MiniMaxHttpTTSService: renamed from Hailuo and move to services/minimax/tts.py

examples: updates for dependabot 05/14/2025

CHANGELOG.md

@@ -5,6 +5,66 @@ All notable changes to **Pipecat** will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Added
+
+- Added support for a new TTS service, `MiniMaxHttpTTSService`.
+  (see https://www.minimax.io/audio)
+
+- A new function `FrameProcessor.setup()` has been added to allow setting up
+  frame processors before receiving a `StartFrame`. This is what's happening
+  internally: `FrameProcessor.setup()` is called, `StartFrame` is pushed from
+  the beginning of the pipeline, your regular pipeline operations, `EndFrame` or
+  `CancelFrame` are pushed from the beginning of the pipeline and finally
+  `FrameProcessor.cleanup()` is called.
+
+- Added support for OpenTelemetry tracing in Pipecat. This initial
+  implementation includes:
+
+  - A `setup_tracing` method where you can specify your OpenTelemetry exporter
+  - Service decorators for STT (`@traced_stt`), LLM (`@traced_llm`), and TTS
+    (`@traced_tts`) which trace the execution and collect properties and
+    metrics (TTFB, token usage, character counts, etc.)
+  - Class decorators that provide execution tracking; these are generic and can
+    be used for service tracking as needed
+  - Spans that help track traces on a per conversations and turn basis:
+
+  ```
+  conversation-uuid
+  ├── turn-1
+  │   ├── stt_deepgramsttservice
+  │   ├── llm_openaillmservice
+  │   └── tts_cartesiattsservice
+  ...
+  └── turn-n
+      └── ...
+  ```
+
+  By default, Pipecat has implemented service decorators to trace execution of
+  STT, LLM, and TTS services. You can enable tracing by setting `enable_tracing`
+  to `True` in the PipelineTask.
+
+- Added `TurnTrackingObserver`, which tracks the start and end of a user/bot
+  turn pair and emits events `on_turn_started` and `on_turn_stopped`
+  corresponding to the start and end of a turn, respectively.
+
+- Allow passing observers to `run_test()` while running unit tests.
+
+### Changed
+
+- `GoogleLLMService` has been updated to use `google-genai` instead of the
+  deprecated `google-generativeai`.
+
+### Other
+
+- Added an `open-telemetry-tracing` example, showing how to setup tracing. The
+  example also includes Jaeger as an open source OpenTelemetry client to review
+  traces from the example runs.
+
+- Added foundational example `29-turn-tracking-observer.py` to show how to use
+  the `TurnTrackingObserver.
+
 ## [0.0.67] - 2025-05-07
 
 ### Added

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

@@ -12,7 +12,7 @@
         "@daily-co/daily-js": "0.74.0"
       },
       "devDependencies": {
-        "vite": "^6.0.9"
+        "vite": "^6.3.5"
       }
     },
     "node_modules/@babel/runtime": {
@@ -999,9 +999,9 @@
       }
     },
     "node_modules/vite": {
-      "version": "6.3.3",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.3.tgz",
-      "integrity": "sha512-5nXH+QsELbFKhsEfWLkHrvgRpTdGJzqOZ+utSdmPTvwHmvU6ITTm3xx+mRusihkcI8GeC7lCDyn3kDtiki9scw==",
+      "version": "6.3.5",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.5.tgz",
+      "integrity": "sha512-cZn6NDFE7wdTpINgs++ZJ4N49W2vRp8LCKrn3Ob1kYNtOo21vfDoaV5GzBfLU4MovSAB8uNRm4jgzVQZ+mBzPQ==",
       "dev": true,
       "dependencies": {
         "esbuild": "^0.25.0",

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

@@ -12,7 +12,7 @@
   "license": "ISC",
   "description": "",
   "devDependencies": {
-    "vite": "^6.0.9"
+    "vite": "^6.3.5"
   },
   "dependencies": {
     "@daily-co/daily-js": "0.74.0"

examples/deployment/modal-example/.gitignore

@@ -1,3 +1,6 @@
+# Modal clone
+modal-examples
+
 # Python
 __pycache__/
 *.py[cod]

examples/deployment/modal-example/README.md

@@ -1,24 +1,44 @@
 # Deploying Pipecat to Modal.com
 
-Barebones deployment example for [modal.com](https://www.modal.com)
+Deployment example for [modal.com](https://www.modal.com). This example demonstrates how to deploy a FastAPI webapp to Modal with an RTVI compatible `/connect` endpoint that launches a Pipecat pipeline in a separate Modal container and returns a room/token for the client to join. This example also supports providing a parameter to the `/connect` endpoint for specifying which Pipecat pipeline to launch; openai, gemini, or vllm. The vllm pipeline points to a self-hosted OpenAI compatible LLM, using a llama model (neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w4a16), deployed to Modal.
 
-1. Install dependencies
-
-```bash
-python -m venv venv
-source venv/bin/active # or OS equivalent
-pip install -r requirements.txt
-```
-
-2. Setup .env
+# Running this Example
+
+## Prerequisites
+
+Setup a Modal account and install it on your machine if you have not already, following their easy 3-steps in their [Getting Started Guide](https://modal.com/docs/guide#getting-started)
+
+## Deploy a self-serve LLM
+
+1. Follow the Modal Guide and example for [Deploying an OpenAI-compatible LLM service with vLLM](https://modal.com/docs/examples/vllm_inference).
+
+    The TLDR, though, is to simply do the following from within this directory:
+
+   ```bash
+   git clone https://github.com/modal-labs/modal-examples
+   cd modal-examples
+   modal deploy 06_gpu_and_ml/llm-serving/vllm_inference.py
+   ```
+
+2. Jot down the endpoint from the previous step to use in the bot_vllm file mentioned below. It will look something like: `https://<Modal workspace>--example-vllm-openai-compatible-serve.modal.run`
+
+**Note:** This Modal example is their [initial getting started example](https://modal.com/docs/examples/vllm_inference) with a Llama-3.1 model. By default, it will tear down the container after 15 minutes of inactivity and can take 5-10 minutes to re-start, during which time it is unusable. So for the purposes of just getting started and this example, we recommend visiting the `/docs` endpoint (`https://<Modal workspace>--example-vllm-openai-compatible-serve.modal.run/docs`) for your deployed llm in a browser to trigger the cold start. Then wait for the page to load, indicating its ready before trying to connect your client.
+
+## Deploy FastAPI App and Pipecat pipeline to Modal 
+
+1. Setup environment variables
 
 ```bash
+cd server
 cp env.example .env
+# Modify .env to provide your service API Keys
 ```
 
 Alternatively, you can configure your Modal app to use [secrets](https://modal.com/docs/guide/secrets)
 
-3. Test the app locally
+1. Update the `modal_url` in `server/src/bot_vllm.py` to point to the url produced from the self-serve llm deploy, mentioned above.
+
+2. From within the `server` directory, test the app locally:
 
 ```bash
 modal serve app.py
@@ -30,8 +50,34 @@ modal serve app.py
 modal deploy app.py
 ```
 
-## Configuration options
+5. Jot down the endpoint from the previous step to use in the client's app.js file mentioned its README. It will look something like: `https://<Modal workspace>--pipecat-modal-fastapi-app.modal.run`
 
-This app sets some sensible defaults for reducing cold starts, such as `minkeep_warm=1`, which will keep at least 1 warm instance ready for your bot function.
+## Launch and Talk to your Bots running on Modal
 
-It has been configured to only allow a concurrency of 1 (`max_inputs=1`) as each user will require their own running function.
+## Option 1: Direct Link
+
+Simply click on the url displayed after running the server or deploy step to launch an agent and be redirected to a Daily room to talk with the launched bot. This will use the OpenAI pipeline.
+
+## Option 2: Connect via an RTVI Client
+
+Follow the instructions provided in the [client folder's README](client/javascript/README.md) for building and running a custom client that connects to your Modal endpoint. The provided client provides a dropdown for choosing which bot pipeline to run.
+
+# Navigating your llm, server, and Pipecat logs
+
+In your [Modal dashboard](https://modal.com/apps), you should have two Apps listed under Live Apps:
+
+1. `example-vllm-openai-compatible`: This App contains the containers and logs used to run your self-hosted LLM. There will be just one App Function listed: `serve`. Click on this function to view logs for your LLM.
+2. `pipecat-modal`: This App contains the containers and logs used to run your `connect` endpoints and Pipecat pipelines. It will list two App Functions:
+    1. `fastapi_app`: This function is running the endpoints that your client will interact with and initiate starting a new pipeline (`/`, `/connect`, `/status`). Click on this function to see logs for each endpoint hit.
+    2. `bot_runner`: This function handles launching and running a bot pipeline. Click on this function to get a list of all pipeline runs and access each run's logs.
+
+## Diagram of Deployment
+
+![](diagram.jpg)
+
+# Modal + Pipecat Tips
+
+- In most other Pipecat examples, we use Popen to launch the pipeline process from the /connect endpoint. In this example, we instead use a Modal function with its own Modal image defined. This change ensures that each run of the Pipeline happens in a isolated, customizable container.
+- For the FastAPI and most common Pipecat Pipeline containers, a default debian_slim CPU-only should be all that's required to run. GPU containers are needed for self-hosted services.
+- To minimize cold starts of the pipeline and reduce latency for users, set `min_containers=1` on the Modal Function that launches the pipeline to ensure at least one warm instance of your function is always available.
+- For next steps on running a self-hosted llm and reducing latency, check out all of [Modal's LLM examples](https://modal.com/docs/examples/vllm_inference).

examples/deployment/modal-example/app.py

@@ -1,80 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-import aiohttp
-import modal
-from bot import _voice_bot_process
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse
-from loguru import logger
-
-MAX_SESSION_TIME = 15 * 60  # 15 minutes
-
-app = modal.App("pipecat-modal")
-
-
-image = modal.Image.debian_slim(python_version="3.12").pip_install_from_requirements(
-    "requirements.txt"
-)
-
-
-@app.function(
-    image=image,
-    cpu=1.0,
-    secrets=[modal.Secret.from_dotenv()],
-    keep_warm=1,
-    enable_memory_snapshot=True,
-    max_inputs=1,  # Do not reuse instances across requests
-    retries=0,
-)
-def launch_bot_process(room_url: str, token: str):
-    _voice_bot_process(room_url, token)
-
-
-@app.function(
-    image=image,
-    secrets=[modal.Secret.from_dotenv()],
-)
-@modal.web_endpoint(method="POST")
-async def start():
-    from pipecat.transports.services.helpers.daily_rest import (
-        DailyRESTHelper,
-        DailyRoomParams,
-    )
-
-    logger.info("Request received")
-
-    async with aiohttp.ClientSession() as session:
-        daily_rest_helper = DailyRESTHelper(
-            daily_api_key=os.getenv("DAILY_API_KEY", ""),
-            daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"),
-            aiohttp_session=session,
-        )
-
-        # Create new Daily room
-        room = await daily_rest_helper.create_room(DailyRoomParams())
-        if not room.url:
-            raise HTTPException(
-                status_code=500,
-                detail="Unable to create room",
-            )
-        logger.info(f"Created room: {room.url}")
-
-        # Create bot token for room
-        token = await daily_rest_helper.get_token(room.url, MAX_SESSION_TIME)
-        if not token:
-            raise HTTPException(status_code=500, detail=f"Failed to get token for room: {room.url}")
-
-        logger.info(f"Bot token created: {token}")
-
-        # Spawn a new bot process
-        launch_bot_process.spawn(room_url=room.url, token=token)
-
-        # Return room URL to the user to join
-        # Note: in production, you would want to return a token to the user
-        return JSONResponse(content={"room_url": room.url, token: token})

examples/deployment/modal-example/bot.py

@@ -1,95 +0,0 @@
-#
-# Copyright (c) 2024–2025, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import os
-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.tts import CartesiaTTSService
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.services.daily import DailyParams, DailyTransport
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-async def main(room_url: str, token: str):
-    transport = DailyTransport(
-        room_url,
-        token,
-        "bot",
-        DailyParams(
-            audio_in_enabled=True,
-            audio_out_enabled=True,
-            transcription_enabled=True,
-            vad_analyzer=SileroVADAnalyzer(),
-        ),
-    )
-
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY", ""), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121"
-    )
-
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
-
-    messages = [
-        {
-            "role": "system",
-            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
-        },
-    ]
-
-    context = OpenAILLMContext(messages)
-    context_aggregator = llm.create_context_aggregator(context)
-
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            context_aggregator.user(),
-            llm,
-            tts,
-            transport.output(),
-            context_aggregator.assistant(),
-        ]
-    )
-
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            allow_interruptions=True,
-            enable_metrics=True,
-            enable_usage_metrics=True,
-            report_only_initial_ttfb=True,
-        ),
-    )
-
-    @transport.event_handler("on_first_participant_joined")
-    async def on_first_participant_joined(transport, participant):
-        await transport.capture_participant_transcription(participant["id"])
-        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
-
-    @transport.event_handler("on_participant_left")
-    async def on_participant_left(transport, participant, reason):
-        await task.cancel()
-
-    runner = PipelineRunner()
-
-    await runner.run(task)
-
-
-def _voice_bot_process(room_url: str, token: str):
-    asyncio.run(main(room_url, token))

examples/deployment/modal-example/client/javascript/.gitignore

@@ -0,0 +1 @@
+node_modules

examples/deployment/modal-example/client/javascript/README.md

@@ -0,0 +1,29 @@
+# JavaScript Implementation
+
+Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/js/introduction).
+
+## Setup
+
+1. Deploy the Modal server. See the main [README](../../README).
+
+2. Navigate to the `client/javascript` directory:
+
+```bash
+cd client/javascript
+```
+
+3. Modify the baseUrl in src/app.js to point to your deployed Modal endpoint
+
+4. Install dependencies:
+
+```bash
+npm install
+```
+
+5. Run the client app:
+
+```
+npm run dev
+```
+
+6. Visit http://localhost:5173 in your browser.

