `FunctionCallResultProperties` dataclass to provide a structured way to
+  control function call behavior, including:
+
+  - `run_llm`: Controls whether to trigger LLM completion
+  - `on_context_updated`: Optional callback triggered after context update
+
+- Added a new foundational example `07e-interruptible-playht-http.py` for easy
+  testing of `PlayHTHttpTTSService`.
+
+- Added support for Google TTS Journey voices in `GoogleTTSService`.
+
+- Added `29-livekit-audio-chat.py`, as a new foundational examples for
+  `LiveKitTransportLayer`.
+
+- Added `enable_prejoin_ui`, `max_participants` and `start_video_off` params
+  to `DailyRoomProperties`.
+
+- Added `session_timeout` to `FastAPIWebsocketTransport` and
+  `WebsocketServerTransport` for configuring session timeouts (in
+  seconds). Triggers `on_session_timeout` for custom timeout handling.
+  See [examples/websocket-server/bot.py](https://github.com/pipecat-ai/pipecat/blob/main/examples/websocket-server/bot.py).
+
+- Added the new modalities option and helper function to set Gemini output
+  modalities.
+
+- 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
+
+- Modified `UserIdleProcessor` to start monitoring only after first
+  conversation activity (`UserStartedSpeakingFrame` or
+  `BotStartedSpeakingFrame`) instead of immediately.
+
+- Modified `OpenAIAssistantContextAggregator` to support controlled completions
+  and to emit context update callbacks via `FunctionCallResultProperties`.
+
+- Added `aws_session_token` to the `PollyTTSService`.
+
+- Changed the default model for `PlayHTHttpTTSService` to `Play3.0-mini-http`.
+
+- `api_key`, `aws_access_key_id` and `region` are no longer required parameters
+  for the PollyTTSService (AWSTTSService)
+
+- Added `session_timeout` example in `examples/websocket-server/bot.py` to
+  handle session timeout event.
+
+- Changed `InputParams` in
+  `src/pipecat/services/gemini_multimodal_live/gemini.py` to support different
+  modalities.
+
+- Changed `DeepgramSTTService` to send `finalize` event whenever VAD detects
+  `UserStoppedSpeakingFrame`. This helps in faster transcriptions and clearing
+  the `Deepgram` audio buffer.
+
+### Fixed
+
+- Fixed an issue where `DeepgramSTTService` was not generating metrics using
+  pipeline's VAD.
+
+- Fixed `UserIdleProcessor` not properly propagating `EndFrame`s through the
+  pipeline.
+
+- Fixed an issue where websocket based TTS services could incorrectly terminate
+  their connection due to a retry counter not resetting.
+
+- Fixed a `PipelineTask` issue that would cause a dangling task after stopping
+  the pipeline with an `EndFrame`.
+
+- Fixed an import issue for `PlayHTHttpTTSService`.
+
+- Fixed an issue where languages couldn't be used with the `PlayHTHttpTTSService`.
+
+- Fixed an issue where `OpenAIRealtimeBetaLLMService` audio chunks were hitting
+  an error when truncating audio content.
+
+- Fixed an issue where setting the voice and model for `RimeHttpTTSService`
+  wasn't working.
+
+- Fixed an issue where `IdleFrameProcessor` and `UserIdleProcessor` were getting
+  initialized before the start of the pipeline.
+
 ## [0.0.52] - 2024-12-24
 
 ### Added
@@ -1264,6 +1667,9 @@ async def on_connected(processor):
 
 ### Changed
 
+- `FrameSerializer.serialize()` and `FrameSerializer.deserialize()` are now
+  `async`.
+
 - `Filter` has been renamed to `FrameFilter` and it's now under
   `processors/filters`.
 

LICENSE

@@ -1,6 +1,6 @@
 BSD 2-Clause License
 
-Copyright (c) 2024, Daily
+Copyright (c) 2024–2025, Daily
 
 Redistribution and use in source and binary forms, with or without
 modification, are permitted provided that the following conditions are met:

README.md

@@ -2,7 +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) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat) <a href="https://app.commanddash.io/agent/github_pipecat-ai_pipecat"><img src="https://img.shields.io/badge/AI-Code%20Agent-EB9FDA"></a>
+[![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)
 
 Pipecat is an open source Python framework for building voice and multimodal conversational agents. It handles the complex orchestration of AI services, network transport, audio processing, and multimodal interactions, letting you focus on creating engaging experiences.
 
@@ -53,19 +53,19 @@ To keep things lightweight, only the core framework is included by default. If y
 pip install "pipecat-ai[option,...]"
 ```
 
-Available options include:
+### Available services
 
-| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | Install Command Example                 |
-| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
-| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                                                                                                                                                                                                                                                                                                                                                                                                                               | `pip install "pipecat-ai[deepgram]"`    |
-| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                      | `pip install "pipecat-ai[openai]"`      |
-| Text-to-Speech      | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"`    |
-| Speech-to-Speech    | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            | `pip install "pipecat-ai[openai]"`      |
-| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), WebSocket, Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    | `pip install "pipecat-ai[daily]"`       |
-| Video               | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     | `pip install "pipecat-ai[tavus,simli]"` |
-| Vision & Image      | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     | `pip install "pipecat-ai[moondream]"`   |
-| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                | `pip install "pipecat-ai[silero]"`      |
-| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | `pip install "pipecat-ai[canonical]"`   |
+| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | Install Command Example                 |
+| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
+| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                                                                                                                                                                                                                                                                                                                                                                                                                                                            | `pip install "pipecat-ai[deepgram]"`    |
+| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"`      |
+| Text-to-Speech      | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts)                                                                                                                                                                          | `pip install "pipecat-ai[cartesia]"`    |
+| Speech-to-Speech    | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                     | `pip install "pipecat-ai[google]"`      |
+| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      | `pip install "pipecat-ai[daily]"`       |
+| Video               | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | `pip install "pipecat-ai[tavus,simli]"` |
+| Vision & Image      | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              | `pip install "pipecat-ai[moondream]"`   |
+| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          | `pip install "pipecat-ai[silero]"`      |
+| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | `pip install "pipecat-ai[canonical]"`   |
 
 📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
 
@@ -81,7 +81,7 @@ Here is a very basic Pipecat bot that greets a user when they join a real-time s
 ```python
 import asyncio
 
-from pipecat.frames.frames import EndFrame, TextFrame
+from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.task import PipelineTask
 from pipecat.pipeline.runner import PipelineRunner
@@ -122,7 +122,7 @@ async def main():
   # Register an event handler to exit the application when the user leaves.
   @transport.event_handler("on_participant_left")
   async def on_participant_left(transport, participant, reason):
-    await task.queue_frame(EndFrame())
+    await task.cancel()
 
   # Run the pipeline task
   await runner.run(task)
@@ -149,27 +149,40 @@ Sign up [here](https://dashboard.daily.co/u/signup) and [create a room](https://
 
 ## Hacking on the framework itself
 
-_Note that you may need to set up a virtual environment before following the instructions below. For instance, you might need to run the following from the root of the repo:_
+_Note: You may need to set up a virtual environment before following these instructions. From the root of the repo:_
 
 ```shell
 python3 -m venv venv
 source venv/bin/activate
 ```
 
-From the root of this repo, run the following:
+Install the development dependencies:
 
 ```shell
 pip install -r dev-requirements.txt
-python -m build
 ```
 
-This builds the package. To use the package locally (e.g. to run sample files), run
+Install the git pre-commit hooks (these help ensure your code follows project rules):
 
 ```shell
-pip install --editable ".[option,...]"
+pre-commit install
 ```
 
