Add README to client-server-web, add phone-bot-twilio files

examples/client-server-web/README.md

@@ -0,0 +1,111 @@
+# Client Server Web Example
+
+Learn how to build web applications using Pipecat's client/server architecture. This approach separates your bot logic from your user interface, giving you full control over the client experience while maintaining real-time voice communication.
+
+This example demonstrates:
+
+- Server-side bot running with Pipecat
+- React client using [Pipecat's client SDK](https://docs.pipecat.ai/client/introduction)
+- Real-time voice communication between client and server
+- UI components from [voice-ui-kit](https://github.com/pipecat-ai/voice-ui-kit) for common voice interface patterns
+
+This is the recommended architecture for web applications that need custom interfaces or client-side functionality.
+
+## Prerequisites
+
+- Python 3.10+
+- `npm` installed
+- AI Service API keys for: [Deepgram](https://console.deepgram.com/signup), [OpenAI](https://auth.openai.com/create-account), and [Cartesia](https://play.cartesia.ai/sign-up)
+
+## Setup
+
+This example requires running both a server and client in **two separate terminal windows**.
+
+### Terminal 1: Server Setup
+
+1. Set up a virtual environment
+
+From the `examples/client-server-web` directory, run:
+
+```bash
+cd server
+python -m venv .venv
+source .venv/bin/activate  # On Windows: .venv\Scripts\activate
+```
+
+> Using `uv`? Create your venv using: `uv venv && source .venv/bin/activate`.
+
+2. Install packages
+
+Then, install the requirements:
+
+```bash
+pip install -r requirements.txt
+```
+
+> Using `uv`? Install requirements using: `uv pip install -r requirements.txt`.
+
+3. Configure environment variables
+
+Create a `.env` file:
+
+```bash
+cp env.example .env
+```
+
+Then, add your API keys:
+
+```
+DEEPGRAM_API_KEY=your_deepgram_api_key
+OPENAI_API_KEY=your_openai_api_key
+CARTESIA_API_KEY=your_cartesia_api_key
+```
+
+4. Run the example
+
+Run your bot using:
+
+```bash
+python bot.py
+```
+
+> Using `uv`? Run your bot using: `uv run bot.py`.
+
+> 💡 First run note: The initial startup may take ~10 seconds as Pipecat downloads required models, like the Silero VAD model.
+
+### Terminal 2: Client Setup
+
+1. Open a new terminal window and navigate to the `client` folder:
+
+From the `examples/client-server-web` directory, run:
+
+```bash
+cd client
+```
+
+2. Install dependencies:
+
+```bash
+npm i
+```
+
+3. Run the client:
+
+```bash
+npm run dev
+```
+
+4. **Open http://localhost:5173 in your browser** and click `Connect` to start talking to your bot.
+
+## Troubleshooting
+
+- **Browser permissions**: Make sure to allow microphone access when prompted by your browser.
+- **Connection issues**: If the WebRTC connection fails, first try a different browser. If that fails, make sure you don't have a VPN or firewall rules blocking traffic. WebRTC uses UDP to communicate.
+- **Audio issues**: Check that your microphone and speakers are working and not muted.
+
+## Next Steps
+
+- **Explore the client SDK**: Learn more about [Pipecat's client SDKs](https://docs.pipecat.ai/client/introduction) for web, mobile, and other platforms
+- **Learn about the voice-ui-kit**: Explore [voice-ui-kit](https://github.com/pipecat-ai/voice-ui-kit) to simplify your front end development
+- **Advanced examples**: Check out [pipecat-examples](https://github.com/pipecat-ai/pipecat-examples) for more complex client/server applications
+- **Join Discord**: Connect with other developers on [Discord](https://discord.gg/pipecat)