examples/deployment/modal-example/client/javascript/index.html

@@ -0,0 +1,49 @@
+<!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">
+          <select id="bot-selector">
+            <option value="openai">OpenAI</option>
+            <option value="gemini">Gemini</option>
+            <option value="vllm">Llama</option>
+          </select>
+          <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="bot-video-container"></div>
+          <audio id="bot-audio" autoplay></audio>
+        </div>
+      </div>
+
+      <div class="device-bar">
+        <div class="device-controls">
+          <select id="device-selector"></select>
+          <button id="mic-toggle-btn">Mute Mic</button>
+        </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/deployment/modal-example/client/javascript/package.json

@@ -0,0 +1,21 @@
+{
+  "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": "^6.3.5"
+  },
+  "dependencies": {
+    "@pipecat-ai/client-js": "^0.3.5",
+    "@pipecat-ai/daily-transport": "^0.3.10"
+  }
+}

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

@@ -0,0 +1,381 @@
+/**
+ * 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 { RTVIClient, RTVIEvent } from '@pipecat-ai/client-js';
+import { DailyTransport } from '@pipecat-ai/daily-transport';
+
+/**
+ * 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.initializeClientAndTransport();
+    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.botVideoContainer = document.getElementById('bot-video-container');
+    this.deviceSelector = document.getElementById('device-selector');
+
+    // 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());
+
+    // Populate device selector
+    this.rtviClient.getAllMics().then((mics) => {
+      console.log('Available mics:', mics);
+      mics.forEach((device) => {
+        const option = document.createElement('option');
+        option.value = device.deviceId;
+        option.textContent = device.label || `Microphone ${device.deviceId}`;
+        this.deviceSelector.appendChild(option);
+      });
+    });
+    this.deviceSelector.addEventListener('change', (event) => {
+      const selectedDeviceId = event.target.value;
+      console.log('Selected device ID:', selectedDeviceId);
+      this.rtviClient.updateMic(selectedDeviceId);
+    });
+
+    // Handle mic mute/unmute toggle
+    const micToggleBtn = document.getElementById('mic-toggle-btn');
+
+    micToggleBtn.addEventListener('click', () => {
+      let micEnabled = this.rtviClient.isMicEnabled;
+      micToggleBtn.textContent = micEnabled ? 'Unmute Mic' : 'Mute Mic';
+      this.rtviClient.enableMic(!micEnabled);
+      // Add logic to mute/unmute the mic
+      if (micEnabled) {
+        console.log('Mic muted');
+        // Add code to mute the mic
+      } else {
+        console.log('Mic unmuted');
+        // Add code to unmute the mic
+      }
+    });
+  }
+
+  /**
+   * Set up the RTVI client and Daily transport
+   */
+  async initializeClientAndTransport() {
+    // Initialize the RTVI client with a DailyTransport and our configuration
+    this.rtviClient = new RTVIClient({
+      transport: new DailyTransport(),
+      params: {
+        // REPLACE WITH YOUR MODAL URL ENDPOINT
+        baseUrl:
+          'https://<Modal workspace>--pipecat-modal-bot-launcher.modal.run',
+        endpoints: {
+          connect: '/connect',
+        },
+        requestData: {
+          bot_name: 'openai',
+        },
+      },
+      enableMic: true, // Enable microphone for user input
+      enableCam: false,
+      callbacks: {
+        // 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 === 'connecting') {
+            window.startTime = Date.now();
+          }
+          if (state === 'ready') {
+            this.setupMediaTracks();
+            console.warn('TIME TO BOT READY:', Date.now() - window.startTime);
+          }
+        },
+        // 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: ${data.text}`);
+        },
+        // Error handling
+        onMessageError: (error) => {
+          console.log('Message error:', error);
+        },
+        onMicUpdated: (data) => {
+          console.log('Mic updated:', data);
+          this.deviceSelector.value = data.deviceId;
+        },
+        onError: (error) => {
+          console.log('Error:', JSON.stringify(error));
+        },
+      },
+    });
+
+    // Set up listeners for media track events
+    this.setupTrackListeners();
+
+    await this.rtviClient.initDevices();
+    window.client = this.rtviClient;
+  }
+
+  /**
+   * Add a timestamped message to the debug log
+   */
+  log(message) {
+    const entry = document.createElement('div');
+    entry.textContent = `${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);
+    }
+    if (tracks.bot?.video) {
+      this.setupVideoTrack(tracks.bot.video);
+    }
+  }
+
+  /**
+   * 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) {
+        if (track.kind === 'audio') {
+          this.setupAudioTrack(track);
+        } else if (track.kind === 'video') {
+          this.setupVideoTrack(track);
+        }
+        this.log(
+          `Track started event: ${track.kind} from ${
+            participant?.name || 'unknown'
+          }`
+        );
+      } else {
+        this.log('Local mic unmuted');
+      }
+    });
+
+    // Listen for tracks stopping
+    this.rtviClient.on(RTVIEvent.TrackStopped, (track, participant) => {
+      if (participant.local) {
+        this.log('Local mic muted');
+        return;
+      }
+      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]);
+  }
+
+  /**
+   * Set up a video track for display
+   * Handles both initial setup and track updates
+   */
+  setupVideoTrack(track) {
+    this.log('Setting up video track');
+    const videoEl = document.createElement('video');
+    videoEl.autoplay = true;
+    videoEl.playsInline = true;
+    videoEl.muted = true;
+    videoEl.style.width = '100%';
+    videoEl.style.height = '100%';
+    videoEl.style.objectFit = 'cover';
+
+    // Check if we're already displaying this track
+    if (this.botVideoContainer.querySelector('video')?.srcObject) {
+      const oldTrack = this.botVideoContainer
+        .querySelector('video')
+        .srcObject.getVideoTracks()[0];
+      if (oldTrack?.id === track.id) return;
+    }
+
+    // Create a new MediaStream with the track and set it as the video source
+    videoEl.srcObject = new MediaStream([track]);
+    this.botVideoContainer.innerHTML = '';
+    this.botVideoContainer.appendChild(videoEl);
+  }
+
+  /**
+   * Initialize and connect to the bot
+   * This sets up the RTVI client, initializes devices, and establishes the connection
+   */
+  async connect() {
+    try {
+      const botSelector = document.getElementById('bot-selector');
+      const selectedBot = botSelector.value;
+      this.rtviClient.params.requestData.bot_name = selectedBot;
+
+      // Initialize audio/video devices
+      this.log('Initializing devices...');
+      await this.rtviClient.initDevices();
+
+      // Connect to the bot
+      this.log(`Connecting to bot: ${selectedBot}`);
+      await this.rtviClient.connect();
+
+      this.log('Connection complete');
+    } catch (error) {
+      // Handle any errors during connection
+      console.error('Connection error:', error);
+      this.log(`Error connecting: ${JSON.stringify(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();
+
+        // Clean up audio
+        if (this.botAudio.srcObject) {
+          this.botAudio.srcObject.getTracks().forEach((track) => track.stop());
+          this.botAudio.srcObject = null;
+        }
+
+        // Clean up video
+        if (this.botVideoContainer.querySelector('video')?.srcObject) {
+          const video = this.botVideoContainer.querySelector('video');
+          video.srcObject.getTracks().forEach((track) => track.stop());
+          video.srcObject = null;
+        }
+        this.botVideoContainer.innerHTML = '';
+      } catch (error) {
+        this.log(`Error disconnecting: ${error.message}`);
+      }
+    }
+  }
+}
+
+// Initialize the client when the page loads
+window.addEventListener('DOMContentLoaded', () => {
+  new ChatbotClient();
+});

examples/deployment/modal-example/client/javascript/src/style.css

@@ -0,0 +1,135 @@
+body {
+  margin: 0;
+  padding: 20px;
+  font-family: Arial, sans-serif;
+  background-color: #f0f0f0;
+}
+
+.container {
+  max-width: 1200px;
+  margin: 0 auto;
+}
+
+.status-bar,
+.device-bar {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  padding: 10px;
+  background-color: #fff;
+  border-radius: 8px;
+  margin-bottom: 20px;
+}
+
+.controls,
+.device-controls {
+  display: flex;
+  align-items: center;
+  gap: 10px; /* Adds spacing between elements */
+}
+
+.device-controls {
+  margin-left: auto;
+}
+
+.controls button,
+.device-controls button {
+  padding: 8px 16px;
+  margin-left: 10px;
+  border: none;
+  border-radius: 4px;
+  cursor: pointer;
+}
+
+#bot-selector,
+#device-selector {
+  padding: 8px 16px;
+  padding-right: 40px;
+  border: none;
+  border-radius: 4px;
+  background-color: #6c757d; /* Gray background */
+  color: white; /* White text */
+  cursor: pointer;
+  appearance: none; /* Removes default browser styling for dropdowns */
+  background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24' fill='white'%3E%3Cpath d='M7 10l5 5 5-5z'/%3E%3C/svg%3E"); /* Custom arrow */
+  background-repeat: no-repeat;
+  background-position: right 8px center; /* Position the arrow */
+}
+
+#bot-selector:focus,
+#device-selector:focus {
+  outline: none;
+  box-shadow: 0 0 4px rgba(0, 0, 0, 0.3); /* Add a subtle focus effect */
+}
+
+#connect-btn {
+  background-color: #4caf50;
+  color: white;
+}
+
+#disconnect-btn {
+  background-color: #f44336;
+  color: white;
+}
+
+#mic-toggle-btn {
+}
+
+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/deployment/modal-example/env.example

@@ -1,3 +0,0 @@
-DAILY_API_KEY=
-OPENAI_API_KEY=
-CARTESIA_API_KEY=

examples/deployment/modal-example/requirements.txt

@@ -1,4 +0,0 @@
-python-dotenv==1.0.1
-modal==0.71.3
-pipecat-ai[daily,silero,cartesia,openai]
-fastapi==0.115.6

