Can work with double sound but not parallel sound

CHANGELOG.md

@@ -9,111 +9,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-- 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
-
-- 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.
-
-### Fixed
-
-- 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
-
-- 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
@@ -126,21 +26,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### 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

README.md

@@ -53,7 +53,7 @@ To keep things lightweight, only the core framework is included by default. If y
 pip install "pipecat-ai[option,...]"
 ```
 
-### Available services
+Available options include:
 
 | Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    | Install Command Example                 |
 | ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
@@ -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 TextFrame
+from pipecat.frames.frames import EndFrame, 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.cancel()
+    await task.queue_frame(EndFrame())
 
   # Run the pipeline task
   await runner.run(task)

examples/README.md

@@ -39,7 +39,7 @@ 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            |
-| [Phone Chatbot](phone-chatbot)             | A chatbot that connects to PSTN/SIP phone calls, powered by Daily or Twilio.                                                                    | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
+| [Dialin Chatbot](dialin-chatbot)             | A chatbot that connects to an incoming phone call from 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. | Cartesia, Deepgram, OpenAI, Websockets |

examples/bot-ready-signalling/README.md

@@ -1,45 +0,0 @@
-# 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

@@ -1,27 +0,0 @@
-# JavaScript Implementation
-
-Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
-
-## Setup
-
-1. Run the bot server. See the [server README](../../README).
-
-2. Navigate to the `client/javascript` directory:
-
-```bash
-cd client/javascript
-```
-
-3. Install dependencies:
-
-```bash
-npm install
-```
-
-4. Run the client app:
-
-```
-npm run dev
-```
-
-5. Visit http://localhost:5173 in your browser.

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

@@ -1,34 +0,0 @@
-<!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

@@ -1,20 +0,0 @@
-{
-  "name": "client",
-  "version": "1.0.0",
-  "main": "index.js",
-  "scripts": {
-    "dev": "vite",
-    "build": "vite build",
-    "preview": "vite preview"
-  },
-  "keywords": [],
-  "author": "",
-  "license": "ISC",
-  "description": "",
-  "devDependencies": {
-    "vite": "^6.0.2"
-  },
-  "dependencies": {
-    "@daily-co/daily-js": "0.74.0"
-  }
-}

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

@@ -1,216 +0,0 @@
-/**
- * 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/src/style.css

@@ -1,98 +0,0 @@
-body {
-  margin: 0;
-  padding: 20px;
-  font-family: Arial, sans-serif;
-  background-color: #f0f0f0;
-}
-
-.container {
-  max-width: 1200px;
-  margin: 0 auto;
-}
-
-.status-bar {
-  display: flex;
-  justify-content: space-between;
-  align-items: center;
-  padding: 10px;
-  background-color: #fff;
-  border-radius: 8px;
-  margin-bottom: 20px;
-}
-
-.controls button {
-  padding: 8px 16px;
-  margin-left: 10px;
-  border: none;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
-#connect-btn {
-  background-color: #4caf50;
-  color: white;
-}
-
-#disconnect-btn {
-  background-color: #f44336;
-  color: white;
-}
-
-button:disabled {
-  opacity: 0.5;
-  cursor: not-allowed;
-}
-
-.main-content {
-  background-color: #fff;
-  border-radius: 8px;
-  padding: 20px;
-  margin-bottom: 20px;
-}
-
-.bot-container {
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-}
-
-#bot-video-container {
-  width: 640px;
-  height: 360px;
-  background-color: #e0e0e0;
-  border-radius: 8px;
-  margin: 20px auto;
-  overflow: hidden;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-}
-
-#bot-video-container video {
-  width: 100%;
-  height: 100%;
-  object-fit: cover;
-}
-
-.debug-panel {
-  background-color: #fff;
-  border-radius: 8px;
-  padding: 20px;
-}
-
-.debug-panel h3 {
-  margin: 0 0 10px 0;
-  font-size: 16px;
-  font-weight: bold;
-}
-
-#debug-log {
-  height: 200px;
-  overflow-y: auto;
-  background-color: #f8f8f8;
-  padding: 10px;
-  border-radius: 4px;
-  font-family: monospace;
-  font-size: 12px;
-  line-height: 1.4;
-}

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

@@ -1,13 +0,0 @@
-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

@@ -1,50 +0,0 @@
-# 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

@@ -1,3 +0,0 @@
-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

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

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

@@ -1,63 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-
-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: argparse.ArgumentParser | None = 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

@@ -1,147 +0,0 @@
-#
-# 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

@@ -1,93 +0,0 @@
-#
-# 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 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,
-        audio: bytes = None,
-        sample_rate: int = 16000,
-        num_channels: int = 1,
-        duration: float = 0.1,
-    ):
-        # Initialize the parent class with the silent frame's data
-        super().__init__(
-            audio=self.create_silent_audio_frame(sample_rate, num_channels, duration).audio,
-            sample_rate=sample_rate,
-            num_channels=num_channels,
-        )
-
-    @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(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

@@ -130,13 +130,11 @@ async def main():
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             print(f"Participant left: {participant}")
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         @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

@@ -53,3 +53,4 @@ async def configure(aiohttp_session: aiohttp.ClientSession):
     token = await daily_rest_helper.get_token(url, expiry_time)
 
     return (url, token)
+    return (url, token)

examples/chatbot-audio-recording/bot.py

@@ -18,6 +18,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -138,7 +139,7 @@ async def main():
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             print(f"Participant left: {participant}")
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/deployment/flyio-example/bot.py

@@ -79,13 +79,11 @@ async def main(room_url: str, token: str):
 
     @transport.event_handler("on_participant_left")
     async def on_participant_left(transport, participant, reason):
-        await task.cancel()
+        await task.queue_frame(EndFrame())
 
     @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/modal-example/bot.py

@@ -5,15 +5,6 @@ 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)
@@ -21,6 +12,16 @@ 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
+    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,
@@ -78,7 +79,7 @@ async def main(room_url: str, token: str):
 
     @transport.event_handler("on_participant_left")
     async def on_participant_left(transport, participant, reason):
-        await task.cancel()
+        await task.queue_frame(EndFrame())
 
     runner = PipelineRunner()
 

examples/dialin-chatbot/README.md

@@ -0,0 +1,94 @@
+<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:
+
+```bash
+curl -X POST 'http://localhost:7860/daily_start_bot' \
+  -H 'Content-Type: application/json' \
+  -d '{
+      "callId": "callId-from-call",
+      "callDomain": "callDomain-from-call"
+  }'
+```
+
+Use [this guide](https://docs.pipecat.ai/guides/telephony/daily-webrtc) to connect a phone number purchased from Daily to the 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

@@ -0,0 +1,195 @@
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import asyncio
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+from openai.types.chat import ChatCompletionToolParam
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+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.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.ai_services import LLMService
+from pipecat.services.deepgram import DeepgramSTTService
+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")
+
+    content = f"""
+You are a delivery service customer support specialist supporting customers with their orders. 