-If you want to use this package from another directory, you can run:
+Install the `pipecat-ai` package locally in editable mode:
+
+```shell
+pip install -e .
+```
+
+The `-e` or `--editable` option allows you to modify the code without reinstalling.
+
+To include optional dependencies, add them to the install command. For example:
+
+```shell
+pip install -e ".[daily,deepgram,cartesia,openai,silero]"     # Updated for the services you're using
+```
+
+If you want to use this package from another directory:
 
 ```shell
 pip install "path_to_this_repo[option,...]"
@@ -180,7 +193,7 @@ pip install "path_to_this_repo[option,...]"
 From the root directory, run:
 
 ```shell
-pytest --doctest-modules --ignore-glob="*to_be_updated*" --ignore-glob=*pipeline_source* src tests
+pytest
 ```
 
 ## Setting up your editor

dev-requirements.txt

@@ -1,9 +1,12 @@
 build~=1.2.2
-grpcio-tools~=1.68.1
+coverage~=7.6.12
+grpcio-tools~=1.67.1
 pip-tools~=7.4.1
-pyright~=1.1.390
+pre-commit~=4.0.1
+pyright~=1.1.393
 pytest~=8.3.4
-ruff~=0.8.3
-setuptools~=75.6.0
+pytest-asyncio~=0.25.2
+ruff~=0.9.5
+setuptools~=70.0.0
 setuptools_scm~=8.1.0
 python-dotenv~=1.0.1

dot-env.template

@@ -60,3 +60,27 @@ SIMLI_FACE_ID=...
 
 # Krisp
 KRISP_MODEL_PATH=...
+
+# DeepSeek
+DEEPSEEK_API_KEY=...
+
+# Groq
+GROQ_API_KEY=...
+
+# Grok
+GROK_API_KEY=...
+
+# Together.ai
+TOGETHER_API_KEY=...
+
+# Cerebras
+CEREBRAS_API_KEY=...
+
+# Fish Audio
+FISH_API_KEY=...
+
+# Assembly AI
+ASSEMBLYAI_API_KEY=...
+
+# OpenRouter
+OPENROUTER_API_KEY=...

examples/README.md

@@ -39,10 +39,10 @@ Next, follow the steps in the README for each demo.
 | [Translation Chatbot](translation-chatbot)   | Listens for user speech, then translates that speech to Spanish and speaks the translation back. Demonstrates multi-participant use-cases. | Deepgram, Azure, OpenAI, Daily, Daily Prebuilt UI                 |
 | [Moondream Chatbot](moondream-chatbot)       | Demonstrates how to add vision capabilities to GPT4. **Note: works best with a GPU**                                                       | Deepgram, ElevenLabs, OpenAI, Moondream, Daily, Daily Prebuilt UI |
 | [Patient intake](patient-intake)             | A chatbot that can call functions in response to user input.                                                                               | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI            |
-| [Dialin Chatbot](dialin-chatbot)             | A chatbot that connects to an incoming phone call from Daily or Twilio.                                                                    | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
+| [Phone Chatbot](phone-chatbot)             | A chatbot that connects to PSTN/SIP phone calls, powered by Daily or Twilio.                                                                    | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
 | [Twilio Chatbot](twilio-chatbot)             | A chatbot that connects to an incoming phone call from Twilio.                                                                             | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
 | [studypal](studypal)                         | A chatbot to have a conversation about any article on the web                                                                              |                                                                   |
-| [WebSocket Chatbot Server](websocket-server) | A real-time websocket server that handles audio streaming and bot interactions with speech-to-text and text-to-speech capabilities | `python-websockets`, `openai`, `deepgram`, `silero-tts`, `numpy` |
+| [WebSocket Chatbot Server](websocket-server) | A real-time websocket server that handles audio streaming and bot interactions with speech-to-text and text-to-speech capabilities. | Cartesia, Deepgram, OpenAI, Websockets |
 
 > [!IMPORTANT]
 > These example projects use Daily as a WebRTC transport and can be joined using their hosted Prebuilt UI.

examples/bot-ready-signalling/README.md

@@ -0,0 +1,45 @@
+# Bot ready signaling
+
+A simple Pipecat example demonstrating how to handle signaling between the client and the bot, 
+ensuring that the bot starts sending audio only when the client is available, 
+thereby avoiding the risk of cutting off the beginning of the audio.
+
+## Quick Start
+
+### First, start the bot server:
+
+1. Navigate to the server directory:
+   ```bash
+   cd server
+   ```
+2. Create and activate a virtual environment:
+   ```bash
+   python3 -m venv venv
+   source venv/bin/activate  # On Windows: venv\Scripts\activate
+   ```
+3. Install requirements:
+   ```bash
+   pip install -r requirements.txt
+   ```
+4. Copy env.example to .env and configure:
+   - Add your API keys
+5. Start the server:
+   ```bash
+   python server.py
+   ```
+
+### Next, connect using the client app:
+
+For client-side setup, refer to the [JavaScript Guide](client/javascript/README.md).
+
+## Important Note
+
+Ensure the bot server is running before using any client implementations.
+
+## Requirements
+
+- Python 3.10+
+- Node.js 16+ (for JavaScript)
+- Daily API key
+- Cartesia API key
+- Modern web browser with WebRTC support

examples/bot-ready-signalling/client/javascript/README.md

@@ -6,10 +6,10 @@ Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/
 
 1. Run the bot server. See the [server README](../../README).
 
-2. Navigate to the `examples/javascript` directory:
+2. Navigate to the `client/javascript` directory:
 