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

@@ -0,0 +1,307 @@
+"""modal_example.
+
+This module shows a simple example of how to deploy a bot using Modal and FastAPI.
+
+It includes:
+- FastAPI endpoints for starting agents and checking bot statuses.
+- Dynamic loading of bot implementations.
+- Use of a Daily transport for bot communication.
+"""
+
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import importlib
+import os
+from contextlib import asynccontextmanager
+from typing import Any, Dict, Literal
+
+import aiohttp
+import modal
+from fastapi import APIRouter, FastAPI, HTTPException
+from fastapi.responses import JSONResponse, RedirectResponse
+from pydantic import BaseModel
+
+# container specifications for the FastAPI web server
+web_image = (
+    modal.Image.debian_slim(python_version="3.13")
+    .pip_install_from_requirements("requirements.txt")
+    .pip_install("pipecat-ai[daily]")
+    .add_local_dir("src", remote_path="/root/src")
+)
+
+# container specifications for the Pipecat pipeline
+bot_image = (
+    modal.Image.debian_slim(python_version="3.13")
+    .apt_install("ffmpeg")
+    .pip_install_from_requirements("requirements.txt")
+    .pip_install("pipecat-ai[daily,elevenlabs,openai,silero,google]")
+    .add_local_dir("src", remote_path="/root/src")
+)
+
+app = modal.App("pipecat-modal", secrets=[modal.Secret.from_dotenv()])
+
+router = APIRouter()
+
+bot_jobs = {}
+daily_helpers = {}
+
+# Names of all supported bot implementations
+# These correspond to the bot files in the src directory
+BotName = Literal["openai", "gemini", "vllm"]
+
+
+def cleanup():
+    """Cleanup function to terminate all bot processes.
+
+    Called during server shutdown.
+    """
+    for entry in bot_jobs.values():
+        func = modal.FunctionCall.from_id(entry[0])
+        if func:
+            func.cancel()
+
+
+def get_bot_file(bot_name: BotName) -> str:
+    """Retrieve the bot file name corresponding to the provided bot_name.
+
+    Args:
+        bot_name (BotName): The name of the bot (e.g., 'openai', 'gemini', 'vllm').
+
+    Returns:
+        str: The file name corresponding to the bot implementation.
+
+    Raises:
+        ValueError: If the bot name is invalid or not supported.
+    """
+    # bot_implementation = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    bot_implementation = bot_name.lower().strip()
+    if not bot_implementation:
+        bot_implementation = "openai"
+    if bot_implementation not in ["openai", "gemini", "vllm"]:
+        raise ValueError(
+            f"Invalid BOT_IMPLEMENTATION: {bot_implementation}. Must be 'openai' or 'gemini' or 'vllm'"
+        )
+
+    return f"bot_{bot_implementation}"
+
+
+def get_runner(path: str, bot_file: str) -> callable:
+    """Dynamically import the run_bot function based on the bot name.
+
+    Args:
+        path (str): The path to the bot files (e.g., 'src').
+        bot_file (str): The file name of the bot implementation (e.g., 'openai', 'gemini', 'vllm').
+
+    Returns:
+        function: The run_bot function from the specified bot module.
+
+    Raises:
+        ImportError: If the specified bot module or run_bot function is not found.
+    """
+    try:
+        # Dynamically construct the module name
+        module_name = f"{path}.{bot_file}"
+        # Import the module
+        module = importlib.import_module(module_name)
+        # Get the run_bot function from the module
+        return getattr(module, "run_bot")
+    except (ImportError, AttributeError) as e:
+        raise ImportError(f"Failed to import run_bot from {module_name}: {e}")
+
+
+async def create_room_and_token() -> tuple[str, str]:
+    """Create a Daily room and generate an authentication token.
+
+    This function checks for existing room URL and token in the environment variables.
+    If not found, it creates a new room using the Daily API and generates a token for it.
+
+    Returns:
+        tuple[str, str]: A tuple containing the room URL and the authentication token.
+
+    Raises:
+        HTTPException: If room creation or token generation fails.
+    """
+    from pipecat.transports.services.helpers.daily_rest import DailyRoomParams
+
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
+    token = os.getenv("DAILY_SAMPLE_ROOM_TOKEN", None)
+    if not room_url:
+        room = await daily_helpers["rest"].create_room(DailyRoomParams())
+        if not room.url:
+            raise HTTPException(status_code=500, detail="Failed to create room")
+        room_url = room.url
+
+        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.function(image=bot_image, min_containers=1)
+async def bot_runner(room_url, token, bot_name: BotName = "openai"):
+    """Launch the provided bot process, providing the given room URL and token for the bot to join.
+
+    Args:
+        room_url (str): The URL of the Daily room where the bot and client will communicate.
+        token (str): The authentication token for the room.
+        bot_name (BotName): The name of the bot implementation to use. Defaults to "openai".
+
+    Raises:
+        HTTPException: If the bot pipeline fails to start.
+    """
+    try:
+        path = "src"
+        bot_file = get_bot_file(bot_name)
+        run_bot = get_runner(path, bot_file)
+
+        print(f"Starting bot process: {bot_file} -u {room_url} -t {token}")
+        await run_bot(room_url, token)
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to start bot pipeline: {e}")
+
+
+@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
+    """
+    from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
+
+    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()
+
+
+class ConnectData(BaseModel):
+    """Data provided by client to specify the bot pipeline.
+
+    Attributes:
+        bot_name (BotName): The name of the bot to connect to. Defaults to "openai".
+    """
+
+    bot_name: BotName = "openai"
+
+
+async def start(data: ConnectData):
+    """Internal method to start a bot agent and return the room URL and token.
+
+    Args:
+        data (ConnectData): The data containing the bot name to use.
+
+    Returns:
+        tuple[str, str]: A tuple containing the room URL and token.
+    """
+    room_url, token = await create_room_and_token()
+    launch_bot_func = modal.Function.from_name("pipecat-modal", "bot_runner")
+    function_id = launch_bot_func.spawn(room_url, token, data.bot_name)
+    bot_jobs[function_id] = (function_id, room_url)
+
+    return room_url, token
+
+
+@router.get("/")
+async def start_agent():
+    """A user endpoint for launching a bot agent and redirecting to the created room URL.
+
+    This function retrieves the bot implementation from the environment,
+    starts the bot agent, and redirects the user to the room URL to
+    interact with the bot through a Daily Prebuilt Interface.
+
+    Returns:
+        RedirectResponse: A response that redirects to the room URL.
+    """
+    bot_name = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    print(f"Starting bot: {bot_name}")
+    room_url, token = await start(ConnectData(bot_name=bot_name))
+
+    return RedirectResponse(room_url)
+
+
+@router.post("/connect")
+async def rtvi_connect(data: ConnectData) -> Dict[Any, Any]:
+    """A user endpoint for launching a bot agent and retrieving the room/token credentials.
+
+    This function retrieves the bot implementation from the request, if provided,
+    starts the bot agent, and returns the room URL and token for the bot. This allows the
+    client to then connect to the bot using their own RTVI interface.
+
+    Args:
+        data (ConnectData): Optional. The data containing the bot name to use.
+
+    Returns:
+        Dict[Any, Any]: A dictionary containing the room URL and token.
+    """
+    print(f"Starting bot: {data.bot_name}")
+    if data is None or not data.bot_name:
+        data.bot_name = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    room_url, token = await start(data)
+
+    return {"room_url": room_url, "token": token}
+
+
+@router.get("/status/{fid}")
+def get_status(fid: str):
+    """Retrieve the status of a bot process by its function ID.
+
+    Args:
+        fid (str): The function ID of the bot process.
+
+    Returns:
+        JSONResponse: A JSON response containing the bot's status and result code.
+
+    Raises:
+        HTTPException: If the bot process with the given ID is not found.
+    """
+    func = modal.FunctionCall.from_id(fid)
+    if not func:
+        raise HTTPException(status_code=404, detail=f"Bot with process id: {fid} not found")
+
+    try:
+        result = func.get(timeout=0)
+        return JSONResponse({"bot_id": fid, "status": "finished", "code": result})
+    except modal.exception.OutputExpiredError:
+        return JSONResponse({"bot_id": fid, "status": "finished", "code": 404})
+    except TimeoutError:
+        return JSONResponse({"bot_id": fid, "status": "running", "code": 202})
+
+
+@app.function(image=web_image, min_containers=1)
+@modal.concurrent(max_inputs=1)
+@modal.asgi_app()
+def fastapi_app():
+    """Create and configure the FastAPI application.
+
+    This function initializes the FastAPI app with middleware, routes, and lifespan management.
+    It is decorated to be used as a Modal ASGI app.
+    """
+    from fastapi.middleware.cors import CORSMiddleware
+
+    # Initialize FastAPI app
+    web_app = FastAPI(lifespan=lifespan)
+
+    web_app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["*"],
+        allow_credentials=True,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    # Include the endpoints from endpoints.py
+    web_app.include_router(router)
+
+    return web_app

examples/deployment/modal-example/server/env.example

@@ -0,0 +1,14 @@
+DAILY_API_KEY=
+
+# determines which bot file to default to: 'openai', 'gemini', or 'vllm'
+BOT_IMPLEMENTATION=openai
+
+# needed for the openai bot pipeline
+OPENAI_API_KEY=
+ELEVENLABS_API_KEY=
+
+# needed for the gemini live bot pipeline
+GOOGLE_API_KEY=
+
+# needed if you modified the API Key for your self-hosted LLM
+VLLM_API_KEY=

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

@@ -0,0 +1,2 @@
+python-dotenv==1.0.1
+modal==0.71.3

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

@@ -0,0 +1,198 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""Gemini Bot Implementation.
+
+This module implements a chatbot using Google's Gemini Multimodal Live model.
+It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Speech-to-speech model
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow using Gemini's streaming capabilities.
+"""
+
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+from PIL import Image
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+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, RTVIObserver, RTVIProcessor
+from pipecat.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+try:
+    logger.remove(0)
+    logger.add(sys.stderr, level="DEBUG")
+except ValueError:
+    # Handle the case where logger is already initialized
+    pass
+
+sprites = []
+script_dir = os.path.dirname(__file__)
+
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def run_bot(room_url: str, token: str):
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport with specific audio parameters
+    - Gemini Live multimodal model integration
+    - Voice activity detection
+    - Animation processing
+    - RTVI event handling
+    """
+    # Set up Daily transport with specific audio/video parameters for Gemini
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            audio_out_enabled=True,
+            camera_out_enabled=True,
+            camera_out_width=1024,
+            camera_out_height=576,
+            vad_enabled=True,
+            vad_audio_passthrough=True,
+            vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
+        ),
+    )
+
+    # Initialize the Gemini Multimodal Live model
+    llm = GeminiMultimodalLiveLLMService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        voice_id="Puck",  # Aoede, Charon, Fenrir, Kore, Puck
+        transcribe_user_audio=True,
+    )
+
+    messages = [
+        {
+            "role": "user",
+            "content": "You are Chatbot, a friendly, helpful robot. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by introducing yourself.",
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    ta = TalkingAnimation()
+
+    #
+    # RTVI events for Pipecat client UI
+    #
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            context_aggregator.user(),
+            llm,
+            ta,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+    await task.queue_frame(quiet_frame)
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        await rtvi.set_bot_ready()
+        # Kick off the conversation
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant):
+        await transport.capture_participant_transcription(participant["id"])
+
+    @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)

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

@@ -0,0 +1,226 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""OpenAI Bot Implementation.
+
+This module implements a chatbot using OpenAI's GPT-4 model for natural language
+processing. It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Text-to-speech using ElevenLabs
+- Support for both English and Spanish
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow.
+"""
+
+import os
+import sys
+
+from dotenv import load_dotenv
+from loguru import logger
+from PIL import Image
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+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, RTVIObserver, RTVIProcessor
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+try:
+    logger.remove(0)
+    logger.add(sys.stderr, level="DEBUG")
+except ValueError:
+    # Handle the case where logger is already initialized
+    pass
+
+sprites = []
+script_dir = os.path.dirname(__file__)
+
+# Load sequential animation frames
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def run_bot(room_url: str, token: str):
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport
+    - Speech-to-text and text-to-speech services
+    - Language model integration
+    - Animation processing
+    - RTVI event handling
+    """
+    # Set up Daily transport with video/audio parameters
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            audio_out_enabled=True,
+            camera_out_enabled=True,
+            camera_out_width=1024,
+            camera_out_height=576,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            transcription_enabled=True,
+            #
+            # Spanish
+            #
+            # transcription_settings=DailyTranscriptionSettings(
+            #     language="es",
+            #     tier="nova",
+            #     model="2-general"
+            # )
+        ),
+    )
+
+    # Initialize text-to-speech service
+    tts = ElevenLabsTTSService(
+        api_key=os.getenv("ELEVENLABS_API_KEY"),
+        #
+        # English
+        #
+        voice_id="SAz9YHcvj6GT2YYXdXww",
+        #
+        # Spanish
+        #
+        # model="eleven_multilingual_v2",
+        # voice_id="gD1IexrzCvsXPHUuT0s3",
+    )
+
+    # Initialize LLM service
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            #
+            # English
+            #
+            "content": "You are an incessant one-upper. Start by asking the user how their day is going.",
+            #
+            # Spanish
+            #
+            # "content": "Eres Chatbot, un amigable y útil robot. Tu objetivo es demostrar tus capacidades de una manera breve. Tus respuestas se convertiran a audio así que nunca no debes incluir caracteres especiales. Contesta a lo que el usuario pregunte de una manera creativa, útil y breve. Empieza por presentarte a ti mismo.",
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    ta = TalkingAnimation()
+
+    #
+    # RTVI events for Pipecat client UI
+    #
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            context_aggregator.user(),
+            llm,
+            tts,
+            ta,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+    await task.queue_frame(quiet_frame)
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        await rtvi.set_bot_ready()
+        # Kick off the conversation
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant):
+        await transport.capture_participant_transcription(participant["id"])
+
+    @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)

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

@@ -0,0 +1,239 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""OpenAI Bot Implementation.
+
+This module implements a chatbot using OpenAI's GPT-4 model for natural language
+processing. It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Text-to-speech using ElevenLabs
+- Support for both English and Spanish
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow.
+"""
+
+import os
+import sys
+from typing import List
+
+from dotenv import load_dotenv
+from loguru import logger
+from openai.types.chat import ChatCompletionMessageParam
+from PIL import Image
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    Frame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+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, RTVIObserver, RTVIProcessor
+from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+try:
+    logger.remove(0)
+    logger.add(sys.stderr, level="DEBUG")
+except ValueError:
+    # Handle the case where logger is already initialized
+    pass
+
+# REPLACE WITH YOUR MODAL URL ENDPOINT
+modal_url = "https://<Modal workspace>--example-vllm-openai-compatible-serve.modal.run"
+api_key = os.getenv("VLLM_API_KEY", "super-secret-key")
+
+
+sprites = []
+script_dir = os.path.dirname(__file__)
+
+# Load sequential animation frames
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def run_bot(room_url: str, token: str):
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport
+    - Speech-to-text and text-to-speech services
+    - Language model integration
+    - Animation processing
+    - RTVI event handling
+    """
+    # Set up Daily transport with video/audio parameters
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            audio_out_enabled=True,
+            camera_out_enabled=True,
+            camera_out_width=1024,
+            camera_out_height=576,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            transcription_enabled=True,
+            #
+            # Spanish
+            #
+            # transcription_settings=DailyTranscriptionSettings(
+            #     language="es",
+            #     tier="nova",
+            #     model="2-general"
+            # )
+        ),
+    )
+
+    # Initialize text-to-speech service
+    tts = ElevenLabsTTSService(
+        api_key=os.getenv("ELEVENLABS_API_KEY"),
+        #
+        # English
+        #
+        voice_id="D38z5RcWu1voky8WS1ja",
+        #
+        # Spanish
+        #
+        # model="eleven_multilingual_v2",
+        # voice_id="gD1IexrzCvsXPHUuT0s3",
+    )
+
+    # Initialize LLM service
+    llm = OpenAILLMService(
+        # To use OpenAI
+        api_key=api_key,
+        # Or, to use a local vLLM (or similar) api server
+        model="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w4a16",
+        base_url=f"{modal_url}/v1",
+    )
+
+    messages = [
+        {
+            "role": "system",
+            #
+            # English
+            #
+            "content": "You are a salesman for Modal, the cloud-native serverless Python computing platform.",
+            #
+            # Spanish
+            #
+            # "content": "Eres Chatbot, un amigable y útil robot. Tu objetivo es demostrar tus capacidades de una manera breve. Tus respuestas se convertiran a audio así que nunca no debes incluir caracteres especiales. Contesta a lo que el usuario pregunte de una manera creativa, útil y breve. Empieza por presentarte a ti mismo.",
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    ta = TalkingAnimation()
+
+    #
+    # RTVI events for Pipecat client UI
+    #
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            context_aggregator.user(),
+            llm,
+            tts,
+            ta,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+    await task.queue_frame(quiet_frame)
+
+    @rtvi.event_handler("on_client_ready")
+    async def on_client_ready(rtvi):
+        await rtvi.set_bot_ready()
+        # Kick off the conversation
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_first_participant_joined")
+    async def on_first_participant_joined(transport, participant):
+        await transport.capture_participant_transcription(participant["id"])
+
+    @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)

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

@@ -0,0 +1,84 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import asyncio
+import importlib
+import os
+
+
+def get_bot_file(arg_bot: str | None) -> str:
+    bot_implementation = arg_bot or os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    if not bot_implementation:
+        bot_implementation = "openai"
+    if bot_implementation not in ["openai", "gemini", "vllm"]:
+        raise ValueError(
+            f"Invalid BOT_IMPLEMENTATION: {bot_implementation}. Must be 'openai' or 'gemini'"
+        )
+    return f"bot_{bot_implementation}"
+
+
+def get_runner(bot_file: str):
+    """Dynamically import the run_bot function based on the bot name.
+
+    Args:
+        bot_name (str): The name of the bot implementation (e.g., 'openai', 'gemini').
+
+    Returns:
+        function: The run_bot function from the specified bot module.
+
+    Raises:
+        ImportError: If the specified bot module or run_bot function is not found.
+    """
+    try:
+        # Dynamically construct the module name
+        module_name = f"{bot_file}"
+        # Import the module
+        module = importlib.import_module(module_name)
+        # Get the run_bot function from the module
+        return getattr(module, "run_bot")
+    except (ImportError, AttributeError) as e:
+        raise ImportError(f"Failed to import run_bot from {module_name}: {e}")
+
+
+def main():
+    """Parse the args to launch the appropriate bot using the given room/token."""
+    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(
+        "-t",
+        "--token",
+        type=str,
+        required=False,
+        help="Daily room token",
+    )
+    parser.add_argument(
+        "-b",
+        "--bot",
+        type=str,
+        required=False,
+        help="Bot runner to use (e.g., openai, gemini)",
+    )
+
+    args, unknown = parser.parse_known_args()
+
+    url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL")
+    token = args.token or os.getenv("DAILY_SAMPLE_ROOM_TOKEN")
+    bot_file = get_bot_file(args.bot)
+
+    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."
+        )
+
+    run_bot = get_runner(bot_file)
+    asyncio.run(run_bot(url, token))
+
+
+if __name__ == "__main__":
+    main()

examples/deployment/pipecat-cloud-daily-pstn-server/README.md

@@ -100,7 +100,28 @@ phone numbers with valid values for your use case.
 