+Begin with: "Hello, this is Hailey from customer support. What can I help you with today?"
+    """
+
+    messages = [
+        {
+            "role": "system",
+            "content": content,
+        },
+    ]
+
+    tools = [
+        ChatCompletionToolParam(
+            type="function",
+            function={
+                "name": "transfer_call",
+                "description": "Transfer the call to a person. This function is used to connect the call to a real person. Examples of real people are: managers, supervisors, or other customer support specialists. Any person is okay as long as they are not a bot.",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "call_id": {
+                            "type": "string",
+                            "description": "This is always {callId}.",
+                        },
+                        "summary": {
+                            "type": "string",
+                            "description": """
+Provide a concise summary in 3-5 sentences. Highlight any  important details or unusual aspects of the conversation.
+                            """,
+                        },
+                    },
+                },
+            },
+        )
+    ]
+
+    context = OpenAILLMContext(messages, tools)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    async def default_transfer_call(
+        function_name, tool_call_id, args, llm: LLMService, context, result_callback
+    ):
+        logger.debug(f"default_transfer_call: {function_name} {tool_call_id} {args}")
+        await result_callback(
+            {
+                "transfer_call": False,
+                "reason": "To transfer call calls, please dial in to the room using a phone or a SIP client.",
+            }
+        )
+
+    llm.register_function(
+        function_name="transfer_call",
+        callback=default_transfer_call,
+    )
+
+    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([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())
+
+    @transport.event_handler("on_dialin_ready")
+    async def on_dialin_ready(_, sip_endpoint):
+        logger.info(f"on_dialin_ready: {sip_endpoint}")
+
+    @transport.event_handler("on_dialin_connected")
+    async def on_dialin_connected(transport, event):
+        logger.info(f"on_dialin_connected: {event}")
+        sip_session_id = event["sessionId"]
+
+        async def transfer_call(
+            function_name, tool_call_id, args, llm: LLMService, context, result_callback
+        ):
+            logger.debug(f"transfer_call: {function_name} {tool_call_id} {args}")
+
+            # sip_url = "sip:your_user_name@sip.linphone.org"
+
+            sip_url = (
+                f"sip:your_username@dailyco.sip.twilio.com?x-daily_id={room_url.split('/')[-1]}"
+            )
+
+            try:
+                await transport.sip_refer(
+                    settings={
+                        "sessionId": sip_session_id,
+                        "toEndPoint": sip_url,
+                    }
+                )
+            except Exception as e:
+                logger.error(f"An error occurred during SIP refer: {e}")
+                await result_callback({"transfer_call": False})
+
+            await result_callback({"transfer_call": True})
+
+        llm.register_function(
+            function_name="transfer_call",
+            callback=transfer_call,
+        )
+
+    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/dialin-chatbot/bot_runner.py

@@ -73,29 +73,24 @@ action using the Twilio Client library.
 """
 
 
-async def _create_daily_room(
-    room_url, callId, callDomain=None, dialoutNumber=None, vendor="daily", detect_voicemail=False
-):
+async def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
     if not room_url:
-        # Create base properties with SIP settings
-        properties = DailyRoomProperties(
-            sip=DailyRoomSipParams(
-                display_name="dialin-user", video=False, sip_mode="dial-in", num_endpoints=1
+        params = DailyRoomParams(
+            properties=DailyRoomProperties(
+                # Note: these are the default values, except for the display name
+                sip=DailyRoomSipParams(
+                    display_name="dialin-user", video=False, sip_mode="dial-in", num_endpoints=1
+                )
             )
         )
 
-        # Only enable dialout if dialoutNumber is provided
-        if dialoutNumber:
-            properties.enable_dialout = True
-
-        params = DailyRoomParams(properties=properties)
-
         print(f"Creating new room...")
         room: DailyRoomObject = await daily_helpers["rest"].create_room(params=params)
 
     else:
         # Check passed room URL exist (we assume that it already has a sip set up!)
         try:
+            print(f"Joining existing room: {room_url}")
             room: DailyRoomObject = await daily_helpers["rest"].get_room_from_url(room_url)
         except Exception:
             raise HTTPException(status_code=500, detail=f"Room not found: {room_url}")
@@ -111,9 +106,7 @@ async def _create_daily_room(
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in docs)
     if vendor == "daily":
-        bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {callId} -d {callDomain}{' -v' if detect_voicemail else ''}"
-        if dialoutNumber:
-            bot_proc += f" -o {dialoutNumber}"
+        bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {callId} -d {callDomain}"
     else:
         bot_proc = f"python3 -m bot_twilio -u {room.url} -t {token} -i {callId} -s {room.config.sip_endpoint}"
 
@@ -184,18 +177,13 @@ async def daily_start_bot(request: Request) -> JSONResponse:
         if "test" in data:
             # Pass through any webhook checks
             return JSONResponse({"test": True})
-        detect_voicemail = data.get("detectVoicemail", False)
         callId = data.get("callId", None)
         callDomain = data.get("callDomain", None)
-        dialoutNumber = data.get("dialoutNumber", None)
     except Exception:
-        raise HTTPException(
-            status_code=500, detail="Missing properties 'callId', 'callDomain', or 'dialoutNumber'"
-        )
+        raise HTTPException(status_code=500, detail="Missing properties 'callId' or 'callDomain'")
 
-    room: DailyRoomObject = await _create_daily_room(
-        room_url, callId, callDomain, dialoutNumber, "daily", detect_voicemail
-    )
+    print(f"CallId: {callId}, CallDomain: {callDomain}")
+    room: DailyRoomObject = await _create_daily_room(room_url, callId, callDomain, "daily")
 
     # Grab a token for the user to join with
     return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})

examples/dialin-chatbot/bot_twilio.py

@@ -8,6 +8,7 @@ from loguru import logger
 from twilio.rest import Client
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -86,7 +87,7 @@ async def main(room_url: str, token: str, callId: str, sipUri: str):
 
     @transport.event_handler("on_participant_left")
     async def on_participant_left(transport, participant, reason):
-        await task.cancel()
+        await task.queue_frame(EndFrame())
 
     @transport.event_handler("on_dialin_ready")
     async def on_dialin_ready(transport, cdata):

examples/foundational/03-still-frame.py

@@ -13,7 +13,7 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
-from pipecat.frames.frames import TextFrame
+from pipecat.frames.frames import EndFrame, 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.cancel()
+            await task.queue_frame(EndFrame())
 
         await runner.run(task)
 

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

@@ -1,64 +0,0 @@
-#
-# 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/06-listen-and-respond.py

@@ -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, MetricsFrame
+from pipecat.frames.frames import EndFrame, Frame, MetricsFrame
 from pipecat.metrics.metrics import (
     LLMUsageMetricsData,
     ProcessingMetricsData,
@@ -38,8 +38,6 @@ 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):
@@ -117,7 +115,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -15,16 +15,10 @@ from PIL import Image
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import (
-    BotStartedSpeakingFrame,
-    BotStoppedSpeakingFrame,
-    Frame,
-    OutputImageRawFrame,