 ```bash
-cd examples/javascript
+cd client/javascript
 ```
 
 3. Install dependencies:

examples/bot-ready-signalling/client/javascript/index.html

@@ -0,0 +1,34 @@
+<!DOCTYPE html>
+<html lang="en">
+
+<head>
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <title>AI Chatbot</title>
+</head>
+
+<body>
+  <div class="container">
+    <div class="status-bar">
+      <div class="status">
+        Status: <span id="connection-status">Disconnected</span>
+      </div>
+      <div class="controls">
+        <button id="connect-btn">Connect</button>
+        <button id="disconnect-btn" disabled>Disconnect</button>
+      </div>
+    </div>
+
+    <audio id="bot-audio" autoplay></audio>
+
+    <div class="debug-panel">
+      <h3>Debug Info</h3>
+      <div id="debug-log"></div>
+    </div>
+  </div>
+
+  <script type="module" src="/src/app.js"></script>
+  <link rel="stylesheet" href="/src/style.css">
+</body>
+
+</html>

examples/bot-ready-signalling/client/javascript/package.json

@@ -11,11 +11,10 @@
   "author": "",
   "license": "ISC",
   "description": "",
-  "dependencies": {
-    "@daily-co/realtime-ai-daily": "^0.2.1",
-    "realtime-ai": "^0.2.1"
-  },
   "devDependencies": {
-    "vite": "^6.0.2"
+    "vite": "^6.0.9"
+  },
+  "dependencies": {
+    "@daily-co/daily-js": "0.74.0"
   }
 }

examples/bot-ready-signalling/client/javascript/src/app.js

@@ -0,0 +1,216 @@
+/**
+ * Copyright (c) 2024–2025, Daily
+ *
+ * SPDX-License-Identifier: BSD 2-Clause License
+ */
+
+import Daily from "@daily-co/daily-js";
+
+/**
+ * ChatbotClient handles the connection and media management for a real-time
+ * voice interaction with an AI bot.
+ */
+class ChatbotClient {
+  constructor() {
+    // Initialize client state
+    this.dailyCallObject = null;
+    this.setupDOMElements();
+    this.setupEventListeners();
+  }
+
+  /**
+   * Set up references to DOM elements and create necessary media elements
+   */
+  setupDOMElements() {
+    // Get references to UI control elements
+    this.connectBtn = document.getElementById('connect-btn');
+    this.disconnectBtn = document.getElementById('disconnect-btn');
+    this.statusSpan = document.getElementById('connection-status');
+    this.debugLog = document.getElementById('debug-log');
+
+    // Create an audio element for bot's voice output
+    this.botAudio = document.createElement('audio');
+    this.botAudio.autoplay = true;
+    this.botAudio.playsInline = true;
+    document.body.appendChild(this.botAudio);
+  }
+
+  /**
+   * Set up event listeners for connect/disconnect buttons
+   */
+  setupEventListeners() {
+    this.connectBtn.addEventListener('click', () => this.connect());
+    this.disconnectBtn.addEventListener('click', () => this.disconnect());
+  }
+
+  /**
+   * Add a timestamped message to the debug log
+   */
+  log(message) {
+    const entry = document.createElement('div');
+    entry.textContent = `${new Date().toISOString()} - ${message}`;
+
+    // Add styling based on message type
+    if (message.startsWith('User: ')) {
+      entry.style.color = '#2196F3'; // blue for user
+    } else if (message.startsWith('Bot: ')) {
+      entry.style.color = '#4CAF50'; // green for bot
+    }
+
+    this.debugLog.appendChild(entry);
+    this.debugLog.scrollTop = this.debugLog.scrollHeight;
+    console.log(message);
+  }
+
+  /**
+   * Update the connection status display
+   */
+  updateStatus(status) {
+    this.statusSpan.textContent = status;
+    this.log(`Status: ${status}`);
+  }
+
+  handleEventToConsole (evt) {
+    this.log(`Received event: ${evt.action}`);
+  };
+
+  /**
+   * Set up listeners for track events (start/stop)
+   * This handles new tracks being added during the session
+   */
+  setupTrackListeners() {
+    if (!this.dailyCallObject) return;
+
+    this.dailyCallObject.on("joined-meeting", () => {
+      this.updateStatus('Connected');
+      this.connectBtn.disabled = true;
+      this.disconnectBtn.disabled = false;
+      this.log('Client connected');
+    });
+    this.dailyCallObject.on("track-started", (evt) => {
+      if (evt.track.kind === "audio" && evt.participant.local === false) {
+        this.log("Audio track started.")
+        this.setupAudioTrack(evt.track);
+      }
+    });
+    this.dailyCallObject.on("track-stopped", this.handleEventToConsole.bind(this));
+    this.dailyCallObject.on("participant-joined", this.handleEventToConsole.bind(this));
+    this.dailyCallObject.on("participant-updated", this.handleEventToConsole.bind(this));
+    this.dailyCallObject.on("participant-left", () => {
+      // When the bot leaves, we are also disconnecting from the call
+      this.disconnect()
+    });
+    this.dailyCallObject.on("left-meeting", () => {
+      this.updateStatus('Disconnected');
+      this.connectBtn.disabled = false;
+      this.disconnectBtn.disabled = true;
+      this.log('Client disconnected');
+    });
+    this.dailyCallObject.on("error", this.handleEventToConsole.bind(this));
+  }
+
+  /**
+   * Set up an audio track for playback
+   * Handles both initial setup and track updates
+   */
+  setupAudioTrack(track) {
+    this.log(`Setting up audio track, track state: ${track.readyState}, muted: ${track.muted}`);
+
+    // Check if we're already playing this track
+    if (this.botAudio.srcObject) {
+      const oldTrack = this.botAudio.srcObject.getAudioTracks()[0];
+      if (oldTrack?.id === track.id) return;
+    }
+    // Create a new MediaStream with the track and set it as the audio source
+    this.botAudio.srcObject = new MediaStream([track]);
+    this.botAudio.onplaying = async (event) => {
+      this.log("onplaying")
+      this.log("Will send the audio message to play the audio at the next tick")
+      this.dailyCallObject.sendAppMessage("playable")
+    }
+  }
+
+  async fetchRoomInfo() {
+    let connectUrl = '/connect'
+    let res = await fetch(connectUrl, {
+      method: "POST",
+      mode: "cors",
+      headers: new Headers({
+        "Content-Type": "application/json"
+      }),
+    })
+    if (res.ok) {
+      return res.json();
+    }
+  }
+
+  /**
+   * Initialize and connect to the bot
+   * This sets up the RTVI client, initializes devices, and establishes the connection
+   */
+  async connect() {
+    try {
+      // Initialize the client
+      this.dailyCallObject = Daily.createCallObject({
+        subscribeToTracksAutomatically: true,
+      });
+
+      // Set up listeners for media track events
+      this.setupTrackListeners();
+
+      this.log('Creating the bot...');
+      let roomInfo = await this.fetchRoomInfo()
+
+      // Connect to the bot
+      this.log('Connecting to bot...');
+      // Only for making debugger easier
+      window.callObject = this.dailyCallObject;
+      await this.dailyCallObject.join({
+        url: roomInfo.room_url,
+      });
+
+      this.log('Connection complete');
+    } catch (error) {
+      // Handle any errors during connection
+      this.log(`Error connecting: ${error.message}`);
+      this.log(`Error stack: ${error.stack}`);
+      this.updateStatus('Error');
+
+      // Clean up if there's an error
+      if (this.dailyCallObject) {
+        try {
+          await this.dailyCallObject.leave();
+        } catch (disconnectError) {
+          this.log(`Error during disconnect: ${disconnectError.message}`);
+        }
+      }
+    }
+  }
+
+  /**
+   * Disconnect from the bot and clean up media resources
+   */
+  async disconnect() {
+    if (this.dailyCallObject) {
+      try {
+        // Disconnect the RTVI client
+        await this.dailyCallObject.leave();
+        await this.dailyCallObject.destroy();
+        this.dailyCallObject = null;
+
+        // Clean up audio
+        if (this.botAudio.srcObject) {
+          this.botAudio.srcObject.getTracks().forEach((track) => track.stop());
+          this.botAudio.srcObject = null;
+        }
+      } catch (error) {
+        this.log(`Error disconnecting: ${error.message}`);
+      }
+    }
+  }
+}
+
+// Initialize the client when the page loads
+window.addEventListener('DOMContentLoaded', () => {
+  new ChatbotClient();
+});

examples/bot-ready-signalling/client/javascript/vite.config.js

@@ -0,0 +1,13 @@
+import { defineConfig } from 'vite';
+
+export default defineConfig({
+    server: {
+        proxy: {
+            // Proxy /api requests to the backend server
+            '/connect': {
+                target: 'http://0.0.0.0:7860', // Replace with your backend URL
+                changeOrigin: true,
+            },
+        },
+    },
+});

examples/bot-ready-signalling/server/README.md

@@ -0,0 +1,50 @@
+# Bot ready signaling Server
+
+A FastAPI server that manages bot instances and provide endpoint for Pipecat client connections.
+
+## Endpoints
+
+- `POST /connect` - Pipecat client connection endpoint
+
+## Environment Variables
+
+Copy `env.example` to `.env` and configure:
+
+```ini
+# Required API Keys
+DAILY_API_KEY=           # Your Daily API key
+CARTESIA_API_KEY=        # Your Cartesia API key
+
+# Optional Configuration
+DAILY_API_URL=           # Optional: Daily API URL (defaults to https://api.daily.co/v1)
+DAILY_SAMPLE_ROOM_URL=   # Optional: Fixed room URL for development
+HOST=                    # Optional: Host address (defaults to 0.0.0.0)
+FAST_API_PORT=           # Optional: Port number (defaults to 7860)
+```
+
+## Running the Server
+
+Set up and activate your virtual environment:
+
+```bash
+python3 -m venv venv
+source venv/bin/activate  # On Windows: venv\Scripts\activate
+```
+
+Install dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+If you want to use the local version of `pipecat` in this repo rather than the last published version, also run:
+
+```bash
+pip install --editable "../../../[daily,cartesia,openai]"
+```
+
+Run the server:
+
+```bash
+python server.py
+```

examples/bot-ready-signalling/server/env.example

@@ -0,0 +1,3 @@
+DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