 ### Dialin Request
 
-The server will receive a request when a call is received from Daily.
+The server will receive a request when a call is received from Daily. 
+The payload that the webhook received is as follows:
+```json
+{
+  // for dial-in from webhook
+  "To": "+14152251493",
+  "From": "+14158483432",
+  "callId": "string-contains-uuid",
+  "callDomain": "string-contains-uuid",
+  "sipHeaders": {
+    "X-My-Custom-Header": "value",
+    "x-caller": "+1234567890",
+    "x-called": "+1987654321", 
+   },
+}
+```
+The `To`, `From`, `callId`, `callDomain` fields are converted to 
+`snake_case` and mapped to `dialin_settings`. In addition, `sipHeader` 
+contains any custom SIP headers received by Daily on the SIP 
+interconnect address (`sip_uri`). These are headers sent from 
+Twilio or other external SIP platforms, for example, to send the 
+caller's phone number.
 
 ### Dialout Request
 
@@ -158,6 +179,7 @@ curl -X POST http://localhost:3000/api/dial \
     "From": "+1987654321",
     "callId": "call-uuid-123",
     "callDomain": "domain-uuid-456",
+    "sipHeader": {},
     "dialout_settings": [
       {
         "phoneNumber": "+1234567890",

examples/deployment/pipecat-cloud-daily-pstn-server/fastapi-webhook-server/server.py

@@ -39,6 +39,11 @@ class RoomRequest(BaseModel):
         None, description="A flag to perform voicemail or answeing-machine detection"
     )
     call_transfer: Optional[Dict[str, Any]] = Field(None, description="to initiate a call transfer")
+    sipHeaders: Optional[Dict[str, Any]] = Field(
+        None,
+        alias="sip_headers",
+        description="Custom SIP headers received from the external SIP provider",
+    )
 
     class Config:
         populate_by_name = True
@@ -57,6 +62,14 @@ class RoomRequest(BaseModel):
     "callDomain": "string-contains-uuid"
     These need to be remapped to dialin_settings
 
+    In addition, we may receive in the body that can be 
+    sent to the bot as a custom field, sip_headers
+    "sipHeaders": {
+        "X-My-Custom-Header": "value",
+        "x-caller": "+14158483432",
+        "x-called": "+14152251493",
+    },
+
     "dialout_settings": [
         {"phoneNumber": "+14158483432", "callerId": "+14152251493"}, 
         {"sipUri": "sip:username@sip.hostname"}
@@ -157,6 +170,7 @@ async def dial(request: RoomRequest, raw_request: Request):
             "dialout_settings": request.dialout_settings,
             "voicemail_detection": request.voicemail_detection,
             "call_transfer": request.call_transfer,
+            "sip_headers": request.sipHeaders,  # passing the SIP headers to the bot
         },
     }
 

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

@@ -65,6 +65,7 @@ export default async function handler(req, res) {
       From,
       callId,
       callDomain,
+      sipHeaders,
       dialout_settings,
       voicemail_detection,
       call_transfer
@@ -117,6 +118,7 @@ export default async function handler(req, res) {
         dialout_settings,
         voicemail_detection,
         call_transfer,
+        sip_headers: sipHeaders,
       },
     };
 

examples/foundational/04c-transports-daily-audio-source.py

@@ -0,0 +1,111 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from daily_runner import configure
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService, Language, LiveOptions
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_in_enabled=True,
+                audio_in_passthrough=False,
+                audio_out_enabled=True,
+                audio_out_sample_rate=16000,
+                transcription_enabled=False,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        stt = DeepgramSTTService(
+            api_key=os.getenv("DEEPGRAM_API_KEY"),
+            live_options=LiveOptions(language=Language.EN),
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                stt,
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_audio(participant["id"])
+            # Kick off the conversation.
+            messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/29-turn-tracking-observer.py

@@ -0,0 +1,119 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.base_transport import TransportParams
+from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
+from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
+
+load_dotenv(override=True)
+
+
+async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
+    logger.info(f"Starting bot")
+
+    transport = SmallWebRTCTransport(
+        webrtc_connection=webrtc_connection,
+        params=TransportParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+        ),
+    )
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+            report_only_initial_ttfb=True,
+        ),
+    )
+
+    turn_observer = task.turn_tracking_observer
+    if turn_observer:
+
+        @turn_observer.event_handler("on_turn_started")
+        async def on_turn_started(observer, turn_number):
+            logger.info(f"🔄 Turn {turn_number} started")
+
+        @turn_observer.event_handler("on_turn_ended")
+        async def on_turn_ended(observer, turn_number, duration, was_interrupted):
+            if was_interrupted:
+                logger.info(f"🔄 Turn {turn_number} interrupted after {duration:.2f}s")
+            else:
+                logger.info(f"🏁 Turn {turn_number} completed in {duration:.2f}s")
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+
+    @transport.event_handler("on_client_closed")
+    async def on_client_closed(transport, client):
+        logger.info(f"Client closed connection")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=False)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from run import main
+
+    main()

examples/foundational/32-gemini-grounding-metadata.py

@@ -11,18 +11,17 @@ from pathlib import Path
 
 from dotenv import load_dotenv
 from loguru import logger
-from openai import audio
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import Frame
+from pipecat.observers.base_observer import BaseObserver, FramePushed
 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.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.google.llm import GoogleLLMService, LLMSearchResponseFrame
+from pipecat.services.llm_service import LLMService
 from pipecat.transports.base_transport import TransportParams
 from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
 from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
@@ -33,7 +32,7 @@ load_dotenv(override=True)
 
 
 # Function handlers for the LLM
-search_tool = {"google_search_retrieval": {}}
+search_tool = {"google_search": {}}
 tools = [search_tool]
 
 system_instruction = """
@@ -50,14 +49,22 @@ Start each interaction by asking the user about which place they would like to k
 """
 
 
-class LLMSearchLoggerProcessor(FrameProcessor):
-    async def process_frame(self, frame: Frame, direction: FrameDirection):
-        await super().process_frame(frame, direction)
+class LLMSearchLoggerObserver(BaseObserver):
+    async def on_push_frame(self, data: FramePushed):
+        src = data.source
+        dst = data.destination
+        frame = data.frame
+        timestamp = data.timestamp
+
+        if not isinstance(src, LLMService) and not isinstance(dst, LLMService):
+            return
+
+        time_sec = timestamp / 1_000_000_000
+
+        arrow = "→"
 
         if isinstance(frame, LLMSearchResponseFrame):
-            print(f"LLMSearchLoggerProcessor: {frame}")
-
-        await self.push_frame(frame)
+            logger.debug(f"🧠 {arrow} {dst} LLM SEARCH RESPONSE FRAME: {frame} at {time_sec:.2f}s")
 
 
 async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
@@ -84,7 +91,6 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
         api_key=os.getenv("GOOGLE_API_KEY"),
         system_instruction=system_instruction,
         tools=tools,
-        model="gemini-1.5-flash-002",
     )
 
     context = OpenAILLMContext(
@@ -97,22 +103,23 @@ async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespac
     )
     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, params=PipelineParams(allow_interruptions=True))
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(allow_interruptions=True),
+        observers=[LLMSearchLoggerObserver()],
+    )
 
     @transport.event_handler("on_client_connected")
     async def on_client_connected(transport, client):

examples/foundational/39-mcp-stdio.py

@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import argparse
 import asyncio
 import io
 import os
@@ -80,7 +81,7 @@ class UrlToImageProcessor(FrameProcessor):
             logger.error(error_msg)
 
 
-async def run_bot(webrtc_connection: SmallWebRTCConnection):
+async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
     logger.info(f"Starting bot")
 
     transport = SmallWebRTCTransport(

examples/foundational/39a-mcp-run-sse.py

@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import argparse
 import os
 import sys
 
@@ -28,7 +29,7 @@ from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
 load_dotenv(override=True)
 
 
-async def run_bot(webrtc_connection: SmallWebRTCConnection):
+async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
     logger.info(f"Starting bot")
 
     transport = SmallWebRTCTransport(

examples/foundational/39b-multiple-mcp.py

@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import argparse
 import asyncio
 import io
 import os
@@ -81,7 +82,7 @@ class UrlToImageProcessor(FrameProcessor):
             logger.error(error_msg)
 
 
-async def run_bot(webrtc_connection: SmallWebRTCConnection):
+async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
     logger.info(f"Starting bot")
 
     transport = SmallWebRTCTransport(

examples/instant-voice/client/javascript/package-lock.json

@@ -16,7 +16,7 @@
         "@types/node": "^22.13.1",
         "@vitejs/plugin-react-swc": "^3.7.2",
         "typescript": "^5.7.3",
-        "vite": "^6.0.2"
+        "vite": "^6.3.5"
       }
     },
     "node_modules/@babel/runtime": {
@@ -1370,9 +1370,9 @@
       }
     },
     "node_modules/vite": {
-      "version": "6.3.3",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.3.tgz",
-      "integrity": "sha512-5nXH+QsELbFKhsEfWLkHrvgRpTdGJzqOZ+utSdmPTvwHmvU6ITTm3xx+mRusihkcI8GeC7lCDyn3kDtiki9scw==",
+      "version": "6.3.5",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.5.tgz",
+      "integrity": "sha512-cZn6NDFE7wdTpINgs++ZJ4N49W2vRp8LCKrn3Ob1kYNtOo21vfDoaV5GzBfLU4MovSAB8uNRm4jgzVQZ+mBzPQ==",
       "dev": true,
       "dependencies": {
         "esbuild": "^0.25.0",

examples/instant-voice/client/javascript/package.json

@@ -15,7 +15,7 @@
     "@types/node": "^22.13.1",
     "@vitejs/plugin-react-swc": "^3.7.2",
     "typescript": "^5.7.3",
-    "vite": "^6.0.2"
+    "vite": "^6.3.5"
   },
   "dependencies": {
     "@pipecat-ai/client-js": "^0.3.5",

examples/news-chatbot/client/javascript/package-lock.json

@@ -13,7 +13,7 @@
         "@pipecat-ai/daily-transport": "^0.3.8"
       },
       "devDependencies": {
-        "vite": "^6.0.9"
+        "vite": "^6.3.5"
       }
     },
     "node_modules/@babel/runtime": {
@@ -1114,9 +1114,9 @@
       }
     },
     "node_modules/vite": {
-      "version": "6.3.3",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.3.tgz",
-      "integrity": "sha512-5nXH+QsELbFKhsEfWLkHrvgRpTdGJzqOZ+utSdmPTvwHmvU6ITTm3xx+mRusihkcI8GeC7lCDyn3kDtiki9scw==",
+      "version": "6.3.5",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.5.tgz",
+      "integrity": "sha512-cZn6NDFE7wdTpINgs++ZJ4N49W2vRp8LCKrn3Ob1kYNtOo21vfDoaV5GzBfLU4MovSAB8uNRm4jgzVQZ+mBzPQ==",
       "dev": true,
       "dependencies": {
         "esbuild": "^0.25.0",

examples/news-chatbot/client/javascript/package.json

@@ -12,7 +12,7 @@
   "license": "ISC",
   "description": "",
   "devDependencies": {
-    "vite": "^6.0.9"
+    "vite": "^6.3.5"
   },
   "dependencies": {
     "@pipecat-ai/client-js": "^0.3.5",

examples/news-chatbot/server/news_bot.py

@@ -102,9 +102,9 @@ async def main():
 
         llm = GoogleLLMService(
             api_key=os.getenv("GOOGLE_API_KEY"),
-            model="gemini-1.5-flash-002",
             system_instruction=system_instruction,
             tools=tools,
+            model="gemini-1.5-flash",
         )
 
         context = OpenAILLMContext(
@@ -153,7 +153,6 @@ async def main():
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):
             logger.debug("First participant joined: {}", participant["id"])
-            await transport.capture_participant_transcription(participant["id"])
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):