-    TextFrame,
-)
+from pipecat.frames.frames import EndFrame, Frame, OutputImageRawFrame, SystemFrame, TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.pipeline.task import PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.cartesia import CartesiaHttpTTSService
@@ -51,7 +45,7 @@ class ImageSyncAggregator(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, BotStartedSpeakingFrame):
+        if not isinstance(frame, SystemFrame) and direction == FrameDirection.DOWNSTREAM:
             await self.push_frame(
                 OutputImageRawFrame(
                     image=self._speaking_image_bytes,
@@ -59,8 +53,7 @@ class ImageSyncAggregator(FrameProcessor):
                     format=self._speaking_image_format,
                 )
             )
-
-        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(frame)
             await self.push_frame(
                 OutputImageRawFrame(
                     image=self._waiting_image_bytes,
@@ -68,8 +61,8 @@ class ImageSyncAggregator(FrameProcessor):
                     format=self._waiting_image_format,
                 )
             )
-
-        await self.push_frame(frame)
+        else:
+            await self.push_frame(frame)
 
 
 async def main():
@@ -116,24 +109,16 @@ 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,
-            PipelineParams(
-                allow_interruptions=True,
-                enable_metrics=True,
-                enable_usage_metrics=True,
-                report_only_initial_ttfb=True,
-            ),
-        )
+        task = PipelineTask(pipeline)
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
@@ -143,7 +128,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/foundational/07-interruptible-vad.py

@@ -13,6 +13,7 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
+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
@@ -93,7 +94,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/foundational/07-interruptible.py

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -91,7 +92,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -95,7 +96,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -19,7 +19,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMMessagesFrame
+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
@@ -124,7 +124,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -16,6 +16,7 @@ from runner import configure
 
 from pipecat.frames.frames import (
     BotInterruptionFrame,
+    EndFrame,
     StopInterruptionFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
@@ -105,7 +106,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -90,7 +91,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -91,7 +92,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,12 +14,14 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.openai import OpenAILLMService
 from pipecat.services.playht import PlayHTHttpTTSService
+from pipecat.transcriptions.language import Language
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -92,7 +94,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -94,7 +95,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -100,7 +101,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -88,7 +89,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -15,6 +15,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -98,7 +99,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -92,7 +93,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -98,7 +99,7 @@ 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.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -89,7 +90,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -104,7 +105,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -98,7 +99,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -97,7 +98,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -97,7 +98,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.filters.krisp_filter import KrispFilter
+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
@@ -92,7 +93,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -92,7 +93,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -84,7 +85,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -17,6 +17,7 @@ from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import (
+    EndFrame,
     Frame,
     InputAudioRawFrame,
     LLMFullResponseEndFrame,
@@ -270,7 +271,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

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

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -91,7 +92,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/foundational/14-function-calling.py

@@ -15,7 +15,6 @@ 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
@@ -30,8 +29,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 
@@ -93,7 +95,7 @@ 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

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 
@@ -93,7 +95,7 @@ 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/14m-function-calling-openrouter.py

@@ -15,7 +15,6 @@ 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
@@ -31,8 +30,11 @@ 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."))
+    # 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."))
     logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
 
 

examples/foundational/17-detect-user-idle.py

@@ -14,7 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import EndFrame, LLMMessagesFrame, TTSSpeakFrame
+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
@@ -63,36 +63,16 @@ async def main():
         context = OpenAILLMContext(messages)
         context_aggregator = llm.create_context_aggregator(context)
 
-        async def handle_user_idle(user_idle: UserIdleProcessor, retry_count: int) -> bool:
-            if retry_count == 1:
-                # First attempt: Add a gentle prompt to the conversation
-                messages.append(
-                    {
-                        "role": "system",
-                        "content": "The user has been quiet. Politely and briefly ask if they're still there.",
-                    }
-                )
-                await user_idle.push_frame(LLMMessagesFrame(messages))
-                return True
-            elif retry_count == 2:
-                # Second attempt: More direct prompt
-                messages.append(
-                    {
-                        "role": "system",
-                        "content": "The user is still inactive. Ask if they'd like to continue our conversation.",
-                    }
-                )
-                await user_idle.push_frame(LLMMessagesFrame(messages))
-                return True
-            else:
-                # Third attempt: End the conversation
-                await user_idle.push_frame(
-                    TTSSpeakFrame("It seems like you're busy right now. Have a nice day!")
-                )
-                await task.queue_frame(EndFrame())
-                return False
+        async def user_idle_callback(user_idle: UserIdleProcessor):
+            messages.append(
+                {
+                    "role": "system",
+                    "content": "Ask the user if they are still there and try to prompt for some input, but be short.",
+                }
+            )
+            await user_idle.push_frame(LLMMessagesFrame(messages))
 
-        user_idle = UserIdleProcessor(callback=handle_user_idle, timeout=5.0)
+        user_idle = UserIdleProcessor(callback=user_idle_callback, timeout=5.0)
 
         pipeline = Pipeline(
             [

examples/foundational/21-tavus-layer.py

@@ -14,6 +14,7 @@ from dotenv import load_dotenv
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+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
@@ -119,7 +120,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/foundational/22b-natural-conversation-proposal.py

@@ -117,15 +117,12 @@ class CompletenessCheck(FrameProcessor):
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
-
         if isinstance(frame, TextFrame) and frame.text == "YES":
             logger.debug("Completeness check YES")
             await self.push_frame(UserStoppedSpeakingFrame())
             await self._notifier.notify()
         elif isinstance(frame, TextFrame) and frame.text == "NO":
             logger.debug("Completeness check NO")
-        else:
-            await self.push_frame(frame, direction)
 
 
 class OutputGate(FrameProcessor):
@@ -169,10 +166,11 @@ class OutputGate(FrameProcessor):
 
     async def _start(self):
         self._frames_buffer = []
-        self._gate_task = self.create_task(self._gate_task_handler())
+        self._gate_task = self.get_event_loop().create_task(self._gate_task_handler())
 
     async def _stop(self):
-        await self.cancel_task(self._gate_task)
+        self._gate_task.cancel()
+        await self._gate_task
 
     async def _gate_task_handler(self):
         while True:

examples/foundational/22c-natural-conversation-mixed-llms.py

@@ -101,12 +101,12 @@ HIGH PRIORITY SIGNALS:
 
 Examples:
 # Complete Wh-question
-[{"role": "assistant", "content": "I can help you learn."},
+[{"role": "assistant", "content": "I can help you learn."}, 
  {"role": "user", "content": "What's the fastest way to learn Spanish"}]
 Output: YES
 
 # Complete Yes/No question despite STT error
-[{"role": "assistant", "content": "I know about planets."},
+[{"role": "assistant", "content": "I know about planets."}, 
  {"role": "user", "content": "Is is Jupiter the biggest planet"}]
 Output: YES
 
@@ -118,12 +118,12 @@ Output: YES
 
 Examples:
 # Direct instruction
-[{"role": "assistant", "content": "I can explain many topics."},
+[{"role": "assistant", "content": "I can explain many topics."}, 
  {"role": "user", "content": "Tell me about black holes"}]
 Output: YES
 
 # Action demand
-[{"role": "assistant", "content": "I can help with math."},
+[{"role": "assistant", "content": "I can help with math."}, 
  {"role": "user", "content": "Solve this equation x plus 5 equals 12"}]
 Output: YES
 
@@ -134,12 +134,12 @@ Output: YES
 
 Examples:
 # Specific answer
-[{"role": "assistant", "content": "What's your favorite color?"},
+[{"role": "assistant", "content": "What's your favorite color?"}, 
  {"role": "user", "content": "I really like blue"}]
 Output: YES
 
 # Option selection
-[{"role": "assistant", "content": "Would you prefer morning or evening?"},
+[{"role": "assistant", "content": "Would you prefer morning or evening?"}, 
  {"role": "user", "content": "Morning"}]
 Output: YES
 
@@ -153,17 +153,17 @@ MEDIUM PRIORITY SIGNALS:
 
 Examples:
 # Self-correction reaching completion
-[{"role": "assistant", "content": "What would you like to know?"},
+[{"role": "assistant", "content": "What would you like to know?"}, 
  {"role": "user", "content": "Tell me about... no wait, explain how rainbows form"}]
 Output: YES
 
 # Topic change with complete thought
-[{"role": "assistant", "content": "The weather is nice today."},
+[{"role": "assistant", "content": "The weather is nice today."}, 
  {"role": "user", "content": "Actually can you tell me who invented the telephone"}]
 Output: YES
 
 # Mid-sentence completion
-[{"role": "assistant", "content": "Hello I'm ready."},
+[{"role": "assistant", "content": "Hello I'm ready."}, 
  {"role": "user", "content": "What's the capital of? France"}]
 Output: YES
 
@@ -175,12 +175,12 @@ Output: YES
 
 Examples:
 # Acknowledgment
-[{"role": "assistant", "content": "Should we talk about history?"},
+[{"role": "assistant", "content": "Should we talk about history?"}, 
  {"role": "user", "content": "Sure"}]
 Output: YES
 
 # Disagreement with completion
-[{"role": "assistant", "content": "Is that what you meant?"},
+[{"role": "assistant", "content": "Is that what you meant?"}, 
  {"role": "user", "content": "No not really"}]
 Output: YES
 
@@ -194,12 +194,12 @@ LOW PRIORITY SIGNALS:
 
 Examples:
 # Word repetition but complete
-[{"role": "assistant", "content": "I can help with that."},
+[{"role": "assistant", "content": "I can help with that."}, 
  {"role": "user", "content": "What what is the time right now"}]
 Output: YES
 
 # Missing punctuation but complete
-[{"role": "assistant", "content": "I can explain that."},
+[{"role": "assistant", "content": "I can explain that."}, 
  {"role": "user", "content": "Please tell me how computers work"}]
 Output: YES
 
@@ -211,12 +211,12 @@ Output: YES
 
 Examples:
 # Filler words but complete
-[{"role": "assistant", "content": "What would you like to know?"},
+[{"role": "assistant", "content": "What would you like to know?"}, 
  {"role": "user", "content": "Um uh how do airplanes fly"}]
 Output: YES
 
 # Thinking pause but incomplete
-[{"role": "assistant", "content": "I can explain anything."},
+[{"role": "assistant", "content": "I can explain anything."}, 
  {"role": "user", "content": "Well um I want to know about the"}]
 Output: NO
 
@@ -241,17 +241,17 @@ DECISION RULES:
 
 Examples:
 # Incomplete despite corrections
-[{"role": "assistant", "content": "What would you like to know about?"},
+[{"role": "assistant", "content": "What would you like to know about?"}, 
  {"role": "user", "content": "Can you tell me about"}]
 Output: NO
 
 # Complete despite multiple artifacts
-[{"role": "assistant", "content": "I can help you learn."},
+[{"role": "assistant", "content": "I can help you learn."}, 
  {"role": "user", "content": "How do you I mean what's the best way to learn programming"}]
 Output: YES
 
 # Trailing off incomplete
-[{"role": "assistant", "content": "I can explain anything."},
+[{"role": "assistant", "content": "I can explain anything."}, 
  {"role": "user", "content": "I was wondering if you could tell me why"}]
 Output: NO
 """
@@ -328,8 +328,6 @@ class CompletenessCheck(FrameProcessor):
             await self._notifier.notify()
         elif isinstance(frame, TextFrame) and frame.text == "NO":
             logger.debug("!!! Completeness check NO")
-        else:
-            await self.push_frame(frame, direction)
 
 
 class OutputGate(FrameProcessor):
@@ -373,10 +371,11 @@ class OutputGate(FrameProcessor):
 
     async def _start(self):
         self._frames_buffer = []
-        self._gate_task = self.create_task(self._gate_task_handler())
+        self._gate_task = self.get_event_loop().create_task(self._gate_task_handler())
 
     async def _stop(self):
-        await self.cancel_task(self._gate_task)
+        self._gate_task.cancel()
+        await self._gate_task
 
     async def _gate_task_handler(self):
         while True:

examples/foundational/22d-natural-conversation-gemini-audio.py

@@ -44,7 +44,9 @@ from pipecat.processors.aggregators.openai_llm_context import (
 )
 from pipecat.processors.filters.function_filter import FunctionFilter
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.user_idle_processor import UserIdleProcessor
 from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.google import GoogleLLMContext, GoogleLLMService
 from pipecat.sync.base_notifier import BaseNotifier
 from pipecat.sync.event_notifier import EventNotifier
@@ -438,11 +440,11 @@ class CompletenessCheck(FrameProcessor):
 
         if isinstance(frame, UserStartedSpeakingFrame):
             if self._idle_task:
-                await self.cancel_task(self._idle_task)
+                self._idle_task.cancel()
         elif isinstance(frame, TextFrame) and frame.text.startswith("YES"):
             logger.debug("Completeness check YES")
             if self._idle_task:
-                await self.cancel_task(self._idle_task)
+                self._idle_task.cancel()
             await self.push_frame(UserStoppedSpeakingFrame())
             await self._audio_accumulator.reset()
             await self._notifier.notify()
@@ -455,9 +457,7 @@ class CompletenessCheck(FrameProcessor):
                 else:
                     # logger.debug("!!! CompletenessCheck idle wait START")
                     self._wakeup_time = time.time() + self.wait_time
-                    self._idle_task = self.create_task(self._idle_task_handler())
-        else:
-            await self.push_frame(frame, direction)
+                    self._idle_task = self.get_event_loop().create_task(self._idle_task_handler())
 
     async def _idle_task_handler(self):
         try:
@@ -599,10 +599,11 @@ class OutputGate(FrameProcessor):
 
     async def _start(self):
         self._frames_buffer = []
-        self._gate_task = self.create_task(self._gate_task_handler())
+        self._gate_task = self.get_event_loop().create_task(self._gate_task_handler())
 
     async def _stop(self):
-        await self.cancel_task(self._gate_task)
+        self._gate_task.cancel()