+DAILY_API_KEY=
+CARTESIA_API_KEY=

examples/bot-ready-signalling/server/requirements.txt

@@ -0,0 +1,4 @@
+python-dotenv
+fastapi[all]
+uvicorn
+pipecat-ai[daily,cartesia,openai]

examples/bot-ready-signalling/server/runner.py

@@ -0,0 +1,64 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+from typing import Optional
+
+import aiohttp
+
+from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
+
+
+async def configure(aiohttp_session: aiohttp.ClientSession):
+    (url, token, _) = await configure_with_args(aiohttp_session)
+    return (url, token)
+
+
+async def configure_with_args(
+    aiohttp_session: aiohttp.ClientSession, parser: Optional[argparse.ArgumentParser] = None
+):
+    if not parser:
+        parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
+    parser.add_argument(
+        "-u", "--url", type=str, required=False, help="URL of the Daily room to join"
+    )
+    parser.add_argument(
+        "-k",
+        "--apikey",
+        type=str,
+        required=False,
+        help="Daily API Key (needed to create an owner token for the room)",
+    )
+
+    args, unknown = parser.parse_known_args()
+
+    url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
+    key = args.apikey or os.getenv("DAILY_API_KEY")
+
+    if not url:
+        raise Exception(
+            "No Daily room specified. use the -u/--url option from the command line, or set DAILY_SAMPLE_ROOM_URL in your environment to specify a Daily room URL."
+        )
+
+    if not key:
+        raise Exception(
+            "No Daily API key specified. use the -k/--apikey option from the command line, or set DAILY_API_KEY in your environment to specify a Daily API key, available from https://dashboard.daily.co/developers."
+        )
+
+    daily_rest_helper = DailyRESTHelper(
+        daily_api_key=key,
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
+    )
+
+    # Create a meeting token for the given room with an expiration 1 hour in
+    # the future.
+    expiry_time: float = 60 * 60
+
+    token = await daily_rest_helper.get_token(url, expiry_time)
+
+    return (url, token, args)

examples/bot-ready-signalling/server/server.py

@@ -0,0 +1,147 @@
+#
+# Copyright (c) 2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+import subprocess
+from contextlib import asynccontextmanager
+from typing import Any, Dict
+
+import aiohttp
+from dotenv import load_dotenv
+from fastapi import FastAPI, HTTPException, Request
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+
+from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams
+
+# Load environment variables from .env file
+load_dotenv(override=True)
+
+# Dictionary to track bot processes: {pid: (process, room_url)}
+bot_procs = {}
+
+# Store Daily API helpers
+daily_helpers = {}
+
+
+def cleanup():
+    """Cleanup function to terminate all bot processes.
+
+    Called during server shutdown.
+    """
+    for entry in bot_procs.values():
+        proc = entry[0]
+        proc.terminate()
+        proc.wait()
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """FastAPI lifespan manager that handles startup and shutdown tasks.
+
+    - Creates aiohttp session
+    - Initializes Daily API helper
+    - Cleans up resources on shutdown
+    """
+    aiohttp_session = aiohttp.ClientSession()
+    daily_helpers["rest"] = DailyRESTHelper(
+        daily_api_key=os.getenv("DAILY_API_KEY", ""),
+        daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
+        aiohttp_session=aiohttp_session,
+    )
+    yield
+    await aiohttp_session.close()
+    cleanup()
+
+
+# Initialize FastAPI app with lifespan manager
+app = FastAPI(lifespan=lifespan)
+
+# Configure CORS to allow requests from any origin
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+async def create_room_and_token() -> tuple[str, str]:
+    """Helper function to create a Daily room and generate an access token.
+
+    Returns:
+        tuple[str, str]: A tuple containing (room_url, token)
+
+    Raises:
+        HTTPException: If room creation or token generation fails
+    """
+    room = await daily_helpers["rest"].create_room(DailyRoomParams())
+    if not room.url:
+        raise HTTPException(status_code=500, detail="Failed to create room")
+
+    token = await daily_helpers["rest"].get_token(room.url)
+    if not token:
+        raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
+
+    return room.url, token
+
+
+@app.post("/connect")
+async def bot_connect(request: Request) -> Dict[Any, Any]:
+    """Connect endpoint that creates a room and returns connection credentials.
+
+    This endpoint is called by client to establish a connection.
+
+    Returns:
+        Dict[Any, Any]: Authentication bundle containing room_url and token
+
+    Raises:
+        HTTPException: If room creation, token generation, or bot startup fails
+    """
+    print("Creating room for RTVI connection")
+    room_url, token = await create_room_and_token()
+    print(f"Room URL: {room_url}")
+
+    # Start the bot process
+    try:
+        bot_file = "signalling_bot"
+        proc = subprocess.Popen(
+            [f"python3 -m {bot_file} -u {room_url} -t {token}"],
+            shell=True,
+            bufsize=1,
+            cwd=os.path.dirname(os.path.abspath(__file__)),
+        )
+        bot_procs[proc.pid] = (proc, room_url)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}")
+
+    # Return the authentication bundle in format expected by DailyTransport
+    return {"room_url": room_url, "token": token}
+
+
+if __name__ == "__main__":
+    import uvicorn
+
+    # Parse command line arguments for server configuration
+    default_host = os.getenv("HOST", "0.0.0.0")
+    default_port = int(os.getenv("FAST_API_PORT", "7860"))
+
+    parser = argparse.ArgumentParser(description="Daily Travel Companion FastAPI server")
+    parser.add_argument("--host", type=str, default=default_host, help="Host address")
+    parser.add_argument("--port", type=int, default=default_port, help="Port number")
+    parser.add_argument("--reload", action="store_true", help="Reload code on change")
+
+    config = parser.parse_args()
+
+    # Start the FastAPI server
+    uvicorn.run(
+        "server:app",
+        host=config.host,
+        port=config.port,
+        reload=config.reload,
+    )

examples/bot-ready-signalling/server/signalling_bot.py

@@ -0,0 +1,95 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+from dataclasses import dataclass
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+@dataclass
+class SilenceFrame(OutputAudioRawFrame):
+    def __init__(
+        self,
+        *,
+        sample_rate: int,
+        duration: float,
+    ):
+        # Initialize the parent class with the silent frame's data
+        super().__init__(
+            audio=self.create_silent_audio_frame(sample_rate, 1, duration).audio,
+            sample_rate=sample_rate,
+            num_channels=1,
+        )
+
+    @staticmethod
+    def create_silent_audio_frame(
+        sample_rate: int, num_channels: int, duration: float
+    ) -> AudioRawFrame:
+        """Create an AudioRawFrame containing silence."""
+        frame_size = num_channels * 2  # 2 bytes per sample for 16-bit audio
+        total_frames = int(sample_rate * duration)
+        total_bytes = total_frames * frame_size
+        silent_audio = bytes(total_bytes)  # Create a byte array filled with zeros
+        return AudioRawFrame(audio=silent_audio, sample_rate=sample_rate, num_channels=num_channels)
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, _) = await configure(session)
+
+        transport = DailyTransport(
+            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True)
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        runner = PipelineRunner()
+
+        task = PipelineTask(Pipeline([tts, transport.output()]))
+
+        # Register an event handler so we can play the audio when we receive a specific message
+        @transport.event_handler("on_app_message")
+        async def on_app_message(transport, message, sender):
+            logger.debug(f"Received app message: {message} - {sender}")
+            if "playable" not in message:
+                return
+            await task.queue_frames(
+                [
+                    SilenceFrame(
+                        sample_rate=task.params.audio_out_sample_rate,
+                        duration=0.5,
+                    ),
+                    TTSSpeakFrame(f"Hello there, how are you doing today ?"),
+                    EndFrame(),
+                ]
+            )
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/canonical-metrics/bot.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,7 +15,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame
+from pipecat.frames.frames import EndFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -65,7 +65,6 @@ async def main():
             # English
             #
             voice_id="cgSgspJ2msm6clMCkdW9",
-            aiohttp_session=session,
             #
             # Spanish
             #
@@ -97,7 +96,7 @@ async def main():
         call completion, CanonicalMetrics will send the audio buffer to Canonical for
         analysis. Visit https://voice.canonical.chat to learn more.
         """
-        audio_buffer_processor = AudioBufferProcessor()
+        audio_buffer_processor = AudioBufferProcessor(num_channels=2)
         canonical = CanonicalMetricsService(
             audio_buffer_processor=audio_buffer_processor,
             aiohttp_session=session,
@@ -105,6 +104,7 @@ async def main():
             call_id=str(uuid.uuid4()),
             assistant="pipecat-chatbot",
             assistant_speaks_first=True,
+            context=context,
         )
         pipeline = Pipeline(
             [
@@ -123,17 +123,20 @@ async def main():
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
+            await audio_buffer_processor.start_recording()