examples/client-server-web/server/README.md

@@ -1,90 +0,0 @@
-# Pipecat Quickstart
-
-Run your first Pipecat bot in under 5 minutes. This example creates a voice AI bot that you can talk to in your browser.
-
-## Prerequisites
-
-### Python 3.10+
-
-Pipecat requires Python 3.10 or newer. Check your version:
-
-```bash
-python --version
-```
-
-If you need to upgrade Python, we recommend using a version manager like `uv` or `pyenv`.
-
-### AI Service API keys
-
-Pipecat orchestrates different AI services in a pipeline, ensuring low latency communication. In this quickstart example, we'll use:
-
-- [Deepgram](https://console.deepgram.com/signup) for Speech-to-Text transcriptions
-- [OpenAI](https://auth.openai.com/create-account) for LLM inference
-- [Cartesia](https://play.cartesia.ai/sign-up) for Text-to-Speech audio generation
-
-Have your API keys ready. We'll add them to your `.env` shortly.
-
-## Setup
-
-1. Set up a virtual environment
-
-From the root directory of the `pipecat` repo, run:
-
-```bash
-cd examples/quickstart
-python -m venv .venv
-source .venv/bin/activate  # On Windows: .venv\Scripts\activate
-```
-
-> Using `uv`? Create your venv using: `uv venv && source .venv/bin/activate`.
-
-2. Install packages
-
-Then, install the requirements:
-
-```bash
-pip install -r requirements.txt
-```
-
-> Using `uv`? Install requirements using: `uv pip install -r requirements.txt`.
-
-3. Configure environment variables
-
-Create a `.env` file:
-
-```bash
-cp env.example .env
-```
-
-Then, add your API keys:
-
-```
-DEEPGRAM_API_KEY=your_deepgram_api_key
-OPENAI_API_KEY=your_openai_api_key
-CARTESIA_API_KEY=your_cartesia_api_key
-```
-
-4. Run the example
-
-Run your bot using:
-
-```bash
-python bot.py
-```
-
-> Using `uv`? Run your bot using: `uv run bot.py`.
-
-Connect to your bot in a browser at http://localhost:7860.
-
-> 💡 First run note: The initial startup may take ~10 seconds as Pipecat downloads required models, like the Silero VAD model.
-
-## Troubleshooting
-
-- **Browser permissions**: Make sure to allow microphone access when prompted by your browser.
-- **Connection issues**: If the WebRTC connection fails, first try a different browser. If that fails, make sure you don't have a VPN or firewall rules blocking traffic. WebRTC uses UDP to communicate.
-- **Audio issues**: Check that your microphone and speakers are working and not muted.
-
-## Next Steps
-
-- **Read the docs**: Check out [Pipecat's docs](https://docs.pipecat.ai/) for guides and reference information.
-- **Join Discord**: Join [Pipecat's Discord server](https://discord.gg/pipecat) to get help and learn about what others are building.

examples/phone-bot-twilio/.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+runpod.toml
+
+# Examples
+templates/streams.xml