+        await self._gate_task
 
     async def _gate_task_handler(self):
         while True:

examples/foundational/25-google-audio-in.py

@@ -212,7 +212,7 @@ class InputTranscriptionFrameEmitter(FrameProcessor):
         elif isinstance(frame, LLMFullResponseEndFrame):
             await self.push_frame(LLMDemoTranscriptionFrame(text=self._aggregation.strip()))
             self._aggregation = ""
-        else:
+        elif isinstance(frame, MetricsFrame):
             await self.push_frame(frame, direction)
 
 

examples/foundational/26-gemini-multimodal-live.py

@@ -15,7 +15,6 @@ from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import LLMMessagesAppendFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -72,21 +71,6 @@ async def main():
             ),
         )
 
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            await task.queue_frames(
-                [
-                    LLMMessagesAppendFrame(
-                        messages=[
-                            {
-                                "role": "assistant",
-                                "content": "Greet the user.",
-                            }
-                        ]
-                    )
-                ]
-            )
-
         runner = PipelineRunner()
 
         await runner.run(task)

examples/foundational/26d-gemini-multimodal-live-text.py

@@ -15,6 +15,7 @@ from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.audio.vad.vad_analyzer import VADParams
+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
@@ -123,7 +124,7 @@ async def main():
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             print(f"Participant left: {participant}")
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/foundational/28a-transcription-processor-openai.py

@@ -15,7 +15,11 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import TranscriptionMessage, TranscriptionUpdateFrame
+from pipecat.frames.frames import (
+    CancelFrame,
+    TranscriptionMessage,
+    TranscriptionUpdateFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -166,7 +170,7 @@ async def main():
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             # Stop the pipeline immediately when the participant leaves
-            await task.cancel()
+            await task.queue_frame(CancelFrame())
 
         runner = PipelineRunner()
 

examples/foundational/28b-transcript-processor-anthropic.py

@@ -15,7 +15,11 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import TranscriptionMessage, TranscriptionUpdateFrame
+from pipecat.frames.frames import (
+    CancelFrame,
+    TranscriptionMessage,
+    TranscriptionUpdateFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -166,7 +170,7 @@ async def main():
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             # Stop the pipeline immediately when the participant leaves
-            await task.cancel()
+            await task.queue_frame(CancelFrame())
 
         runner = PipelineRunner()
 

examples/foundational/28c-transcription-processor-gemini.py

@@ -15,7 +15,11 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import TranscriptionMessage, TranscriptionUpdateFrame
+from pipecat.frames.frames import (
+    CancelFrame,
+    TranscriptionMessage,
+    TranscriptionUpdateFrame,
+)
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -176,7 +180,7 @@ async def main():
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             # Stop the pipeline immediately when the participant leaves
-            await task.cancel()
+            await task.queue_frame(CancelFrame())
 
         runner = PipelineRunner()
 

examples/foundational/30-observer.py

@@ -17,6 +17,7 @@ from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import (
     BotStartedSpeakingFrame,
     BotStoppedSpeakingFrame,
+    EndFrame,
     Frame,
     LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
@@ -169,7 +170,7 @@ async def main():
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
-            await task.cancel()
+            await task.queue_frame(EndFrame())
 
         runner = PipelineRunner()
 

examples/foundational/31-gemini-grounding-metadata.py

@@ -1,130 +0,0 @@
-#
-# Copyright (c) 2024, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import os
-import sys
-from pathlib import Path
-
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame
-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.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.services.deepgram import DeepgramSTTService
-from pipecat.services.google import GoogleLLMService, LLMSearchResponseFrame
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-
-sys.path.append(str(Path(__file__).parent.parent))
-from runner import configure
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-# Function handlers for the LLM
-search_tool = {"google_search_retrieval": {}}
-tools = [search_tool]
-
-system_instruction = """
-You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting. 
-
-Always use the google search API to retrieve the latest news. You must also use it to check which day is today.
-
-You can:
-- Use the Google search API to check the current date.
-- Provide the most recent and relevant news from any place by using the google search API.
-- Answer any questions the user may have, ensuring your responses are accurate and concise.
-
-Start each interaction by asking the user about which place they would like to know the information.
-"""
-
-
-class LLMSearchLoggerProcessor(FrameProcessor):
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, LLMSearchResponseFrame):
-            print(f"LLMSearchLoggerProcessor: {frame}")
-
-        await self.push_frame(frame)
-
-
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, token) = await configure(session)
-
-        transport = DailyTransport(
-            room_url,
-            token,
-            "Latest news!",
-            DailyParams(
-                audio_out_enabled=True,
-                vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer(),
-                vad_audio_passthrough=True,
-            ),
-        )
-
-        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-        )
-
-        # Initialize the Gemini Multimodal Live model
-        llm = GoogleLLMService(
-            api_key=os.getenv("GOOGLE_API_KEY"),
-            system_instruction=system_instruction,
-            tools=tools,
-        )
-
-        context = OpenAILLMContext(
-            [
-                {
-                    "role": "user",
-                    "content": "Start by greeting the user warmly, introducing yourself, and mentioning the current day. Be friendly and engaging to set a positive tone for the interaction.",
-                }
-            ],
-        )
-        context_aggregator = llm.create_context_aggregator(context)
-
-        llm_search_logger = LLMSearchLoggerProcessor()
-
-        pipeline = Pipeline(
-            [
-                transport.input(),
-                stt,
-                context_aggregator.user(),
-                llm,
-                llm_search_logger,
-                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 task.queue_frames([context_aggregator.user().get_context_frame()])
-
-        runner = PipelineRunner()
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

examples/foundational/32-double-room.py

@@ -0,0 +1,156 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import math
+import os
+import random
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.frames.frames import BotSpeakingFrame, EndFrame, Frame, TextFrame, TTSSpeakFrame
+from pipecat.observers.base_observer import BaseObserver
+from pipecat.pipeline.parallel_pipeline import ParallelPipeline
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.filters.function_filter import FunctionFilter
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.transports.services.daily import DailyOutputTransport, DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+class DebugObserver(BaseObserver):
+    """Observer to log interruptions and bot speaking events to the console.
+
+    Logs all frame instances of:
+    - StartInterruptionFrame
+    - BotStartedSpeakingFrame
+    - BotStoppedSpeakingFrame
+
+    This allows you to see the frame flow from processor to processor through the pipeline for these frames.