             await transport.capture_participant_transcription(participant["id"])
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             print(f"Participant left: {participant}")
-            await task.queue_frame(EndFrame())
+            await task.cancel()
 
         @transport.event_handler("on_call_state_updated")
         async def on_call_state_updated(transport, state):
             if state == "left":
+                # Here we don't want to cancel, we just want to finish sending
+                # whatever is queued, so we use an EndFrame().
                 await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()

examples/canonical-metrics/runner.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -53,4 +53,3 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
     token = await daily_rest_helper.get_token(url, expiry_time)
 
     return (url, token)
-    return (url, token)

examples/canonical-metrics/server.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/chatbot-audio-recording/bot.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -18,7 +18,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -83,7 +82,6 @@ async def main():
             # English
             #
             voice_id="cgSgspJ2msm6clMCkdW9",
-            aiohttp_session=session,
             #
             # Spanish
             #
@@ -110,8 +108,9 @@ async def main():
         context = OpenAILLMContext(messages)
         context_aggregator = llm.create_context_aggregator(context)
 
-        # Save audio every 10 seconds.
-        audiobuffer = AudioBufferProcessor(buffer_size=480000)
+        # NOTE: Watch out! This will save all the conversation in memory. You
+        # can pass `buffer_size` to get periodic callbacks.
+        audiobuffer = AudioBufferProcessor()
 
         pipeline = Pipeline(
             [
@@ -133,13 +132,14 @@ async def main():
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
+            await audiobuffer.start_recording()
             await transport.capture_participant_transcription(participant["id"])
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             print(f"Participant left: {participant}")
-            await task.queue_frame(EndFrame())
+            await task.cancel()
 
         runner = PipelineRunner()
 

examples/chatbot-audio-recording/runner.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/chatbot-audio-recording/server.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/deployment/flyio-example/bot.py

@@ -7,7 +7,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame
+from pipecat.frames.frames import EndFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -75,15 +75,17 @@ async def main(room_url: str, token: str):
     @transport.event_handler("on_first_participant_joined")
     async def on_first_participant_joined(transport, participant):
         await transport.capture_participant_transcription(participant["id"])
-        await task.queue_frames([LLMMessagesFrame(messages)])
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
 
     @transport.event_handler("on_participant_left")
     async def on_participant_left(transport, participant, reason):
-        await task.queue_frame(EndFrame())
+        await task.cancel()
 
     @transport.event_handler("on_call_state_updated")
     async def on_call_state_updated(transport, state):
         if state == "left":
+            # Here we don't want to cancel, we just want to finish sending
+            # whatever is queued, so we use an EndFrame().
             await task.queue_frame(EndFrame())
 
     runner = PipelineRunner()

examples/deployment/flyio-example/bot_runner.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/deployment/modal-example/bot.py

@@ -5,6 +5,15 @@ import sys
 from dotenv import load_dotenv
 from loguru import logger
 
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -12,16 +21,6 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def main(room_url: str, token: str):
-    from pipecat.audio.vad.silero import SileroVADAnalyzer
-    from pipecat.frames.frames import EndFrame, LLMMessagesFrame
-    from pipecat.pipeline.pipeline import Pipeline
-    from pipecat.pipeline.runner import PipelineRunner
-    from pipecat.pipeline.task import PipelineParams, PipelineTask
-    from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-    from pipecat.services.cartesia import CartesiaTTSService
-    from pipecat.services.openai import OpenAILLMService
-    from pipecat.transports.services.daily import DailyParams, DailyTransport
-
     transport = DailyTransport(
         room_url,
         token,
@@ -75,11 +74,11 @@ async def main(room_url: str, token: str):
     async def on_first_participant_joined(transport, participant):
         await transport.capture_participant_transcription(participant["id"])
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([LLMMessagesFrame(messages)])
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
 
     @transport.event_handler("on_participant_left")
     async def on_participant_left(transport, participant, reason):
-        await task.queue_frame(EndFrame())
+        await task.cancel()
 
     runner = PipelineRunner()
 

examples/deployment/modal-example/requirements.txt

@@ -1,5 +1,5 @@
 python-dotenv==1.0.1
-modal==0.65.48
-pipecat-ai[daily,silero,cartesia,openai]==0.0.48
-fastapi==0.115.4
-aiohttp==3.11.9
+modal==0.71.3
+pipecat-ai[daily,silero,cartesia,openai]==0.0.52
+fastapi==0.115.6
+aiohttp==3.11.11

examples/dialin-chatbot/README.md

@@ -1,85 +0,0 @@
-<div align="center">
- <img alt="pipecat" width="300px" height="auto" src="image.png">
-</div>
-
-# Dialin example
-
-Example project that demonstrates how to add phone number dialin to your Pipecat bots. We include examples for both Daily (`bot_daily.py`) and Twilio (`bot_twilio.py`), depending on who you want to use as a phone vendor.
-
-- 🔁 Transport: Daily WebRTC
-- 💬 Speech-to-Text: Deepgram via Daily transport
-- 🤖 LLM: GPT4-o / OpenAI
-- 🔉 Text-to-Speech: ElevenLabs
-
-#### Should I use Daily or Twilio as a vendor?
-
-If you're starting from scratch, using Daily to provision phone numbers alongside Daily as a transport offers some convenience (such as automatic call forwarding.)
-
-If you already have Twilio numbers and workflows that you want to connect to your Pipecat bots, there is some additional configuration required (you'll need to create a `on_dialin_ready` and use the Twilio client to trigger the forward.)
-
-You can read more about this, as well as see respective walkthroughs in our docs.
-
-## Setup
-
-```shell
-# Install the requirements
-pip install -r requirements.txt
-
-# Setup your env
-mv env.example .env
-```
-
-## Using Daily numbers
-
-Run `bot_runner.py` to handle incoming HTTP requests:
-
-`python bot_runner.py --host localhost`
-
-Then target the following URL:
-
-`POST /daily_start_bot`
-
-For more configuration options, please consult Daily's API documentation.
-
-
-## Using Twilio numbers
-
-As above, but target the following URL:
-
-`POST /twilio_start_bot`
-
-For more configuration options, please consult Twilio's API documentation.
-
-## Deployment example
-
-A Dockerfile is included in this demo for convenience. Here is an example of how to build and deploy your bot to [fly.io](https://fly.io).
-
-*Please note: This demo spawns agents as subprocesses for convenience / demonstration purposes. You would likely not want to do this in production as it would limit concurrency to available system resources. For more information on how to deploy your bots using VMs, refer to the Pipecat documentation.*
-
-### Build the docker image
-
-`docker build -t tag:project .`
-
-### Launch the fly project
-
-`mv fly.example.toml fly.toml`
-
-`fly launch` (using the included fly.toml)
-
-### Setup your secrets on Fly
-
-Set the necessary secrets (found in `env.example`)
-
-`fly secrets set DAILY_API_KEY=... OPENAI_API_KEY=... ELEVENLABS_API_KEY=... ELEVENLABS_VOICE_ID=...`
-
-If you're using Twilio as a number vendor:
-
-`fly secrets set TWILIO_ACCOUNT_SID=... TWILIO_AUTH_TOKEN=...`
-
-### Deploy!
-
-`fly deploy`
-
-## Need to do something more advanced?
-
-This demo covers the basics of bot telephony. If you want to know more about working with PSTN / SIP, please ping us on [Discord](https://discord.gg/pipecat).

examples/dialin-chatbot/bot_daily.py

@@ -1,103 +0,0 @@
-import argparse
-import asyncio
-import os
-import sys
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.services.elevenlabs import ElevenLabsTTSService
-from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import DailyDialinSettings, DailyParams, DailyTransport
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-daily_api_key = os.getenv("DAILY_API_KEY", "")
-daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
-
-
-async def main(room_url: str, token: str, callId: str, callDomain: str):
-    # diallin_settings are only needed if Daily's SIP URI is used
-    # If you are handling this via Twilio, Telnyx, set this to None
-    # and handle call-forwarding when on_dialin_ready fires.
-    diallin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
-
-    transport = DailyTransport(
-        room_url,
-        token,
-        "Chatbot",
-        DailyParams(
-            api_url=daily_api_url,
-            api_key=daily_api_key,
-            dialin_settings=diallin_settings,
-            audio_in_enabled=True,
-            audio_out_enabled=True,
-            camera_out_enabled=False,
-            vad_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(),
-            transcription_enabled=True,
-        ),
-    )
-
-    tts = ElevenLabsTTSService(
-        api_key=os.getenv("ELEVENLABS_API_KEY", ""),
-        voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
-    )
-
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
-
-    messages = [
-        {
-            "role": "system",