examples/open-telemetry-tracing/README.md

@@ -0,0 +1,169 @@
+# OpenTelemetry Tracing for Pipecat
+
+This demo showcases OpenTelemetry tracing integration for Pipecat services, allowing you to visualize service calls, performance metrics, and dependencies in a Jaeger dashboard.
+
+## Features
+
+- **Hierarchical Tracing**: Track entire conversations, turns, and service calls
+- **Service Tracing**: Detailed spans for TTS, STT, and LLM services with rich context
+- **TTFB Metrics**: Capture Time To First Byte metrics for latency analysis
+- **Usage Statistics**: Track character counts for TTS and token usage for LLMs
+- **Flexible Exporters**: Use Jaeger, Zipkin, or any OpenTelemetry-compatible backend
+
+## Trace Structure
+
+Traces are organized hierarchically:
+
+```
+Conversation (conversation-uuid)
+├── turn-1
+│   ├── stt_deepgramsttservice
+│   ├── llm_openaillmservice
+│   └── tts_cartesiattsservice
+└── turn-2
+    ├── stt_deepgramsttservice
+    ├── llm_openaillmservice
+    └── tts_cartesiattsservice
+    turn-N
+    └── ...
+```
+
+This organization helps you track conversation-to-conversation and turn-to-turn.
+
+## Setup Instructions
+
+### 1. Start the Jaeger Container
+
+Run Jaeger in Docker to collect and visualize traces:
+
+```bash
+docker run -d --name jaeger \
+  -e COLLECTOR_ZIPKIN_HOST_PORT=:9411 \
+  -p 16686:16686 \
+  -p 4317:4317 \
+  -p 4318:4318 \
+  jaegertracing/all-in-one:latest
+```
+
+### 2. Environment Configuration
+
+Create a `.env` file with your API keys and enable tracing:
+
+```
+ENABLE_TRACING=true
+OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317  # Point to your preferred backend
+# OTEL_CONSOLE_EXPORT=true  # Set to any value for debug output to console
+
+# Service API keys
+DEEPGRAM_API_KEY=your_key_here
+CARTESIA_API_KEY=your_key_here
+OPENAI_API_KEY=your_key_here
+```
+
+### 3. Configure Your Pipeline Task
+
+Enable tracing in your Pipecat application:
+
+```python
+# Initialize OpenTelemetry with your chosen exporter
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+
+exporter = OTLPSpanExporter(
+    endpoint="http://localhost:4317",  # Jaeger OTLP endpoint
+    insecure=True,
+)
+
+setup_tracing(
+    service_name="pipecat-demo",
+    exporter=exporter,
+    console_export=os.getenv("OTEL_CONSOLE_EXPORT", "false").lower() == "true",
+)
+
+# Enable tracing in your PipelineTask
+task = PipelineTask(
+    pipeline,
+    params=PipelineParams(
+        allow_interruptions=True,
+        enable_metrics=True,  # Required for some service metrics
+    ),
+    enable_tracing=True,  # Enables both turn and conversation tracing
+    conversation_id="customer-123",  # Optional - will auto-generate if not provided
+)
+```
+
+### 4. Exporter Options
+
+While this demo uses Jaeger, you can configure any OpenTelemetry-compatible exporter:
+
+#### Jaeger (Default for the demo)
+
+```python
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+
+exporter = OTLPSpanExporter(
+    endpoint="http://localhost:4317",  # Jaeger OTLP endpoint
+    insecure=True,
+)
+```
+
+#### Cloud Providers
+
+Many cloud providers offer OpenTelemetry-compatible observability services:
+
+- AWS X-Ray
+- Google Cloud Trace
+- Azure Monitor
+- Datadog APM
+
+See the OpenTelemetry documentation for specific exporter configurations:
+https://opentelemetry.io/ecosystem/vendors/
+
+### 5. Install Dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+### 6. Run the Demo
+
+```bash
+python bot.py
+```
+
+### 7. View Traces in Jaeger
+
+Open your browser to [http://localhost:16686](http://localhost:16686) and select the "pipecat-demo" service to view traces.
+
+## Understanding the Traces
+
+- **Conversation Spans**: The top-level span representing an entire conversation
+- **Turn Spans**: Child spans of conversations that represent each turn in the dialog
+- **Service Spans**: Detailed service operations nested under turns
+- **Service Attributes**: Each service includes rich context about its operation:
+  - **TTS**: Voice ID, character count, service type
+  - **STT**: Transcription text, language, model
+  - **LLM**: Messages, tokens used, model, service configuration
+- **Metrics**: Performance data like `metrics.ttfb_ms` and processing durations
+
+## How It Works
+
+The tracing system consists of:
+
+1. **TurnTrackingObserver**: Detects conversation turns
+2. **TurnTraceObserver**: Creates spans for turns and conversations
+3. **Service Decorators**: `@traced_tts`, `@traced_stt`, `@traced_llm` for service-specific tracing
+4. **Context Providers**: Share context between different parts of the pipeline
+
+## Troubleshooting
+
+- **No Traces in Jaeger**: Ensure the Docker container is running and the OTLP endpoint is correct
+- **Debugging Traces**: Set `OTEL_CONSOLE_EXPORT=true` to print traces to the console for debugging
+- **Missing Metrics**: Check that `enable_metrics=True` in PipelineParams
+- **Connection Errors**: Verify network connectivity to the Jaeger container
+- **Exporter Issues**: Try the Console exporter (`OTEL_CONSOLE_EXPORT=true`) to verify tracing works
+- **Other Backends**: If using a different backend, ensure you've configured the correct exporter and endpoint
+
+## References
+
+- [OpenTelemetry Python Documentation](https://opentelemetry-python.readthedocs.io/)
+- [Jaeger Documentation](https://www.jaegertracing.io/docs/latest/)

examples/open-telemetry-tracing/bot.py

@@ -0,0 +1,159 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.llm_service import FunctionCallParams
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.base_transport import TransportParams
+from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
+from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
+from pipecat.utils.tracing.setup import setup_tracing
+
+load_dotenv(override=True)
+
+IS_TRACING_ENABLED = bool(os.getenv("ENABLE_TRACING"))
+
+# Initialize tracing if enabled
+if IS_TRACING_ENABLED:
+    # Create the exporter
+    otlp_exporter = OTLPSpanExporter(
+        endpoint=os.getenv("OTEL_EXPORTER_OTLP_ENDPOINT", "http://localhost:4317"),
+        insecure=True,
+    )
+
+    # Set up tracing with the exporter
+    setup_tracing(
+        service_name="pipecat-demo",
+        exporter=otlp_exporter,
+        console_export=bool(os.getenv("OTEL_CONSOLE_EXPORT")),
+    )
+    logger.info("OpenTelemetry tracing initialized")
+
+
+async def fetch_weather_from_api(params: FunctionCallParams):
+    await params.llm.push_frame(TTSSpeakFrame("Let me check on that."))
+    await params.result_callback({"conditions": "nice", "temperature": "75"})
+
+
+async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
+    logger.info(f"Starting bot")
+
+    transport = SmallWebRTCTransport(
+        webrtc_connection=webrtc_connection,
+        params=TransportParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+        ),
+    )
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(
+        api_key=os.getenv("OPENAI_API_KEY"), params=OpenAILLMService.InputParams(temperature=0.5)
+    )
+
+    # You can also register a function_name of None to get all functions
+    # sent to the same callback with an additional function_name parameter.
+    llm.register_function("get_current_weather", fetch_weather_from_api)
+
+    weather_function = FunctionSchema(
+        name="get_current_weather",
+        description="Get the current weather",
+        properties={
+            "location": {
+                "type": "string",
+                "description": "The city and state, e.g. San Francisco, CA",
+            },
+            "format": {
+                "type": "string",
+                "enum": ["celsius", "fahrenheit"],
+                "description": "The temperature unit to use. Infer this from the user's location.",
+            },
+        },
+        required=["location", "format"],
+    )
+    tools = ToolsSchema(standard_tools=[weather_function])
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages, tools)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            stt,
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            allow_interruptions=True,
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        enable_tracing=IS_TRACING_ENABLED,
+        # Optionally, add a conversation ID to track the conversation
+        # conversation_id="8df26cc1-6db0-4a7a-9930-1e037c8f1fa2",
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+
+    @transport.event_handler("on_client_closed")
+    async def on_client_closed(transport, client):
+        logger.info(f"Client closed connection")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=False)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from run import main
+
+    main()

examples/open-telemetry-tracing/env.example

@@ -0,0 +1,10 @@
+DEEPGRAM_API_KEY=your_deepgram_key
+CARTESIA_API_KEY=your_cartesia_key
+OPENAI_API_KEY=your_openai_key
+
+# Set to any value to enable tracing
+ENABLE_TRACING=true
+# OTLP endpoint (defaults to localhost:4317 if not set)
+OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
+# Set to any value to enable console output for debugging
+# OTEL_CONSOLE_EXPORT=true

examples/open-telemetry-tracing/requirements.txt

@@ -0,0 +1,6 @@
+fastapi
+uvicorn
+python-dotenv
+pipecat-ai[webrtc,silero,cartesia,deepgram,openai,tracing]
+pipecat-ai-small-webrtc-prebuilt
+opentelemetry-exporter-otlp-proto-grpc

examples/open-telemetry-tracing/run.py

@@ -0,0 +1,205 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+import asyncio
+import importlib.util
+import os
+import sys
+from contextlib import asynccontextmanager
+from inspect import iscoroutinefunction, signature
+from typing import Any, Callable, Dict, Optional, Tuple
+
+import uvicorn
+from dotenv import load_dotenv
+from fastapi import BackgroundTasks, FastAPI
+from fastapi.responses import RedirectResponse
+from loguru import logger
+from pipecat_ai_small_webrtc_prebuilt.frontend import SmallWebRTCPrebuiltUI
+
+from pipecat.transports.network.webrtc_connection import IceServer, SmallWebRTCConnection
+
+# Load environment variables
+load_dotenv(override=True)
+
+app = FastAPI()
+
+# Store connections by pc_id
+pcs_map: Dict[str, SmallWebRTCConnection] = {}
+
+ice_servers = [
+    IceServer(
+        urls="stun:stun.l.google.com:19302",
+    )
+]
+
+# Mount the frontend at /
+app.mount("/client", SmallWebRTCPrebuiltUI)
+
+# Store program arguments
+args: argparse.Namespace = argparse.Namespace()
+
+# Store the bot module and function info
+bot_module: Any = None
+run_bot_func: Optional[Callable] = None
+is_webrtc_bot: bool = True
+
+
+def import_bot_file(file_path: str) -> Tuple[Any, Callable, bool]:
+    """Dynamically import the bot file and determine how to run it.
+
+    Returns:
+        tuple: (module, run_function, is_webrtc_bot)
+          - module: The imported module
+          - run_function: Either run_bot or main function
+          - is_webrtc_bot: True if run_bot function exists and accepts a WebRTC connection
+    """
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"Bot file not found: {file_path}")
+
+    # Extract module name without extension
+    module_name = os.path.splitext(os.path.basename(file_path))[0]
+
+    # Load the module
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if not spec or not spec.loader:
+        raise ImportError(f"Could not load spec for {file_path}")
+
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)
+
+    # Check for run_bot function first
+    if hasattr(module, "run_bot"):
+        run_func = module.run_bot
+        # Check if the function accepts a WebRTC connection
+        sig = signature(run_func)
+        is_webrtc = len(sig.parameters) > 0
+        return module, run_func, is_webrtc
+
+    # Fall back to main function
+    if hasattr(module, "main") and iscoroutinefunction(module.main):
+        return module, module.main, False
+
+    raise AttributeError(f"No run_bot or async main function found in {file_path}")
+
+
+@app.get("/", include_in_schema=False)
+async def root_redirect():
+    return RedirectResponse(url="/client/")
+
+
+@app.post("/api/offer")
+async def offer(request: dict, background_tasks: BackgroundTasks):
+    global run_bot_func, is_webrtc_bot
+
+    if not run_bot_func:
+        raise RuntimeError("No bot file has been loaded")
+
+    if not is_webrtc_bot:
+        return {
+            "error": "This bot doesn't support WebRTC connections, it's running in standalone mode"
+        }
+
+    pc_id = request.get("pc_id")
+
+    if pc_id and pc_id in pcs_map:
+        pipecat_connection = pcs_map[pc_id]
+        logger.info(f"Reusing existing connection for pc_id: {pc_id}")
+        await pipecat_connection.renegotiate(
+            sdp=request["sdp"], type=request["type"], restart_pc=request.get("restart_pc", False)
+        )
+    else:
+        pipecat_connection = SmallWebRTCConnection(ice_servers)
+        await pipecat_connection.initialize(sdp=request["sdp"], type=request["type"])
+
+        @pipecat_connection.event_handler("closed")
+        async def handle_disconnected(webrtc_connection: SmallWebRTCConnection):
+            logger.info(f"Discarding peer connection for pc_id: {webrtc_connection.pc_id}")
+            pcs_map.pop(webrtc_connection.pc_id, None)
+
+        # We've already checked that run_bot_func exists
+        assert run_bot_func is not None
+        background_tasks.add_task(run_bot_func, pipecat_connection, args)
+
+    answer = pipecat_connection.get_answer()
+    # Updating the peer connection inside the map
+    pcs_map[answer["pc_id"]] = pipecat_connection
+
+    return answer
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    yield  # Run app
+    coros = [pc.close() for pc in pcs_map.values()]
+    await asyncio.gather(*coros)
+    pcs_map.clear()
+
+
+async def run_standalone_bot() -> None:
+    """Run a standalone bot that doesn't require WebRTC"""
+    global run_bot_func
+    if run_bot_func is not None:
+        await run_bot_func()
+    else:
+        raise RuntimeError("No bot function available to run")
+
+
+def main(parser: Optional[argparse.ArgumentParser] = None):
+    global args
+
+    if not parser:
+        parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
+    parser.add_argument("bot_file", nargs="?", help="Path to the bot file", default=None)
+    parser.add_argument(
+        "--host", default="localhost", help="Host for HTTP server (default: localhost)"
+    )
+    parser.add_argument(
+        "--port", type=int, default=7860, help="Port for HTTP server (default: 7860)"
+    )
+    parser.add_argument("--verbose", "-v", action="count", default=0)
+    args = parser.parse_args()
+
+    logger.remove(0)
+    if args.verbose:
+        logger.add(sys.stderr, level="TRACE")
+    else:
+        logger.add(sys.stderr, level="DEBUG")
+
+    # Infer the bot file from the caller if not provided explicitly
+    bot_file = args.bot_file
+    if bot_file is None:
+        # Get the __file__ of the script that called main()
+        import inspect
+
+        caller_frame = inspect.stack()[1]
+        caller_globals = caller_frame.frame.f_globals
+        bot_file = caller_globals.get("__file__")
+
+    if not bot_file:
+        print("❌ Could not determine the bot file. Pass it explicitly to main().")
+        sys.exit(1)
+
+    # Import the bot file
+    try:
+        global run_bot_func, bot_module, is_webrtc_bot
+        bot_module, run_bot_func, is_webrtc_bot = import_bot_file(bot_file)
+        logger.info(f"Successfully loaded bot from {bot_file}")
+
+        if is_webrtc_bot:
+            logger.info("Detected WebRTC-compatible bot, starting web server...")
+            uvicorn.run(app, host=args.host, port=args.port)
+        else:
+            logger.info("Detected standalone bot, running directly...")
+            asyncio.run(run_standalone_bot())
+    except Exception as e:
+        logger.error(f"Error loading bot file: {e}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