+    Log format: [EVENT TYPE]: [source processor] → [destination processor] at [timestamp]s
+    """
+
+    async def on_push_frame(
+        self,
+        src: FrameProcessor,
+        dst: FrameProcessor,
+        frame: Frame,
+        direction: FrameDirection,
+        timestamp: int,
+    ):
+        arrow = "→" if direction == FrameDirection.DOWNSTREAM else "←"
+        # Convert timestamp to seconds for readability
+        time_sec = timestamp / 1_000_000_000
+
+        if isinstance(frame, BotSpeakingFrame):
+            return
+
+        if isinstance(dst, DailyOutputTransport):
+            logger.debug(f"{frame} {src} {arrow} {dst} at {time_sec:.2f}s")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, _) = await configure(session)
+
+        transport1 = DailyTransport(
+            "https://hush.daily.co/sip",
+            None,
+            "Don't Do Anything",
+            DailyParams(audio_out_enabled=True),
+        )
+
+        transport2 = DailyTransport(
+            "https://hush.daily.co/demo",
+            None,
+            "Summarize Call",
+            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()
+
+        async def true_filter(frame) -> bool:
+            return True
+
+        async def false_filter(frame) -> bool:
+            return False
+
+        pipeline = Pipeline(
+            [
+                transport1.input(),
+                transport2.input(),
+                ParallelPipeline(
+                    [transport1.output()],
+                    [tts, transport2.output()],
+                ),
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+                observers=[DebugObserver()],
+            ),
+        )
+
+        # Register an event handler so we can play the audio when the
+        # participant joins.
+        @transport1.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            participant_name = participant.get("info", {}).get("userName", "")
+            logger.info(f"-- {participant_name} joined transport1")
+
+        def get_call_summary():
+            """In a real app this would be a call to a database or API."""
+            # Randomly choose between two options
+            message = random.choice(
+                [
+                    "Alice needs help finding her customer record.",
+                    "Bob is calling about his lost password.",
+                ]
+            )
+
+            return message
+
+        @transport2.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            participant_name = participant.get("info", {}).get("userName", "")
+            logger.info(f"-- {participant_name} joined transport2")
+            call_summary = get_call_summary()
+            await task.queue_frames(
+                [
+                    TTSSpeakFrame(
+                        f"Hi {participant_name}! Here's the summary of the call: {call_summary}"
+                    ),
+                    EndFrame(),
+                ]
+            )
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/news-chatbot/.gitignore

@@ -1,51 +0,0 @@
-# Python
-__pycache__/
-*.py[cod]
-*$py.class
-*.so
-.Python
-build/
-dist/
-*.egg-info/
-.installed.cfg
-*.egg
-.pytest_cache/
-.coverage
-.coverage.*
-.env
-.venv
-env/
-venv/
-ENV/
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# JavaScript/Node.js
-node_modules/
-dist/
-dist-ssr/
-*.local
-.env.local
-.env.development.local
-.env.test.local
-.env.production.local
-
-# Logs
-logs/
-*.log
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-pnpm-debug.log*
-
-# Editor/IDE
-.vscode/*
-!.vscode/extensions.json
-.idea/
-*.swp
-*.swo
-.DS_Store
-
-# Project specific
-runpod.toml

examples/news-chatbot/README.md

@@ -1,48 +0,0 @@
-# News Chatbot
-
-A simple AI-powered chatbot that leverages Gemini's real-time search capabilities in a voice AI application.
-
-This example demonstrates Gemini's ability to query Google search in real time and return relevant responses, including links to the URLs that Gemini searched.
-
-All the details about grounding with Google Search can be found [here](https://ai.google.dev/gemini-api/docs/grounding?lang=python).
-
-## 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 and React implementations)
-- Daily API key
-- Gemini API key (for Gemini bot)
-- Cartesia API key
-- Modern web browser with WebRTC support

examples/news-chatbot/client/javascript/README.md

@@ -1,27 +0,0 @@
-# JavaScript Implementation
-
-Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
-
-## Setup
-
-1. Run the bot server. See the [server README](../../README).
-
-2. Navigate to the `client/javascript` directory:
-
-```bash
-cd client/javascript
-```
-
-3. Install dependencies:
-
-```bash
-npm install
-```
-
-4. Run the client app:
-
-```
-npm run dev
-```
-
-5. Visit http://localhost:5173 in your browser.

examples/news-chatbot/client/javascript/index.html

@@ -1,40 +0,0 @@
-<!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>
-
-    <div class="main-content">
-      <div class="bot-container">
-        <div id="search-result-container">
-        </div>
-        <audio id="bot-audio" autoplay></audio>
-      </div>
-    </div>
-
-    <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/news-chatbot/client/javascript/package.json

@@ -1,21 +0,0 @@
-{
-  "name": "client",
-  "version": "1.0.0",
-  "main": "index.js",
-  "scripts": {
-    "dev": "vite",
-    "build": "vite build",
-    "preview": "vite preview"
-  },
-  "keywords": [],
-  "author": "",
-  "license": "ISC",
-  "description": "",
-  "devDependencies": {
-    "vite": "^6.0.2"
-  },
-  "dependencies": {
-    "@pipecat-ai/client-js": "^0.3.2",
-    "@pipecat-ai/daily-transport": "^0.3.4"
-  }
-}

examples/news-chatbot/client/javascript/src/app.js

@@ -1,341 +0,0 @@
-/**
- * Copyright (c) 2024–2025, Daily
- *
- * SPDX-License-Identifier: BSD 2-Clause License
- */
-
-/**
- * RTVI Client Implementation
- *
- * This client connects to an RTVI-compatible bot server using WebRTC (via Daily).
- * It handles audio/video streaming and manages the connection lifecycle.
- *
- * Requirements:
- * - A running RTVI bot server (defaults to http://localhost:7860)
- * - The server must implement the /connect endpoint that returns Daily.co room credentials
- * - Browser with WebRTC support
- */
-
-import {LogLevel, RTVIClient, RTVIClientHelper, RTVIEvent} from '@pipecat-ai/client-js';
-import { DailyTransport } from '@pipecat-ai/daily-transport';
-
-class SearchResponseHelper extends RTVIClientHelper {
-
-  constructor(contentPanel) {
-    super()
-    this.contentPanel = contentPanel
-  }
-
-  handleMessage(rtviMessage) {
-    console.log("SearchResponseHelper, received message:", rtviMessage)
-    if (rtviMessage.data) {
-      // Clear existing content
-      this.contentPanel.innerHTML = "";
-
-      // Create a container for all content
-      const contentContainer = document.createElement('div');
-      contentContainer.className = "content-container";
-
-      // Add the search_result
-      if (rtviMessage.data.search_result) {
-        const searchResultDiv = document.createElement('div');
-        searchResultDiv.className = "search-result";
-        searchResultDiv.textContent = rtviMessage.data.search_result;
-        contentContainer.appendChild(searchResultDiv);
-      }
-
-      // Add the sources
-      if (rtviMessage.data.origins) {
-        const sourcesDiv = document.createElement('div');
-        sourcesDiv.className = "sources";
-
-        const sourcesTitle = document.createElement('h3');
-        sourcesTitle.className = "sources-title";
-        sourcesTitle.textContent = "Sources:";
-        sourcesDiv.appendChild(sourcesTitle);
-
-        rtviMessage.data.origins.forEach(origin => {
-          const sourceLink = document.createElement('a');
-          sourceLink.className = "source-link";
-          sourceLink.href = origin.site_uri;
-          sourceLink.target = "_blank";
-          sourceLink.textContent = origin.site_title;
-          sourcesDiv.appendChild(sourceLink);
-        });
-
-        contentContainer.appendChild(sourcesDiv);
-      }
-
-      // Add the rendered_content in an iframe
-      if (rtviMessage.data.rendered_content) {
-        const iframe = document.createElement('iframe');
-        iframe.className = "iframe-container";
-        iframe.srcdoc = rtviMessage.data.rendered_content;
-        contentContainer.appendChild(iframe);
-      }
-
-      // Append the content container to the content panel
-      this.contentPanel.appendChild(contentContainer);
-    }
-  }
-
-  getMessageTypes() {
-    return ["bot-llm-search-response"]
-  }
-}
-
-/**
- * ChatbotClient handles the connection and media management for a real-time
- * voice and video interaction with an AI bot.