-            "content": "You are Chatbot, a friendly, helpful robot. 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, but keep your responses brief. Start by saying 'Oh, hello! Who dares dial me at this hour?!'.",
-        },
-    ]
-
-    context = OpenAILLMContext(messages)
-    context_aggregator = llm.create_context_aggregator(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            context_aggregator.user(),
-            llm,
-            tts,
-            transport.output(),
-            context_aggregator.assistant(),
-        ]
-    )
-
-    task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
-
-    @transport.event_handler("on_first_participant_joined")
-    async def on_first_participant_joined(transport, participant):
-        await transport.capture_participant_transcription(participant["id"])
-        await task.queue_frames([LLMMessagesFrame(messages)])
-
-    @transport.event_handler("on_participant_left")
-    async def on_participant_left(transport, participant, reason):
-        await task.queue_frame(EndFrame())
-
-    runner = PipelineRunner()
-
-    await runner.run(task)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
-    parser.add_argument("-u", type=str, help="Room URL")
-    parser.add_argument("-t", type=str, help="Token")
-    parser.add_argument("-i", type=str, help="Call ID")
-    parser.add_argument("-d", type=str, help="Call Domain")
-    config = parser.parse_args()
-
-    asyncio.run(main(config.u, config.t, config.i, config.d))

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/foundational/01a-local-audio.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -16,8 +16,7 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
 from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.local.audio import LocalAudioTransport
+from pipecat.transports.local.audio import LocalAudioTransport, LocalTransportParams
 
 load_dotenv(override=True)
 
@@ -26,7 +25,7 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def main():
-    transport = LocalAudioTransport(TransportParams(audio_out_enabled=True))
+    transport = LocalAudioTransport(LocalTransportParams(audio_out_enabled=True))
 
     tts = CartesiaTTSService(
         api_key=os.getenv("CARTESIA_API_KEY"),
@@ -41,7 +40,7 @@ async def main():
         await asyncio.sleep(1)
         await task.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
 
-    runner = PipelineRunner()
+    runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
 
     await asyncio.gather(runner.run(task), say_something())
 

examples/foundational/01c-fastpitch.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/foundational/03-still-frame.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -13,7 +13,7 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
-from pipecat.frames.frames import EndFrame, TextFrame
+from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
@@ -53,7 +53,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.queue_frame(EndFrame())
+            await task.cancel()
 
         await runner.run(task)
 

examples/foundational/03a-local-still-frame.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -0,0 +1,64 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.frames.frames import EndFrame, TextFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.services.google import GoogleImageGenService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, _) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            None,
+            "Show a still frame image",
+            DailyParams(camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024),
+        )
+
+        imagegen = GoogleImageGenService(
+            api_key=os.getenv("GOOGLE_API_KEY"),
+        )
+
+        runner = PipelineRunner()
+
+        task = PipelineTask(
+            Pipeline([imagegen, transport.output()]), PipelineParams(enable_metrics=True)
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await task.queue_frame(TextFrame("a cat in the style of picasso"))
+            await task.queue_frame(TextFrame("a dog in the style of picasso"))
+            await task.queue_frame(TextFrame("a fish in the style of picasso"))
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.queue_frame(EndFrame())
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/04-utterance-and-speech.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -51,7 +51,6 @@ async def main():
         )
 
         elevenlabs_tts = ElevenLabsTTSService(
-            aiohttp_session=session,
             api_key=os.getenv("ELEVENLABS_API_KEY"),
             voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
         )

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, LLMMessagesFrame, MetricsFrame
+from pipecat.frames.frames import Frame, MetricsFrame
 from pipecat.metrics.metrics import (
     LLMUsageMetricsData,
     ProcessingMetricsData,
@@ -38,6 +38,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 class MetricsLogger(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
         if isinstance(frame, MetricsFrame):
             for d in frame.data:
                 if isinstance(d, TTFBMetricsData):
@@ -47,9 +49,7 @@ class MetricsLogger(FrameProcessor):
                 elif isinstance(d, LLMUsageMetricsData):
                     tokens = d.value
                     print(
-                        f"!!! MetricsFrame: {frame}, tokens: {
-                            tokens.prompt_tokens}, characters: {
-                            tokens.completion_tokens}"
+                        f"!!! MetricsFrame: {frame}, tokens: {tokens.prompt_tokens}, characters: {tokens.completion_tokens}"
                     )
                 elif isinstance(d, TTSUsageMetricsData):
                     print(f"!!! MetricsFrame: {frame}, characters: {d.value}")
@@ -113,7 +113,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,10 +15,16 @@ from PIL import Image
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame, OutputImageRawFrame, SystemFrame, TextFrame
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    TextFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.cartesia import CartesiaHttpTTSService
@@ -45,7 +51,7 @@ class ImageSyncAggregator(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if not isinstance(frame, SystemFrame) and direction == FrameDirection.DOWNSTREAM:
+        if isinstance(frame, BotStartedSpeakingFrame):
             await self.push_frame(
                 OutputImageRawFrame(
                     image=self._speaking_image_bytes,
@@ -53,7 +59,8 @@ class ImageSyncAggregator(FrameProcessor):
                     format=self._speaking_image_format,
                 )
             )
-            await self.push_frame(frame)
+
+        elif isinstance(frame, BotStoppedSpeakingFrame):
             await self.push_frame(
                 OutputImageRawFrame(
                     image=self._waiting_image_bytes,
@@ -61,8 +68,8 @@ class ImageSyncAggregator(FrameProcessor):
                     format=self._waiting_image_format,
                 )
             )
-        else:
-            await self.push_frame(frame)
+
+        await self.push_frame(frame)
 
 
 async def main():
@@ -109,16 +116,24 @@ async def main():
         pipeline = Pipeline(
             [
                 transport.input(),
-                image_sync_aggregator,
                 context_aggregator.user(),
                 llm,
                 tts,
+                image_sync_aggregator,
                 transport.output(),
                 context_aggregator.assistant(),
             ]
         )
 
-        task = PipelineTask(pipeline)
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
@@ -126,6 +141,10 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             await task.queue_frames([TextFrame(f"Hi there {participant_name}!")])
 
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
         runner = PipelineRunner()
 
         await runner.run(task)

examples/foundational/07-interruptible-vad.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -13,7 +13,6 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -90,7 +89,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

examples/foundational/07-interruptible.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -88,7 +87,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -78,13 +77,25 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -101,7 +101,15 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
@@ -114,6 +122,10 @@ async def main():
             messages = [({"content": "Please briefly introduce yourself to the user."})]
             await task.queue_frames([LLMMessagesFrame(messages)])
 
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
         runner = PipelineRunner()
 
         await runner.run(task)

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -16,7 +16,6 @@ from runner import configure
 
 from pipecat.frames.frames import (
     BotInterruptionFrame,
-    LLMMessagesFrame,
     StopInterruptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
@@ -80,7 +79,15 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @stt.event_handler("on_speech_started")
         async def on_speech_started(stt, *args, **kwargs):
@@ -94,7 +101,11 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -73,13 +72,25 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -88,7 +87,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,12 +14,12 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
-from pipecat.services.openai import OpenAILLMService, OpenAITTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.services.playht import PlayHTHttpTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -38,14 +38,17 @@ async def main():
             "Respond bot",
             DailyParams(
                 audio_out_enabled=True,
-                audio_out_sample_rate=24000,
                 transcription_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