examples/p2p-webrtc/video-transform/client/typescript/package-lock.json

@@ -16,7 +16,7 @@
         "@types/node": "^22.13.1",
         "@vitejs/plugin-react-swc": "^3.7.2",
         "typescript": "^5.7.3",
-        "vite": "^6.0.2"
+        "vite": "^6.3.5"
       }
     },
     "node_modules/@babel/runtime": {
@@ -1371,9 +1371,9 @@
       }
     },
     "node_modules/vite": {
-      "version": "6.3.3",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.3.tgz",
-      "integrity": "sha512-5nXH+QsELbFKhsEfWLkHrvgRpTdGJzqOZ+utSdmPTvwHmvU6ITTm3xx+mRusihkcI8GeC7lCDyn3kDtiki9scw==",
+      "version": "6.3.5",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.5.tgz",
+      "integrity": "sha512-cZn6NDFE7wdTpINgs++ZJ4N49W2vRp8LCKrn3Ob1kYNtOo21vfDoaV5GzBfLU4MovSAB8uNRm4jgzVQZ+mBzPQ==",
       "dev": true,
       "dependencies": {
         "esbuild": "^0.25.0",

examples/p2p-webrtc/video-transform/client/typescript/package.json

@@ -15,7 +15,7 @@
     "@types/node": "^22.13.1",
     "@vitejs/plugin-react-swc": "^3.7.2",
     "typescript": "^5.7.3",
-    "vite": "^6.0.2"
+    "vite": "^6.3.5"
   },
   "dependencies": {
     "@pipecat-ai/client-js": "^0.3.2",

examples/simple-chatbot/client/javascript/package-lock.json

@@ -13,7 +13,7 @@
         "@pipecat-ai/daily-transport": "^0.3.8"
       },
       "devDependencies": {
-        "vite": "^6.0.9"
+        "vite": "^6.3.5"
       }
     },
     "node_modules/@babel/runtime": {
@@ -1114,9 +1114,9 @@
       }
     },
     "node_modules/vite": {
-      "version": "6.3.3",
-      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.3.tgz",
-      "integrity": "sha512-5nXH+QsELbFKhsEfWLkHrvgRpTdGJzqOZ+utSdmPTvwHmvU6ITTm3xx+mRusihkcI8GeC7lCDyn3kDtiki9scw==",
+      "version": "6.3.5",
+      "resolved": "https://registry.npmjs.org/vite/-/vite-6.3.5.tgz",
+      "integrity": "sha512-cZn6NDFE7wdTpINgs++ZJ4N49W2vRp8LCKrn3Ob1kYNtOo21vfDoaV5GzBfLU4MovSAB8uNRm4jgzVQZ+mBzPQ==",
       "dev": true,
       "dependencies": {
         "esbuild": "^0.25.0",

examples/simple-chatbot/client/javascript/package.json

@@ -12,7 +12,7 @@
   "license": "ISC",
   "description": "",
   "devDependencies": {
-    "vite": "^6.0.9"
+    "vite": "^6.3.5"
   },
   "dependencies": {
     "@pipecat-ai/client-js": "^0.3.5",

examples/simple-chatbot/client/react-native/.gitignore

@@ -0,0 +1,5 @@
+ios
+android
+node_modules
+.expo
+.env

examples/simple-chatbot/client/react-native/.nvmrc

@@ -0,0 +1 @@
+22.14

examples/simple-chatbot/client/react-native/App.js

@@ -0,0 +1,21 @@
+// Disabling the logs from react-native-webrtc
+import debug from 'debug';
+debug.disable('rn-webrtc:*');
+
+// Ignoring the warnings from react-native-background-timer while they don't fix this issue:
+// https://github.com/ocetnik/react-native-background-timer/issues/366
+import { LogBox } from 'react-native';
+LogBox.ignoreLogs([
+  "`new NativeEventEmitter()` was called with a non-null argument without the required `addListener` method.",
+  "`new NativeEventEmitter()` was called with a non-null argument without the required `removeListeners` method."
+]);
+
+// Enable debug logs
+/*window.localStorage = window.localStorage || {};
+window.localStorage.debug = '*';
+window.localStorage.getItem = (itemName) => {
+  console.log('Requesting the localStorage item ', itemName);
+  return window.localStorage[itemName];
+};*/
+
+export { default } from './src/App';

examples/simple-chatbot/client/react-native/README.md

@@ -0,0 +1,89 @@
+# React Native implementation
+
+Basic implementation using the [Pipecat RN SDK](https://docs.pipecat.ai/client/react-native/introduction).
+
+## Usage
+
+### Expo requirements
+
+This project cannot be used with an [Expo Go](https://docs.expo.dev/workflow/expo-go/) app because [it requires custom native code](https://docs.expo.io/workflow/customizing/).
+
+When a project requires custom native code or a config plugin, we need to transition from using [Expo Go](https://docs.expo.dev/workflow/expo-go/)
+to a [development build](https://docs.expo.dev/development/introduction/).
+
+More details about the custom native code used by this demo can be found in [rn-daily-js-expo-config-plugin](https://github.com/daily-co/rn-daily-js-expo-config-plugin).
+
+### Building remotely
+
+If you do not have experience with Xcode and Android Studio builds or do not have them installed locally on your computer, you will need to follow [this guide from Expo to use EAS Build](https://docs.expo.dev/development/create-development-builds/#create-and-install-eas-build).
+
+### Building locally
+
+You will need to have installed locally on your computer:
+- [Xcode](https://developer.apple.com/xcode/) to build for iOS;
+- [Android Studio](https://developer.android.com/studio) to build for Android;
+
+#### Install the demo dependencies
+
+```bash
+# Use the version of node specified in .nvmrc
+nvm i
+
+# Install dependencies
+yarn install
+
+# Before a native app can be compiled, the native source code must be generated.
+npx expo prebuild
+```
+
+#### Running on Android
+
+After plugging in an Android device [configured for debugging](https://developer.android.com/studio/debug/dev-options), run the following command:
+
+```
+npm run android
+```
+
+#### Running on iOS
+
+First, you'll need to do a one-time setup. This is required to build to a physical device.
+
+If you're familiar with Xcode, open `ios/RNSimpleChatbot.xcworkspace` and, in the target settings, provide a development team registered with Apple.
+
+If you're newer to Xcode, here are some more detailed instructions to get you started.
+
+First, open the project in Xcode. Make sure to specifically select `RNSimpleChatbot.xcworkspace` from `/ios`. The `/ios` directory will have been generated by running `npx expo prebuild` as instructed above. This is also a good time to plug in your iOS device to be sure the following steps are successful.
+
+From the main menu, select `Settings` and then `Accounts`. Click the `+` sign to add an account (e.g. an Apple ID).
+
+![xcode-accounts.png](./docsAssets/xcode-accounts.png)
+
+Once an account is added, perform the following steps:
+
+ 1. Close `Settings`.
+ 1. Select the folder icon in the top left corner.
+ 1. Select `RNSimpleChatbot` from the side panel
+ 1. Navigate to `Signing & Capabilities` in the top nav bar.
+ 1. Open the "Team" dropdown
+ 1. Select the account added in the previous step.
+
+The "Signing Certificate" section should update accordingly with your account information.
+
+![xcode-signing.png](./docsAssets/xcode-signing.png)
+
+**Troubleshooting common errors:**
+
+- If you see the error `Change your bundle identifier to a unique string to try again`, update the "Bundle Identifier" input in `Signing & Capabilities` to make it unique. This should resolve the error.
+
+- If you see an error that says `Xcode was unable to launch because it has an invalid code signature, inadequate entitlements or its profile has not been explicitly trusted by the user`, you may need to update the settings on your iPhone to enable the required permissions as follows:
+
+1. Open `Settings` on your iPhone
+1. Select `General`, then `Device Management`
+1. Click `Trust` for DailyPlayground
+
+- You may also be prompted to enter you login keychain password. Be sure to click `Always trust` to avoid the prompt showing multiple times.
+
+After, run the following command:
+```
+npm run ios
+```

examples/simple-chatbot/client/react-native/app.json

@@ -0,0 +1,75 @@
+{
+  "expo": {
+    "name": "RN Simple Chatbot",
+    "slug": "simple-chatbot-demo",
+    "newArchEnabled": false,
+    "version": "1.0.0",
+    "orientation": "portrait",
+    "icon": "./assets/images/pipecat.png",
+    "userInterfaceStyle": "light",
+    "splash": {
+      "image": "./assets/images/splash.png",
+      "resizeMode": "contain",
+      "backgroundColor": "#ffffff"
+    },
+    "updates": {
+      "fallbackToCacheTimeout": 0
+    },
+    "assetBundlePatterns": [
+      "**/*"
+    ],
+    "ios": {
+      "supportsTablet": true,
+      "bitcode": false,
+      "bundleIdentifier": "co.daily.SimpleChatbot",
+      "infoPlist": {
+        "UIBackgroundModes": [
+          "voip"
+        ]
+      }
+    },
+    "android": {
+      "adaptiveIcon": {
+        "foregroundImage": "./assets/images/pipecat.png",
+        "backgroundColor": "#FFFFFF"
+      },
+      "package": "co.daily.SimpleChatbot",
+      "permissions": [
+        "android.permission.ACCESS_NETWORK_STATE",
+        "android.permission.BLUETOOTH",
+        "android.permission.CAMERA",
+        "android.permission.INTERNET",
+        "android.permission.MODIFY_AUDIO_SETTINGS",
+        "android.permission.RECORD_AUDIO",
+        "android.permission.SYSTEM_ALERT_WINDOW",
+        "android.permission.WAKE_LOCK",
+        "android.permission.FOREGROUND_SERVICE",
+        "android.permission.FOREGROUND_SERVICE_CAMERA",
+        "android.permission.FOREGROUND_SERVICE_MICROPHONE",
+        "android.permission.FOREGROUND_SERVICE_MEDIA_PROJECTION",
+        "android.permission.POST_NOTIFICATIONS"
+      ]
+    },
+    "web": {
+      "favicon": "./assets/images/pipecat.png"
+    },
+    "plugins": [
+      "@config-plugins/react-native-webrtc",
+      "@daily-co/config-plugin-rn-daily-js",
+      [
+        "expo-build-properties",
+        {
+          "android": {
+            "minSdkVersion": 24,
+            "compileSdkVersion": 35,
+            "targetSdkVersion": 35,
+            "buildToolsVersion": "35.0.0"
+          },
+          "ios": {
+            "deploymentTarget": "15.1"
+          }
+        }
+      ]
+    ]
+  }
+}

examples/simple-chatbot/client/react-native/babel.config.js

@@ -0,0 +1,6 @@
+module.exports = function(api) {
+  api.cache(true);
+  return {
+    presets: ['babel-preset-expo'],
+  };
+};

examples/simple-chatbot/client/react-native/env.example

@@ -0,0 +1 @@
+EXPO_SIMPLE_CHATBOT_SERVER=http://$YOUR_IP:7860

examples/simple-chatbot/client/react-native/metro.config.js

@@ -0,0 +1,2 @@
+const { getDefaultConfig } = require('expo/metro-config');
+module.exports = getDefaultConfig(__dirname);

examples/simple-chatbot/client/react-native/package.json

@@ -0,0 +1,44 @@
+{
+  "name": "simple-chatbot-demo",
+  "version": "1.0.0",
+  "scripts": {
+    "start": "expo start --dev-client",
+    "android": "expo run:android --device",
+    "ios": "expo run:ios --device",
+    "web": "expo start --web",
+    "update": "(cd ../rtvi-client-react-native-daily; yarn build); cp -R ../rtvi-client-react-native-daily/lib/* ./node_modules/react-native-realtime-ai-daily/lib/;"
+  },
+  "dependencies": {
+    "@config-plugins/react-native-webrtc": "^10.0.0",
+    "@daily-co/config-plugin-rn-daily-js": "0.0.7",
+    "@daily-co/react-native-daily-js": "^0.76.0",
+    "@daily-co/react-native-webrtc": "^118.0.3-daily.2",
+    "@react-native-async-storage/async-storage": "1.24.0",
+    "@react-navigation/native": "^7.0.14",
+    "@react-navigation/stack": "^7.1.1",
+    "expo": "^53.0.7",
+    "expo-build-properties": "~0.14.6",
+    "expo-dev-client": "~5.1.8",
+    "expo-splash-screen": "~0.30.8",
+    "expo-status-bar": "~2.2.3",
+    "react": "19.0.0",
+    "react-native": "0.79.2",
+    "react-native-background-timer": "^2.4.1",
+    "react-native-gesture-handler": "^2.25.0",
+    "react-native-get-random-values": "^1.11.0",
+    "@pipecat-ai/react-native-daily-transport": "^0.3.5",
+    "react-native-safe-area-context": "^5.4.0",
+    "react-native-screens": "^4.10.0",
+    "react-native-toast-message": "^2.3.0"
+  },
+  "devDependencies": {
+    "@babel/core": "^7.27.1",
+    "@types/react-native": "^0.73.0",
+    "typescript": "~5.8.3"
+  },
+  "private": true,
+  "resolutions": {
+    "@daily-co/react-native-webrtc/debug": "^4.0.0",
+    "@daily-co/react-native-webrtc/@types/react-native": "^0.73.0"
+  }
+}