examples/phone-bot-twilio/README.md

@@ -0,0 +1,115 @@
+# Twilio Chatbot
+
+This project is a FastAPI-based chatbot that integrates with Twilio to handle WebSocket connections and provide real-time communication. The project includes endpoints for starting a call and handling WebSocket connections.
+
+## Table of Contents
+
+- [Features](#features)
+- [Requirements](#requirements)
+- [Installation](#installation)
+- [Configure Twilio URLs](#configure-twilio-urls)
+- [Running the Application](#running-the-application)
+- [Usage](#usage)
+
+## Features
+
+- **FastAPI**: A modern, fast (high-performance), web framework for building APIs with Python 3.6+.
+- **WebSocket Support**: Real-time communication using WebSockets.
+- **CORS Middleware**: Allowing cross-origin requests for testing.
+- **Dockerized**: Easily deployable using Docker.
+
+## Requirements
+
+- Python 3.10
+- Docker (for containerized deployment)
+- ngrok (for tunneling)
+- Twilio Account
+
+## Installation
+
+1. **Set up a virtual environment** (optional but recommended):
+
+   ```sh
+   python -m venv venv
+   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
+   ```
+
+2. **Install dependencies**:
+
+   ```sh
+   pip install -r requirements.txt
+   ```
+
+3. **Create .env**:
+   Copy the example environment file and update with your settings:
+
+   ```sh
+   cp env.example .env
+   ```
+
+4. **Install ngrok**:
+   Follow the instructions on the [ngrok website](https://ngrok.com/download) to download and install ngrok.
+
+## Configure Twilio URLs
+
+1. **Start ngrok**:
+   In a new terminal, start ngrok to tunnel the local server:
+
+   ```sh
+   ngrok http 8765
+   ```
+
+2. **Update the Twilio Webhook**:
+
+   - Go to your Twilio phone number's configuration page
+   - Under "Voice Configuration", in the "A call comes in" section:
+     - Select "Webhook" from the dropdown
+     - Enter your ngrok URL (e.g., http://<ngrok_url>)
+     - Ensure "HTTP POST" is selected
+   - Click Save at the bottom of the page
+
+3. **Configure streams.xml**:
+   - Copy the template file to create your local version:
+     ```sh
+     cp templates/streams.xml.template templates/streams.xml
+     ```
+   - In `templates/streams.xml`, replace `<your server url>` with your ngrok URL (without `https://`)
+   - The final URL should look like: `wss://abc123.ngrok.io/ws`
+
+## Running the Application
+
+Choose one of these two methods to run the application:
+
+### Using Python (Option 1)
+
+**Run the FastAPI application**:
+
+```sh
+# Make sure you’re in the project directory and your virtual environment is activated
+python server.py
+```
+
+### Using Docker (Option 2)
+
+1. **Build the Docker image**:
+
+   ```sh
+   docker build -t twilio-chatbot .
+   ```
+
+2. **Run the Docker container**:
+   ```sh
+   docker run -it --rm -p 8765:8765 twilio-chatbot
+   ```
+
+The server will start on port 8765. Keep this running while you test with Twilio.
+
+## Usage
+
+To start a call, simply make a call to your configured Twilio phone number. The webhook URL will direct the call to your FastAPI application, which will handle it accordingly.
+
+## Testing
+
+It is also possible to test the server without making phone calls by using one of these clients.
+- [python](client/python/README.md): This Python client enables automated testing of the server via WebSocket without the need to make actual phone calls. 
+- [typescript](client/typescript/README.md): This typescript client enables manual testing of the server via WebSocket without the need to make actual phone calls.

examples/phone-bot-twilio/bot.py

@@ -0,0 +1,121 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""Pipecat Twilio Phone Example.
+
+The example runs a simple voice AI bot that you can connect to using a
+phone via Twilio.
+
+Required AI services:
+- Deepgram (Speech-to-Text)
+- OpenAI (LLM)
+- Cartesia (Text-to-Speech)
+
+The example connects between client and server using a Twilio websocket
+connection.
+
+Run the bot using::
+
+    python bot.py -t twilio
+"""
+
+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.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.transports.base_transport import BaseTransport
+from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+
+async def run_bot(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    logger.info(f"Starting bot")
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a friendly AI assistant. Respond naturally and keep your answers conversational.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            rtvi,  # RTVI processor
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Say hello and briefly introduce yourself."})
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.local import main
+
+    # SmallWebRTCTransport for a P2P WebRTC connection
+    transport_params = {
+        "twilio": lambda: FastAPIWebsocketParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+        ),
+    }
+
+    main(run_bot, transport_params=transport_params)

examples/phone-bot-twilio/env.example

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

examples/phone-bot-twilio/requirements.txt

@@ -0,0 +1 @@
+pipecat-ai[cartesia,openai,silero,deepgram,websocket,runner]

examples/phone-bot-twilio/templates/streams.xml.template

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Response>
+  <Connect>
+    <Stream url="wss://<your server url>/ws"></Stream>
+  </Connect>
+  <Pause length="40"/>
+</Response>

examples/quickstart/README.md

@@ -28,10 +28,9 @@ Have your API keys ready. We'll add them to your `.env` shortly.
 
 1. Set up a virtual environment
 
-From the root directory of the `pipecat` repo, run:
+From the `examples/quickstart` directory, run:
 
 ```bash
-cd examples/quickstart
 python -m venv .venv
 source .venv/bin/activate  # On Windows: .venv\Scripts\activate
 ```
@@ -74,7 +73,7 @@ python bot.py
 
 > Using `uv`? Run your bot using: `uv run bot.py`.
 
-Connect to your bot in a browser at http://localhost:7860.
+**Open http://localhost:7860 in your browser** and click `Connect` to start talking to your bot.
 
 > 💡 First run note: The initial startup may take ~10 seconds as Pipecat downloads required models, like the Silero VAD model.