             ),
         )
 
-        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
+        tts = PlayHTHttpTTSService(
+            user_id=os.getenv("PLAYHT_USER_ID"),
+            api_key=os.getenv("PLAYHT_API_KEY"),
+            voice_url="s3://voice-cloning-zero-shot/d9ff78ba-d016-47f6-b0ef-dd630f59414e/female-cs/manifest.json",
+        )
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
@@ -70,14 +73,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -91,7 +90,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -82,14 +81,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -0,0 +1,109 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.openai import OpenAILLMService, OpenAISTTService, OpenAITTSService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                audio_out_sample_rate=24000,
+                transcription_enabled=False,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+                vad_audio_passthrough=True,
+            ),
+        )
+
+        # You can use the OpenAI compatible API like Groq.
+        # stt = OpenAISTTService(
+        #     base_url="https://api.groq.com/openai/v1",
+        #     api_key="gsk_***",
+        #     model="whisper-large-v3",
+        # )
+        stt = OpenAISTTService(api_key=os.getenv("OPENAI_API_KEY"), model="whisper-1")
+
+        tts = OpenAITTSService(api_key=os.getenv("OPENAI_API_KEY"), voice="alloy")
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,  # STT
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,7 +15,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -80,14 +79,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -74,14 +73,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -79,19 +78,27 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
 
         # Register an event handler to exit the application when the user leaves.
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.queue_frame(EndFrame())
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -39,7 +38,6 @@ async def main():
             "Respond bot",
             DailyParams(
                 audio_out_enabled=True,
-                audio_out_sample_rate=24000,
                 transcription_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
@@ -71,14 +69,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -90,7 +89,10 @@ async def main():
         task = PipelineTask(
             pipeline,
             PipelineParams(
-                allow_interruptions=True, enable_metrics=True, enable_usage_metrics=True
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
             ),
         )
 
@@ -98,7 +100,11 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -80,14 +79,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -22,6 +21,7 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.google import GoogleTTSService
 from pipecat.services.openai import OpenAILLMService
+from pipecat.transcriptions.language import Language
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -40,7 +40,6 @@ async def main():
             "Respond bot",
             DailyParams(
                 audio_out_enabled=True,
-                audio_out_sample_rate=24000,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
                 vad_audio_passthrough=True,
@@ -50,8 +49,8 @@ async def main():
         stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
         tts = GoogleTTSService(
-            voice_id="en-US-Neural2-J",
-            params=GoogleTTSService.InputParams(language="en-US", rate="1.05"),
+            voice_id="en-US-Journey-F",
+            params=GoogleTTSService.InputParams(language=Language.EN_US),
         )
 
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
@@ -78,14 +77,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -79,14 +78,26 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,14 +14,10 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.filters.krisp_filter import KrispFilter
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantResponseAggregator,
-    LLMUserResponseAggregator,
-)
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.deepgram import DeepgramSTTService, DeepgramTTSService
 from pipecat.services.openai import OpenAILLMService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
@@ -63,28 +59,40 @@ async def main():
             },
         ]
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline(
             [
                 transport.input(),  # Transport user input
                 stt,  # STT
-                tma_in,  # User responses
+                context_aggregator.user(),  # User responses
                 llm,  # LLM
                 tts,  # TTS
                 transport.output(),  # Transport bot output
-                tma_out,  # Assistant spoken responses
+                context_aggregator.assistant(),  # Assistant spoken responses
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -89,7 +88,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -81,7 +80,11 @@ async def main():
         async def on_first_participant_joined(transport, participant):
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -216,11 +216,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = GoogleLLMService(
-            model="gemini-1.5-flash-latest",
-            # model="gemini-exp-1114",
-            api_key=os.getenv("GOOGLE_API_KEY"),
-        )
+        llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
 
         messages = [
             {
@@ -268,6 +264,10 @@ async def main():
             # Kick off the conversation.
             await task.queue_frames([context_aggregator.user().get_context_frame()])
 
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
         runner = PipelineRunner()
 
         await runner.run(task)

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -14,7 +14,6 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -88,7 +87,11 @@ async def main():
             await transport.capture_participant_transcription(participant["id"])
             # Kick off the conversation.
             messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-            await task.queue_frames([LLMMessagesFrame(messages)])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
 
         runner = PipelineRunner()
 

examples/foundational/08-bots-arguing.py

@@ -48,7 +48,6 @@ async def main():
             region=os.getenv("AZURE_SPEECH_REGION"),
         )
         tts2 = ElevenLabsTTSService(
-            aiohttp_session=session,
             api_key=os.getenv("ELEVENLABS_API_KEY"),
             voice_id="jBpfuIE2acCO8z3wKNLl",
         )

examples/foundational/09-mirror.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -21,7 +21,7 @@ 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.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
@@ -61,7 +61,6 @@ async def main():
             "Test",
             DailyParams(
                 audio_in_enabled=True,
-                audio_in_sample_rate=24000,
                 audio_out_enabled=True,
                 camera_out_enabled=True,
                 camera_out_is_live=True,
@@ -78,7 +77,9 @@ async def main():
 
         runner = PipelineRunner()
 
-        task = PipelineTask(pipeline)
+        task = PipelineTask(
+            pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
+        )
 
         await runner.run(task)
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -22,7 +22,7 @@ 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.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.transports.base_transport import TransportParams
 from pipecat.transports.local.tk import TkLocalTransport
@@ -62,7 +62,7 @@ async def main():
         tk_root.title("Local Mirror")
 
         daily_transport = DailyTransport(
-            room_url, token, "Test", DailyParams(audio_in_enabled=True, audio_in_sample_rate=24000)
+            room_url, token, "Test", DailyParams(audio_in_enabled=True)
         )
 
         tk_transport = TkLocalTransport(
@@ -82,7 +82,9 @@ async def main():
 
         pipeline = Pipeline([daily_transport.input(), MirrorProcessor(), tk_transport.output()])
 
-        task = PipelineTask(pipeline)
+        task = PipelineTask(
+            pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
+        )
 
         async def run_tk():
             while not task.has_finished():

examples/foundational/10-wake-phrase.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/foundational/11-sound-effects.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/foundational/12-describe-video.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -7,6 +7,7 @@
 import asyncio
 import os
 import sys
+from typing import Optional
 
 import aiohttp
 from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-    def __init__(self, participant_id: str | None = None):
+    def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -7,6 +7,7 @@
 import asyncio
 import os
 import sys
+from typing import Optional
 
 import aiohttp
 from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-    def __init__(self, participant_id: str | None = None):
+    def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
 
@@ -72,9 +73,7 @@ async def main():
 
         vision_aggregator = VisionImageFrameAggregator()
 
-        google = GoogleLLMService(
-            model="gemini-1.5-flash-latest", api_key=os.getenv("GOOGLE_API_KEY")
-        )
+        google = GoogleLLMService(model="gemini-2.0-flash-001", api_key=os.getenv("GOOGLE_API_KEY"))
 
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -7,6 +7,7 @@
 import asyncio
 import os
 import sys
+from typing import Optional
 
 import aiohttp
 from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-    def __init__(self, participant_id: str | None = None):
+    def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -7,6 +7,7 @@
 import asyncio
 import os
 import sys
+from typing import Optional
 
 import aiohttp