- */
-class ChatbotClient {
-  constructor() {
-    // Initialize client state
-    this.rtviClient = 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');
-    this.searchResultContainer = document.getElementById('search-result-container');
-
-    // 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}`);
-  }
-
-  /**
-   * Check for available media tracks and set them up if present
-   * This is called when the bot is ready or when the transport state changes to ready
-   */
-  setupMediaTracks() {
-    if (!this.rtviClient) return;
-
-    // Get current tracks from the client
-    const tracks = this.rtviClient.tracks();
-
-    // Set up any available bot tracks
-    if (tracks.bot?.audio) {
-      this.setupAudioTrack(tracks.bot.audio);
-    }
-  }
-
-  /**
-   * Set up listeners for track events (start/stop)
-   * This handles new tracks being added during the session
-   */
-  setupTrackListeners() {
-    if (!this.rtviClient) return;
-
-    // Listen for new tracks starting
-    this.rtviClient.on(RTVIEvent.TrackStarted, (track, participant) => {
-      // Only handle non-local (bot) tracks
-      if (!participant?.local && track.kind === 'audio') {
-        this.setupAudioTrack(track);
-      }
-    });
-
-    // Listen for tracks stopping
-    this.rtviClient.on(RTVIEvent.TrackStopped, (track, participant) => {
-      this.log(
-        `Track stopped event: ${track.kind} from ${
-          participant?.name || 'unknown'
-        }`
-      );
-    });
-  }
-
-  /**
-   * Set up an audio track for playback
-   * Handles both initial setup and track updates
-   */
-  setupAudioTrack(track) {
-    this.log('Setting up audio track');
-    // 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]);
-  }
-
-  /**
-   * Initialize and connect to the bot
-   * This sets up the RTVI client, initializes devices, and establishes the connection
-   */
-  async connect() {
-    try {
-      // Create a new Daily transport for WebRTC communication
-      const transport = new DailyTransport();
-
-      // Initialize the RTVI client with our configuration
-      this.rtviClient = new RTVIClient({
-        transport,
-        params: {
-          // The baseURL and endpoint of your bot server that the client will connect to
-          baseUrl: 'http://localhost:7860',
-          endpoints: {
-            connect: '/connect',
-          },
-        },
-        enableMic: true, // Enable microphone for user input
-        enableCam: false,
-        callbacks: {
-          // Handle connection state changes
-          onConnected: () => {
-            this.updateStatus('Connected');
-            this.connectBtn.disabled = true;
-            this.disconnectBtn.disabled = false;
-            this.log('Client connected');
-          },
-          onDisconnected: () => {
-            this.updateStatus('Disconnected');
-            this.connectBtn.disabled = false;
-            this.disconnectBtn.disabled = true;
-            this.log('Client disconnected');
-          },
-          // Handle transport state changes
-          onTransportStateChanged: (state) => {
-            this.updateStatus(`Transport: ${state}`);
-            this.log(`Transport state changed: ${state}`);
-            if (state === 'ready') {
-              this.setupMediaTracks();
-            }
-          },
-          // Handle bot connection events
-          onBotConnected: (participant) => {
-            this.log(`Bot connected: ${JSON.stringify(participant)}`);
-          },
-          onBotDisconnected: (participant) => {
-            this.log(`Bot disconnected: ${JSON.stringify(participant)}`);
-          },
-          onBotReady: (data) => {
-            this.log(`Bot ready: ${JSON.stringify(data)}`);
-            this.setupMediaTracks();
-          },
-          // Transcript events
-          onUserTranscript: (data) => {
-            // Only log final transcripts
-            if (data.final) {
-              this.log(`User: ${data.text}`);
-            }
-          },
-          onBotTranscript: (data) => {
-            this.log(`Bot: ${data.text}`);
-          },
-          // Error handling
-          onMessageError: (error) => {
-            console.log('Message error:', error);
-          },
-          onError: (error) => {
-            console.log('Error:', error);
-          },
-        },
-      });
-      //this.rtviClient.setLogLevel(LogLevel.DEBUG)
-      this.rtviClient.registerHelper("llm", new SearchResponseHelper(this.searchResultContainer))
-
-      // Set up listeners for media track events
-      this.setupTrackListeners();
-
-      // Initialize audio devices
-      this.log('Initializing devices...');
-      await this.rtviClient.initDevices();
-
-      // Connect to the bot
-      this.log('Connecting to bot...');
-      await this.rtviClient.connect();
-
-      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.rtviClient) {
-        try {
-          await this.rtviClient.disconnect();
-        } catch (disconnectError) {
-          this.log(`Error during disconnect: ${disconnectError.message}`);
-        }
-      }
-    }
-  }
-
-  /**
-   * Disconnect from the bot and clean up media resources
-   */
-  async disconnect() {
-    if (this.rtviClient) {
-      try {
-        // Disconnect the RTVI client
-        await this.rtviClient.disconnect();
-        this.rtviClient = null;
-
-        // Clean up audio
-        if (this.botAudio.srcObject) {
-          this.botAudio.srcObject.getTracks().forEach((track) => track.stop());
-          this.botAudio.srcObject = null;
-        }
-
-        // Clean up video
-        this.searchResultContainer.innerHTML = '';
-      } catch (error) {
-        this.log(`Error disconnecting: ${error.message}`);
-      }
-    }
-  }
-}
-
-// Initialize the client when the page loads
-window.addEventListener('DOMContentLoaded', () => {
-  new ChatbotClient();
-});

examples/news-chatbot/client/javascript/src/style.css

@@ -1,134 +0,0 @@
-body {
-  margin: 0;
-  padding: 20px;
-  font-family: Arial, sans-serif;
-  background-color: #f0f0f0;
-}
-
-.container {
-  max-width: 1200px;
-  margin: 0 auto;
-}
-
-.status-bar {
-  display: flex;
-  justify-content: space-between;
-  align-items: center;
-  padding: 10px;
-  background-color: #fff;
-  border-radius: 8px;
-  margin-bottom: 20px;
-}
-
-.controls button {
-  padding: 8px 16px;
-  margin-left: 10px;
-  border: none;
-  border-radius: 4px;
-  cursor: pointer;
-}
-
-#connect-btn {
-  background-color: #4caf50;
-  color: white;
-}
-
-#disconnect-btn {
-  background-color: #f44336;
-  color: white;
-}
-
-button:disabled {
-  opacity: 0.5;
-  cursor: not-allowed;
-}
-
-.main-content {
-  background-color: #fff;
-  border-radius: 8px;
-  padding: 20px;
-  margin-bottom: 20px;
-}
-
-.bot-container {
-  display: flex;
-  flex-direction: column;
-  align-items: center;
-}
-
-#search-result-container {
-  background-color: #e0e0e0;
-  padding: 20px;
-  width: calc(100% - 40px);
-  height: 450px;
-  overflow: auto;
-}
-
-/* Container for all content */
-.content-container {
-    display: flex;
-    flex-direction: column;
-    gap: 20px; /* Space between elements */
-    font-family: Arial, sans-serif;
-}
-
-/* Styles for the search result */
-.search-result {
-    font-size: 16px;