examples/simple-chatbot/client/react-native/src/App.tsx

@@ -0,0 +1,34 @@
+import React from "react"
+
+import { NavigationContainer } from '@react-navigation/native';
+import { createStackNavigator } from '@react-navigation/stack';
+import PreJoinView from './views/PreJoinView';
+import MeetingView from './views/MeetingView';
+import { VoiceClientProvider } from './context/VoiceClientContext';
+import Toast from 'react-native-toast-message';
+
+import { useVoiceClientNavigation } from './hooks/useVoiceClientNavigation';
+
+const Stack = createStackNavigator();
+
+const NavigationManager: React.FC = () => {
+  useVoiceClientNavigation();  // This hook now controls the navigation based on the connection state.
+  return null; // This component doesn't render anything but manages navigation.
+};
+
+const App: React.FC = () => {
+  return (
+    <VoiceClientProvider>
+      <NavigationContainer>
+        <Stack.Navigator initialRouteName="Prejoin">
+          <Stack.Screen name="Prejoin" component={PreJoinView} options={{ headerShown: false }}/>
+          <Stack.Screen name="Meeting" component={MeetingView} options={{ headerShown: false }}/>
+        </Stack.Navigator>
+        <NavigationManager />
+        <Toast />
+      </NavigationContainer>
+    </VoiceClientProvider>
+  );
+};
+
+export default App;

examples/simple-chatbot/client/react-native/src/components/MicrophoneView.tsx

@@ -0,0 +1,94 @@
+import React, { useState, useMemo } from 'react';
+import { View, StyleSheet, LayoutChangeEvent, ViewStyle } from 'react-native';
+import { MaterialIcons } from '@expo/vector-icons';
+import Colors from '../theme/Colors';
+import { useVoiceClient } from '../context/VoiceClientContext';
+
+interface MicrophoneViewProps {
+  style?: ViewStyle; // Optional additional styles for the button container
+}
+
+const MicrophoneView: React.FC<MicrophoneViewProps> = ({ style }) => {
+  const { isMicEnabled, localAudioLevel: audioLevel } = useVoiceClient();
+  const [dimensions, setDimensions] = useState({ width: 0, height: 0 });
+
+  const onLayout = (event: LayoutChangeEvent) => {
+    const { width, height } = event.nativeEvent.layout;
+      setDimensions({ width, height });
+  };
+
+  const { width } = dimensions;
+
+  const circleSize = useMemo(() => width * 0.9, [width]);
+  const innerCircleSize = useMemo(() => width * 0.82, [width]);
+  const audioCircleSize = useMemo(() => audioLevel * width * 0.95, [audioLevel, width]);
+
+  return (
+    <View style={[styles.container, style]} onLayout={onLayout}>
+      <View
+        style={[
+          styles.outerCircle,
+          { width: circleSize, height: circleSize, borderRadius: circleSize / 2 },
+        ]}
+      >
+        <View
+          style={[
+            styles.innerCircle,
+            {
+              backgroundColor: !isMicEnabled ? Colors.disabledMic : Colors.backgroundCircle,
+              width: innerCircleSize,
+              height: innerCircleSize,
+              borderRadius: innerCircleSize / 2,
+            },
+          ]}
+        />
+
+        {isMicEnabled && (
+          <View
+            style={[
+              styles.audioCircle,
+              {
+                width: audioCircleSize,
+                height: audioCircleSize,
+                borderRadius: audioCircleSize / 2,
+              },
+            ]}
+          />
+        )}
+
+        <MaterialIcons
+          name={!isMicEnabled ? "mic-off" : "mic"}
+          size={width * 0.2}
+          color="white"
+          style={styles.micIcon}
+        />
+      </View>
+    </View>
+  );
+};
+
+const styles = StyleSheet.create({
+  container: {
+    justifyContent: 'center',
+    alignItems: 'center',
+  } as ViewStyle,
+  outerCircle: {
+    borderWidth: 1,
+    borderColor: Colors.buttonsBorder,
+    justifyContent: 'center',
+    alignItems: 'center',
+  } as ViewStyle,
+  innerCircle: {
+    position: 'absolute',
+  } as ViewStyle,
+  audioCircle: {
+    position: 'absolute',
+    backgroundColor: Colors.micVolume,
+    opacity: 0.5,
+  } as ViewStyle,
+  micIcon: {
+    position: 'absolute',
+  },
+});
+
+export default MicrophoneView;

examples/simple-chatbot/client/react-native/src/components/WaveformView.tsx

@@ -0,0 +1,128 @@
+import React, { useEffect, useState } from 'react';
+import { LayoutChangeEvent, StyleSheet, Text, View, ViewStyle } from 'react-native';
+import { MaterialIcons } from '@expo/vector-icons';
+import Colors from '../theme/Colors';
+import { useVoiceClient } from '../context/VoiceClientContext';
+
+const dotCount = 5;
+
+const WaveformView: React.FC = () => {
+  const [audioLevels, setAudioLevels] = useState(Array(dotCount).fill(0));
+  const [dimensions, setDimensions] = useState({ width: 0, height: 0 });
+
+  const { currentState: voiceClientStatus, botReady: isBotReady, remoteAudioLevel: audioLevel } = useVoiceClient();
+
+  const onLayout = (event: LayoutChangeEvent) => {
+    const { width, height } = event.nativeEvent.layout;
+    setDimensions({ width, height });
+  };
+
+  useEffect(() => {
+    setAudioLevels((prevLevels) => [...prevLevels.slice(1), audioLevel]);
+  }, [audioLevel]);
+
+  const { width, height } = dimensions;
+  const circleSize = width * 0.9;
+  const innerCircleSize = width * 0.82;
+  const barWidth = (width * 0.5) / dotCount;
+
+  return (
+    <View style={styles.container} onLayout={onLayout}>
+      <View style={[styles.outerCircle, { width: circleSize, height: circleSize, borderRadius: circleSize / 2 }]}>
+        <View
+          style={[
+            styles.innerCircle,
+            {
+              backgroundColor: isBotReady ? Colors.backgroundCircle : Colors.backgroundCircleNotConnected,
+              width: innerCircleSize,
+              height: innerCircleSize,
+              borderRadius: innerCircleSize / 2,
+            },
+          ]}
+        >
+          {isBotReady ? (
+            audioLevel > 0 ? (
+              <View style={[styles.waveformContainer, { width: width * 0.5, height: width * 0.5 }]}>
+                {audioLevels.map((level, index) => (
+                  <View
+                    key={index}
+                    style={[
+                      styles.waveformBar,
+                      {
+                        width: barWidth - 10, // Subtract some margin
+                        height: level * height,
+                      },
+                    ]}
+                  />
+                ))}
+              </View>
+            ) : (
+              <View style={[styles.dotContainer, { width: width * 0.5, height: height * 0.5 }]}>
+                {Array(dotCount)
+                  .fill(0)
+                  .map((_, index) => (
+                    <View key={index} style={[styles.dot, { width: height * 0.1, height: height * 0.1 }]} />
+                  ))}
+              </View>
+            )
+          ) : (
+            <View style={styles.notReadyContainer}>
+              <MaterialIcons name="hourglass-empty" size={32} color="white" />
+              <Text style={styles.voiceClientStatusText}>{voiceClientStatus}</Text>
+            </View>
+          )}
+        </View>
+      </View>
+    </View>
+  );
+};
+
+const styles = StyleSheet.create({
+  container: {
+    justifyContent: 'center',
+    alignItems: 'center',
+    width: "100%",
+  } as ViewStyle,
+  outerCircle: {
+    borderWidth: 1,
+    borderColor: 'gray',
+    justifyContent: 'center',
+    alignItems: 'center',
+  } as ViewStyle,
+  innerCircle: {
+    justifyContent: 'center',
+    alignItems: 'center',
+    position: 'relative',
+  } as ViewStyle,
+  waveformContainer: {
+    flexDirection: 'row',
+    justifyContent: 'space-between',
+    alignItems: 'center',
+  } as ViewStyle,
+  waveformBar: {
+    backgroundColor: 'white',
+    maxHeight: '100%',
+    borderRadius: 12,
+  } as ViewStyle,
+  dotContainer: {
+    flexDirection: 'row',
+    justifyContent: 'space-between',
+    alignItems: 'center',
+  } as ViewStyle,
+  dot: {
+    backgroundColor: 'white',
+    borderRadius: 50,
+  } as ViewStyle,
+  notReadyContainer: {
+    justifyContent: 'center',
+    alignItems: 'center',
+  } as ViewStyle,
+  voiceClientStatusText: {
+    color: 'white',
+    marginTop: 10,
+    fontSize: 16,
+    fontWeight: 'bold',
+  } as ViewStyle,
+});
+
+export default WaveformView;

examples/simple-chatbot/client/react-native/src/context/VoiceClientContext.tsx

@@ -0,0 +1,229 @@
+import React, { createContext, useState, useContext, ReactNode, useCallback, useMemo, useRef, useEffect } from 'react'
+import Toast from 'react-native-toast-message'
+import { RNDailyTransport } from '@pipecat-ai/react-native-daily-transport'
+import { RTVIClient, TransportState, RTVIMessage, Participant } from '@pipecat-ai/client-js'
+import { MediaStreamTrack } from '@daily-co/react-native-webrtc'
+import { SettingsManager } from '../settings/SettingsManager';
+
+interface VoiceClientContextProps {
+  voiceClient: RTVIClient | null
+  inCall: boolean
+  currentState: string
+  botReady: boolean
+  localAudioLevel: number
+  remoteAudioLevel: number
+  isMicEnabled: boolean
+  isCamEnabled: boolean
+  videoTrack?: MediaStreamTrack
+  timerCountDown: number
+  // methods
+  start: (url: string) => Promise<void>
+  leave: () => void
+  toggleMicInput: () => void
+  toggleCamInput: () => void
+}
+
+export const VoiceClientContext = createContext<VoiceClientContextProps | undefined>(undefined)
+
+interface VoiceClientProviderProps {
+  children: ReactNode
+}
+
+export const VoiceClientProvider: React.FC<VoiceClientProviderProps> = ({ children }) => {
+  const [voiceClient, setVoiceClient] = useState<RTVIClient | null>(null)
+  const [inCall, setInCall] = useState<boolean>(false)
+  const [currentState, setCurrentState] = useState<TransportState>("disconnected")
+  const [botReady, setBotReady] = useState<boolean>(false)
+  const [isMicEnabled, setIsMicEnabled] = useState<boolean>(false)
+  const [isCamEnabled, setIsCamEnabled] = useState<boolean>(false)
+  const [videoTrack, setVideoTrack] = useState<MediaStreamTrack>()
+  const [localAudioLevel, setLocalAudioLevel] = useState<number>(0)
+  const [remoteAudioLevel, setRemoteAudioLevel] = useState<number>(0)
+  const [timerCountDown, setTimerCountDown] = useState<number>(0)
+
+  const botSpeakingRef = useRef(false)
+  let meetingTimer: NodeJS.Timeout | null
+
+  const createVoiceClient = useCallback((url: string): RTVIClient => {
+    return new RTVIClient({
+      transport: new RNDailyTransport(),
+      params: {
+        baseUrl: url,
+        endpoints: {
+          connect: "/connect"
+        }
+      },
+      enableMic: true,
+      enableCam: false
+    })
+  }, [])
+
+  const handleError = useCallback((error: any) => {
+    console.log("Error occurred:", error)
+    const errorMessage = error.message || error.data?.error || "An unexpected error occurred"
+    Toast.show({
+      type: 'error',
+      text1: errorMessage,
+    })
+  }, [])
+
+  const setupListeners = useCallback((voiceClient: RTVIClient): void => {
+    const inCallStates = new Set(["authenticating", "connecting", "connected", "ready"])
+
+    voiceClient
+      .on("transportStateChanged", (state: TransportState) => {
+        setCurrentState(voiceClient.state)
+        setInCall(inCallStates.has(state))
+      })
+      .on("error", (error: RTVIMessage) => {
+        handleError(error)
+      })
+      .on("botReady", () => {
+        setBotReady(true)
+        let expirationTime = voiceClient.transportExpiry
+        if (expirationTime) {
+          startTimer(expirationTime)
+        }
+      })
+      .on("disconnected", () => {
+        setBotReady(false)
+        stopTimer()
+        setIsMicEnabled(false)
+        setIsCamEnabled(false)
+      })
+      .on("localAudioLevel", (level: number) => {
+          setLocalAudioLevel(level)
+      })
+      .on("remoteAudioLevel", (level: number) => {
+        if (botSpeakingRef.current) {
+          setRemoteAudioLevel(level)
+        }
+      })
+      .on("userStartedSpeaking", () => {
+        // nothing to do here
+      })
+      .on("userStoppedSpeaking", () => {
+        // nothing to do here
+      })
+      .on("botStartedSpeaking", () => {
+        botSpeakingRef.current = true
+      })
+      .on("botStoppedSpeaking", () => {
+        botSpeakingRef.current = false
+        setRemoteAudioLevel(0)
+      })
+      .on("connected", () => {
+        setIsMicEnabled(voiceClient.isMicEnabled)
+        setIsCamEnabled(voiceClient.isCamEnabled)
+      })
+      .on("trackStarted", (track: MediaStreamTrack, p?: Participant) => {
+        if (p?.local && track.kind === 'video'){
+          setVideoTrack(track)
+        }
+      })
+  }, [handleError])
+
+  const start = useCallback(async (url: string): Promise<void> => {
+    const client = createVoiceClient(url)
+    setVoiceClient(client)
+    setupListeners(client)
+    try {
+      await client.connect()
+      // updating the preferences
+      const newSettings = await SettingsManager.getSettings();
+      newSettings.backendURL = url
+      await SettingsManager.updateSettings(newSettings)
+    } catch (error) {
+      handleError(error)
+    }
+  }, [createVoiceClient, setupListeners, handleError])
+
+  const leave = useCallback(async (): Promise<void> => {
+    if (voiceClient) {
+      await voiceClient.disconnect()
+      setVoiceClient(null)
+    }
+  }, [voiceClient])
+
+  const toggleMicInput = useCallback(async (): Promise<void> => {
+    if (voiceClient) {
+      try {
+        let enableMic = !isMicEnabled
+        voiceClient.enableMic(enableMic)
+        setIsMicEnabled(enableMic)
+      } catch (e) {
+        handleError(e)
+      }
+    }
+  }, [voiceClient, isMicEnabled])
+
+  const toggleCamInput = useCallback(async (): Promise<void> => {
+    if (voiceClient) {
+      try {
+        let enableCam = !isCamEnabled
+        voiceClient.enableCam(enableCam)
+        setIsCamEnabled(enableCam)
+      } catch (e) {
+        handleError(e)
+      }
+    }
+  }, [voiceClient, isCamEnabled])
+
+  const startTimer = (expirationTime: number): void => {
+    const currentTime = Math.floor(Date.now() / 1000)
+    const leftTime = expirationTime - currentTime
+    setTimerCountDown(leftTime)
+    meetingTimer = setInterval(() => {
+      setTimerCountDown((prevCountDown) => {
+        return prevCountDown - 1
+      })
+    }, 1000)
+  }
+
+  const stopTimer = (): void => {
+      if (meetingTimer) {
+      clearInterval(meetingTimer)
+      meetingTimer = null
+    }
+    setTimerCountDown(0)
+  }
+
+  useEffect(() => {
+    return () => {
+      if (voiceClient) {
+        voiceClient.removeAllListeners() // Cleanup on unmount
+      }
+    }
+  }, [voiceClient])
+
+  const contextValue = useMemo(() => ({
+    voiceClient,
+    inCall,
+    currentState,
+    botReady,
+    isMicEnabled,
+    isCamEnabled,
+    localAudioLevel,
+    remoteAudioLevel,
+    videoTrack,
+    timerCountDown,
+    start,
+    leave,
+    toggleMicInput,
+    toggleCamInput
+  }), [voiceClient, inCall, currentState, botReady, isMicEnabled, isCamEnabled, localAudioLevel, remoteAudioLevel, videoTrack, timerCountDown, start, leave, toggleMicInput, toggleCamInput])
+
+  return (
+    <VoiceClientContext.Provider value={contextValue}>
+      {children}
+    </VoiceClientContext.Provider>
+  )
+}
+
+export const useVoiceClient = (): VoiceClientContextProps => {
+  const context = useContext(VoiceClientContext)
+  if (!context) {
+    throw new Error('useVoiceClient must be used within a VoiceClientProvider')
+  }
+  return context
+}