 from dotenv import load_dotenv
@@ -32,7 +33,7 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 class UserImageRequester(FrameProcessor):
-    def __init__(self, participant_id: str | None = None):
+    def __init__(self, participant_id: Optional[str] = None):
         super().__init__()
         self._participant_id = participant_id
 

examples/foundational/13-whisper-transcription.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -16,8 +16,7 @@ from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.whisper import WhisperSTTService
-from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.local.audio import LocalAudioTransport
+from pipecat.transports.local.audio import LocalAudioTransport, LocalTransportParams
 
 load_dotenv(override=True)
 
@@ -34,7 +33,7 @@ class TranscriptionLogger(FrameProcessor):
 
 
 async def main():
-    transport = LocalAudioTransport(TransportParams(audio_in_enabled=True))
+    transport = LocalAudioTransport(LocalTransportParams(audio_in_enabled=True))
 
     stt = WhisperSTTService()
 
@@ -44,7 +43,7 @@ async def main():
 
     task = PipelineTask(pipeline)
 
-    runner = PipelineRunner()
+    runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
 
     await runner.run(task)
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

examples/foundational/14-function-calling.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -29,11 +30,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -62,11 +62,7 @@ async def main():
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = GoogleLLMService(
-            model="gemini-1.5-flash-latest",
-            # model="gemini-exp-1114",
-            api_key=os.getenv("GOOGLE_API_KEY"),
-        )
+        llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
         llm.register_function("get_weather", get_weather)
         llm.register_function("get_image", get_image)
 

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,11 +15,12 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.services.groq import GroqLLMService
+from pipecat.services.groq import GroqLLMService, GroqSTTService
 from pipecat.services.openai import OpenAILLMContext
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 
@@ -52,20 +50,20 @@ async def main():
             "Respond bot",
             DailyParams(
                 audio_out_enabled=True,
-                transcription_enabled=True,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
+                vad_audio_passthrough=True,
             ),
         )
 
+        stt = GroqSTTService(api_key=os.getenv("GROQ_API_KEY"), model="distil-whisper-large-v3-en")
+
         tts = CartesiaTTSService(
             api_key=os.getenv("CARTESIA_API_KEY"),
             voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
         )
 
-        llm = GroqLLMService(
-            api_key=os.getenv("GROQ_API_KEY"), model="llama3-groq-70b-8192-tool-use-preview"
-        )
+        llm = GroqLLMService(api_key=os.getenv("GROQ_API_KEY"), model="llama-3.3-70b-versatile")
         # Register a function_name of None to get all functions
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
@@ -107,6 +105,7 @@ async def main():
         pipeline = Pipeline(
             [
                 transport.input(),
+                stt,
                 context_aggregator.user(),
                 llm,
                 tts,

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

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

examples/foundational/14h-function-calling-azure.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

examples/foundational/14i-function-calling-fireworks.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

examples/foundational/14j-function-calling-nim.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

examples/foundational/14k-function-calling-cerebras.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024–2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -15,6 +15,7 @@ from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,11 +31,8 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def start_fetch_weather(function_name, llm, context):
-    # note: we can't push a frame to the LLM here. the bot
-    # can interrupt itself and/or cause audio overlapping glitches.
-    # possible question for Aleix and Chad about what the right way
-    # to trigger speech is, now, with the new queues/async/sync refactors.
-    # await llm.push_frame(TextFrame("Let me check on that."))
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 
@@ -95,7 +93,7 @@ async def main():
         messages = [
             {
                 "role": "system",
-                "content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. 
+                "content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
 
 You have one functions available:
 

examples/foundational/14l-function-calling-deepseek.py

@@ -0,0 +1,146 @@
+#
+# Copyright (c) 2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from openai.types.chat import ChatCompletionToolParam
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.deepseek import DeepSeekLLMService
+from pipecat.services.openai import OpenAILLMContext
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def start_fetch_weather(function_name, llm, context):
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
+    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
+
+
+async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await result_callback({"conditions": "nice", "temperature": "75"})
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        llm = DeepSeekLLMService(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
+        # Register a function_name of None to get all functions
+        # sent to the same callback with an additional function_name parameter.
+        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+
+        tools = [
+            ChatCompletionToolParam(
+                type="function",
+                function={
+                    "name": "get_current_weather",
+                    "description": "Get the current weather for a specific location. You MUST use this function whenever asked about weather.",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string",
+                                "description": "The city and state, e.g. San Francisco, CA",
+                            },
+                            "format": {
+                                "type": "string",
+                                "enum": ["celsius", "fahrenheit"],
+                                "description": "The temperature unit to use. Use fahrenheit for US locations, celsius for others.",
+                            },
+                        },
+                        "required": ["location", "format"],
+                    },
+                },
+            )
+        ]
+        messages = [
+            {
+                "role": "system",
+                "content": """You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
+
+You have one functions available:
+
+1. get_current_weather is used to get current weather information.
+
+Infer whether to use Fahrenheit or Celsius automatically based on the location, unless the user specifies a preference.
+
+Start by asking me for my location. Then, use 'get_weather_current' to give me a forecast.
+
+        Respond to what the user said in a creative and helpful way.""",
+            },
+        ]
+
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                tts,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/14m-function-calling-openrouter.py

@@ -0,0 +1,140 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from openai.types.chat import ChatCompletionToolParam
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.azure import AzureTTSService
+from pipecat.services.openrouter import OpenRouterLLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def start_fetch_weather(function_name, llm, context):
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
+    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
+
+
+async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await result_callback({"conditions": "nice", "temperature": "75"})
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = AzureTTSService(
+            api_key=os.getenv("AZURE_API_KEY"),
+            region="eastus",
+            voice="en-US-JennyNeural",
+            params=AzureTTSService.InputParams(language="en-US", rate="1.1", style="cheerful"),
+        )
+
+        llm = OpenRouterLLMService(
+            api_key=os.getenv("OPENROUTER_API_KEY"), model="openai/gpt-4o-2024-11-20"
+        )
+        # Register a function_name of None to get all functions
+        # sent to the same callback with an additional function_name parameter.
+        llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
+
+        tools = [
+            ChatCompletionToolParam(
+                type="function",
+                function={
+                    "name": "get_current_weather",
+                    "description": "Get the current weather",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {
+                                "type": "string",
+                                "description": "The city and state, e.g. San Francisco, CA",
+                            },
+                            "format": {
+                                "type": "string",
+                                "enum": ["celsius", "fahrenheit"],
+                                "description": "The temperature unit to use. Infer this from the users location.",
+                            },
+                        },
+                        "required": ["location", "format"],
+                    },
+                },
+            )
+        ]
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                tts,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())