-    line-height: 1.5;
-    color: #333;
-}
-
-/* Styles for the sources container */
-.sources {
-    display: flex;
-    flex-direction: column;
-    gap: 8px; /* Space between source links */
-}
-
-.sources-title {
-    font-size: 16px;
-    font-weight: bold;
-    color: #444;
-}
-
-/* Styles for source links */
-.source-link {
-    text-decoration: none;
-    color: #1a73e8;
-}
-
-.source-link:hover {
-    text-decoration: underline;
-}
-
-/* Styles for the iframe container */
-.iframe-container {
-    flex: none;
-    width: 100%;
-    height: 400px; /* Adjust height as needed */
-    border: none;
-}
-
-.debug-panel {
-  background-color: #fff;
-  border-radius: 8px;
-  padding: 20px;
-}
-
-.debug-panel h3 {
-  margin: 0 0 10px 0;
-  font-size: 16px;
-  font-weight: bold;
-}
-
-#debug-log {
-  height: 200px;
-  overflow-y: auto;
-  background-color: #f8f8f8;
-  padding: 10px;
-  border-radius: 4px;
-  font-family: monospace;
-  font-size: 12px;
-  line-height: 1.4;
-}

examples/news-chatbot/client/javascript/vite.config.js

@@ -1,13 +0,0 @@
-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/news-chatbot/server/README.md

@@ -1,52 +0,0 @@
-# News Chatbot 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
-DEEPGRAM_API_KEY=        # Your Deepgram API key
-GOOGLE_API_KEY=          # Your Google/Gemini 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,deepgram,google,cartesia,openai,silero]"
-```
-
-Run the server:
-
-```bash
-python server.py
-```

examples/news-chatbot/server/env.example

@@ -1,5 +0,0 @@
-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=
-DEEPGRAM_API_KEY=
-GOOGLE_API_KEY=

examples/news-chatbot/server/news_bot.py

@@ -1,166 +0,0 @@
-#
-# Copyright (c) 2024-2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import os
-import sys
-from pathlib import Path
-
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame
-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.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIProcessor
-from pipecat.services.cartesia import CartesiaTTSService
-from pipecat.services.deepgram import DeepgramSTTService
-from pipecat.services.google import GoogleLLMService, LLMSearchResponseFrame
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-from pipecat.utils.text.markdown_text_filter import MarkdownTextFilter
-
-sys.path.append(str(Path(__file__).parent.parent))
-from runner import configure
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-# Function handlers for the LLM
-# https://ai.google.dev/gemini-api/docs/grounding?lang=python#dynamic-retrieval
-# Some queries are likely to benefit more from Grounding with Google Search than others.
-# The dynamic retrieval feature gives you additional control over when to use Grounding with Google Search.
-# If the dynamic retrieval mode is unspecified, Grounding with Google Search is always triggered.
-# If the mode is set to dynamic, the model decides when to use grounding based on a threshold that you can configure.
-# The threshold is a floating-point value in the range [0,1] and defaults to 0.3.
-# If the threshold value is 0, the response is always grounded with Google Search; if it's 1, it never is.
-search_tool = {
-    "google_search_retrieval": {
-        "dynamic_retrieval_config": {
-            "mode": "MODE_DYNAMIC",
-            "dynamic_threshold": 0,
-        }  # always grounding
-    }
-}
-tools = [search_tool]
-
-system_instruction = """
-You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so ensure they are formatted in plain text without special characters (e.g., *, _, -) or overly complex formatting.
-
-Guidelines:
-- Use the Google search API to retrieve the current date and provide the latest news.
-- Always deliver accurate and concise responses.
-- Ensure all responses are clear, using plain text only. Avoid any special characters or symbols.
-
-Start every interaction by asking how you can assist the user.
-"""
-
-
-class LLMSearchLoggerProcessor(FrameProcessor):
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
-
-        if isinstance(frame, LLMSearchResponseFrame):
-            print(f"LLMSearchLoggerProcessor: {frame}")
-
-        await self.push_frame(frame)
-
-
-async def main():
-    async with aiohttp.ClientSession() as session:
-        (room_url, token) = await configure(session)
-
-        transport = DailyTransport(
-            room_url,
-            token,
-            "Latest news!",
-            DailyParams(
-                audio_out_enabled=True,
-                vad_enabled=True,
-                vad_analyzer=SileroVADAnalyzer(),
-                vad_audio_passthrough=True,
-            ),
-        )
-
-        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-
-        tts = CartesiaTTSService(
-            api_key=os.getenv("CARTESIA_API_KEY"),
-            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
-            text_filter=MarkdownTextFilter(),
-        )
-
-        llm = GoogleLLMService(
-            api_key=os.getenv("GOOGLE_API_KEY"),
-            system_instruction=system_instruction,
-            tools=tools,
-        )
-
-        context = OpenAILLMContext(
-            [
-                {
-                    "role": "user",
-                    "content": "Start by greeting the user warmly, introducing yourself, and mentioning the current day. Be friendly and engaging to set a positive tone for the interaction.",
-                }
-            ],
-        )
-        context_aggregator = llm.create_context_aggregator(context)
-
-        llm_search_logger = LLMSearchLoggerProcessor()
-
-        #
-        # RTVI events for Pipecat client UI
-        #
-        rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
-
-        pipeline = Pipeline(
-            [
-                transport.input(),
-                stt,
-                rtvi,
-                context_aggregator.user(),
-                llm,
-                llm_search_logger,
-                tts,
-                transport.output(),
-                context_aggregator.assistant(),
-            ]
-        )
-
-        task = PipelineTask(
-            pipeline,
-            PipelineParams(
-                allow_interruptions=True,
-                observers=[rtvi.observer()],
-            ),
-        )
-
-        @rtvi.event_handler("on_client_ready")
-        async def on_client_ready(rtvi):
-            await rtvi.set_bot_ready()
-
-        @transport.event_handler("on_first_participant_joined")
-        async def on_first_participant_joined(transport, participant):
-            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.cancel()
-
-        runner = PipelineRunner()
-        await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

examples/news-chatbot/server/requirements.txt

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

examples/news-chatbot/server/runner.py

@@ -1,63 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import argparse
-import os
-
-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: argparse.ArgumentParser | None = 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/news-chatbot/server/server.py

@@ -1,147 +0,0 @@
-#
-# 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 = "news_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,
-    )