examples/simple-chatbot/client/react-native/src/hooks/useVoiceClientNavigation.ts

@@ -0,0 +1,22 @@
+import { useEffect } from 'react';
+import { useNavigation, NavigationProp } from '@react-navigation/native';
+import { useVoiceClient } from '../context/VoiceClientContext';
+
+export type RootStackParamList = {
+  Meeting: undefined;
+  Prejoin: undefined;
+};
+
+export const useVoiceClientNavigation = () => {
+  const navigation = useNavigation<NavigationProp<RootStackParamList>>();
+  const { inCall } = useVoiceClient();
+
+  useEffect(() => {
+    if (inCall) {
+      navigation.navigate('Meeting');
+    } else {
+      navigation.navigate('Prejoin');
+    }
+  }, [inCall, navigation]);
+
+};

examples/simple-chatbot/client/react-native/src/settings/SettingsManager.ts

@@ -0,0 +1,42 @@
+import AsyncStorage from '@react-native-async-storage/async-storage';
+
+export interface SettingsManager {
+  enableCam: boolean;
+  enableMic: boolean;
+  backendURL: string;
+}
+
+// Define the settings object
+const defaultSettings: SettingsManager = {
+  enableCam: false,
+  enableMic: true,
+  backendURL: process.env.EXPO_SIMPLE_CHATBOT_SERVER || "",
+};
+
+export class SettingsManager {
+  private static preferencesKey = 'settingsPreference';
+
+  static async getSettings(): Promise<SettingsManager> {
+    try {
+      const data = await AsyncStorage.getItem(this.preferencesKey);
+      if (data !== null) {
+        return JSON.parse(data) as SettingsManager;
+      } else {
+        return defaultSettings;
+      }
+    } catch (error) {
+      console.error("Failed to load settings:", error);
+      return defaultSettings;
+    }
+  }
+
+  static async updateSettings(settings: SettingsManager): Promise<void> {
+    try {
+      const data = JSON.stringify(settings);
+      await AsyncStorage.setItem(this.preferencesKey, data);
+    } catch (error) {
+      console.error("Failed to save settings:", error);
+    }
+  }
+}
+

examples/simple-chatbot/client/react-native/src/theme/Assets.ts

@@ -0,0 +1,7 @@
+export const Images = {
+  dailyBot: require('../../assets/images/pipecat.png'),
+};
+
+export const Icons = {
+  vision: require('../../assets/icons/vision.png'),
+};

examples/simple-chatbot/client/react-native/src/theme/Colors.ts

@@ -0,0 +1,27 @@
+type ColorsType = {
+  white: string;
+  black: string;
+  backgroundCircle: string;
+  backgroundCircleNotConnected: string;
+  backgroundApp: string;
+  buttonsBorder: string;
+  micVolume: string;
+  timer: string;
+  disabledMic: string;
+  disabledVision: string;
+};
+
+const Colors: ColorsType = {
+  white: '#ffffff',
+  black: '#000000',
+  backgroundCircle: '#374151',
+  backgroundCircleNotConnected: '#D1D5DB',
+  backgroundApp: '#F9FAFB',
+  buttonsBorder: '#E5E7EB',
+  micVolume: '#86EFAC',
+  timer: '#E5E7EB',
+  disabledMic: '#ee6b6e',
+  disabledVision: '#BBF7D0',
+};
+
+export default Colors;

examples/simple-chatbot/client/react-native/src/theme/CustomButton.tsx

@@ -0,0 +1,62 @@
+import React from 'react';
+import { TouchableOpacity, Text, StyleSheet, ViewStyle, TextStyle, GestureResponderEvent } from 'react-native';
+import { MaterialIcons } from '@expo/vector-icons';
+
+interface CustomButtonProps {
+  title: string;
+  onPress: (event: GestureResponderEvent) => void;
+  backgroundColor?: string; // Optional prop for background color
+  textColor?: string; // Optional prop for text color
+  style?: ViewStyle; // Optional additional styles for the button container
+  textStyle?: TextStyle; // Optional additional styles for the text
+  iconName?: string; // Optional prop for the icon name from MaterialIcons
+  iconPosition?: 'left' | 'right'; // Optional prop to control icon position
+  iconSize?: number; // Optional prop for icon size
+  iconColor?: string; // Optional prop for icon color
+}
+
+const CustomButton: React.FC<CustomButtonProps> = ({
+  title,
+  onPress,
+  backgroundColor = 'black',
+  textColor = 'white',
+  style,
+  textStyle,
+  iconName,
+  iconPosition = 'left',
+  iconSize = 24,
+  iconColor = 'white',
+}) => {
+  return (
+    <TouchableOpacity
+      onPress={onPress}
+      style={[styles.button, { backgroundColor }, style]}>
+      {iconName && iconPosition === 'left' && (
+        <MaterialIcons name={iconName as keyof typeof MaterialIcons.glyphMap} size={iconSize} color={iconColor} style={styles.icon} />
+      )}
+      <Text style={[styles.text, { color: textColor }, textStyle]}>{title}</Text>
+      {iconName && iconPosition === 'right' && (
+        <MaterialIcons name={iconName as keyof typeof MaterialIcons.glyphMap} size={iconSize} color={iconColor} style={styles.icon} />
+      )}
+    </TouchableOpacity>
+  );
+};
+
+const styles = StyleSheet.create({
+  button: {
+    padding: 12,
+    borderRadius: 8,
+    alignItems: 'center',
+    justifyContent: 'center',
+    flexDirection: 'row', // Ensures icon and text are aligned in a row
+  },
+  text: {
+    fontSize: 16,
+    fontWeight: 'bold',
+  },
+  icon: {
+    marginHorizontal: 5, // Adds space between the icon and text
+  },
+});
+
+export default CustomButton;

examples/simple-chatbot/client/react-native/src/views/MeetingView.tsx

@@ -0,0 +1,139 @@
+import {
+  View,
+  StyleSheet,
+  Text,
+  Image,
+  TouchableOpacity,
+} from 'react-native';
+
+import React from "react"
+
+import { useVoiceClient } from '../context/VoiceClientContext';
+
+import { Images } from '../theme/Assets';
+import { MaterialIcons } from '@expo/vector-icons';
+
+import WaveformView from '../components/WaveformView';
+import MicrophoneView from '../components/MicrophoneView';
+import { SafeAreaView } from 'react-native-safe-area-context';
+import Colors from '../theme/Colors';
+import CustomButton from '../theme/CustomButton';
+
+const MeetingView: React.FC = () => {
+
+  const { leave, toggleMicInput, toggleCamInput, timerCountDown } = useVoiceClient();
+
+  const timerString = (count: number): string => {
+    const hours = Math.floor(count / 3600);
+    const minutes = Math.floor((count % 3600) / 60);
+    const seconds = count % 60;
+    return `${String(hours).padStart(2, '0')}:${String(minutes).padStart(2, '0')}:${String(seconds).padStart(2, '0')}`;
+  };
+
+  return (
+    <SafeAreaView style={styles.safeArea}>
+      <View style={styles.container}>
+        <View style={styles.header}>
+          <Image source={Images.dailyBot} style={styles.botImage} />
+          <View style={styles.timerContainer}>
+            <MaterialIcons name="timelapse" size={24} color="black" />
+            <Text style={styles.timerText}>{timerString(timerCountDown)}</Text>
+          </View>
+        </View>
+
+        <View style={styles.mainPanel}>
+          <WaveformView/>
+          <View style={styles.bottomControls}>
+            <TouchableOpacity onPress={toggleMicInput}>
+              <MicrophoneView
+                style={styles.microphone}
+              />
+            </TouchableOpacity>
+          </View>
+        </View>
+
+        {/* Bottom Panel */}
+        <View style={styles.bottomPanel}>
+          <CustomButton
+            title="End"
+            iconName={"exit-to-app"}
+            onPress={leave}
+            backgroundColor={Colors.black}
+          />
+        </View>
+      </View>
+    </SafeAreaView>
+  );
+};
+
+const styles = StyleSheet.create({
+  safeArea: {
+    flex: 1,
+    width: "100%",
+    backgroundColor: Colors.backgroundApp,
+  },
+  container: {
+    flex: 1,
+    padding: 20,
+  },
+  header: {
+    flexDirection: 'row',
+    alignItems: 'center',
+    justifyContent: 'space-between',
+    paddingBottom: 10,
+  },
+  botImage: {
+    width: 48,
+    height: 48,
+  },
+  timerContainer: {
+    flexDirection: 'row',
+    alignItems: 'center',
+    backgroundColor: Colors.timer,
+    padding: 10,
+    borderRadius: 12,
+  },
+  timerText: {
+    color: 'black',
+    fontWeight: '500',
+    fontSize: 18,
+    marginLeft: 5,
+  },
+  mainPanel: {
+    flex: 1,
+    justifyContent: 'center',
+    alignItems: 'center',
+  },
+  bottomControls: {
+    flexDirection: 'row',
+    justifyContent: 'center',
+    alignItems: 'center',
+    width: '100%',
+    paddingBottom: 20,
+  },
+  microphone: {
+    width: 160,
+    height: 160,
+  },
+  camera: {
+    width: 120,
+    height: 120,
+  },
+  bottomPanel: {
+    paddingVertical: 10,
+  },
+  endButton: {
+    flexDirection: 'row',
+    alignItems: 'center',
+    justifyContent: 'center',
+    backgroundColor: 'black',
+    borderRadius: 12,
+    padding: 10,
+  },
+  endText: {
+    marginLeft: 5,
+    color: 'white',
+  },
+});
+
+export default MeetingView;

examples/simple-chatbot/client/react-native/src/views/PreJoinView.tsx

@@ -0,0 +1,82 @@
+import {
+  View,
+  StyleSheet,
+  Text,
+  TextInput,
+  Image
+} from "react-native"
+
+import React, { useEffect, useState } from 'react';
+
+import { useVoiceClient } from '../context/VoiceClientContext';
+
+import Colors from '../theme/Colors';
+import { Images } from '../theme/Assets';
+import CustomButton from '../theme/CustomButton';
+import { SettingsManager } from '../settings/SettingsManager';
+
+const styles = StyleSheet.create({
+  container: {
+    flex: 1,
+    padding: 20,
+    backgroundColor: Colors.backgroundApp,
+    justifyContent: 'center',
+    alignItems: 'center',
+  },
+  image: {
+    width: 64,
+    height: 64,
+    marginBottom: 20,
+  },
+  header: {
+    fontSize: 18,
+    fontWeight: 'bold',
+    marginBottom: 20,
+  },
+  textInput: {
+    width: '100%',
+    padding: 10,
+    borderColor: Colors.buttonsBorder,
+    backgroundColor: Colors.white,
+    borderWidth: 1,
+    borderRadius: 5,
+    marginBottom: 10,
+  },
+  lastTextInput: {
+    marginBottom: 20,
+  },
+});
+
+const PreJoinView: React.FC = () => {
+  const { start } = useVoiceClient();
+
+  const [backendURL, setBackendURL] = useState<string>('')
+
+  useEffect(() => {
+    const loadSettings = async () => {
+      const loadedSettings = await SettingsManager.getSettings();
+      setBackendURL(loadedSettings.backendURL)
+    };
+    loadSettings();
+  }, []);
+
+  return (
+    <View style={styles.container}>
+      <Image source={Images.dailyBot} style={styles.image} />
+      <Text style={styles.header}>Connect to Pipecat.</Text>
+      <TextInput
+        placeholder="Server URL"
+        value={backendURL}
+        onChangeText={setBackendURL}
+        style={[styles.textInput, styles.lastTextInput]}
+      />
+      <CustomButton
+        title="Connect"
+        onPress={() => start(backendURL)}
+        backgroundColor={Colors.backgroundCircle}
+      />
+    </View>
+  )
+};
+
+export default PreJoinView;