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Merge pull request #109 from pipecat-ai/bot-output
Adding a new example to exemplify the bot-output RTVI event
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‎code-helper/.gitignore‎

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# Byte-compiled / optimized / DLL files
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__pycache__/
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MANIFEST
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client/*.tsbuildinfo

‎code-helper/README.md‎

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# code-helper
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This example demonstrates using `LLMTextProcessor` to categorize the LLM's
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output text so that the client can easily render different types of output
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accordingly, while the TTS speaks these same types in separate but also
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custom ways, spelling out credit card numbers, while skipping trying to
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read out code snippets or not saying the 'https' part of a url.
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This example also includes a text entry box in the client to show how the
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bot handles text input and can respond either with audio or not and the
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categorization and "bot output" continues seemlessly.
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The client in this example will render the user and bot transcripts using
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simply the `user-transcript` and `bot-output` messages. The bot output will
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render each sentence and then highlight each word as it is said. All code
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provided by the bot will be highlighted as such and links will be formatted.
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Concepts this example is meant to demonstrate:
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- Custom handling of LLM text output for different purposes:
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- For the purpose of having the TTS skip certain outputs or speak certain
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outputs differently
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- For the purpose of supporting a client UI for easier rendering of
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different types of text or for altering for filtering out text before
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sending it to the client.
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- Client <-> Bot Communication with RTVI
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- Tool calling for sensitive information and custom handling of that
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information for TTS and RTVI purposes.
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- Client->Server Text input
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## Configuration
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- **Bot Type**: Web
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- **Transport(s)**: SmallWebRTC
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- **Pipeline**: Cascade
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- **STT**: Deepgram
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- **LLM**: OpenAI
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- **TTS**: ElevenLabs
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## Setup
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### Server
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1. **Navigate to server directory**:
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```bash
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cd server
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```
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2. **Install dependencies**:
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```bash
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uv sync
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```
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3. **Configure environment variables**:
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```bash
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cp .env.example .env
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# Edit .env and add your API keys
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```
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4. **Run the bot**:
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- SmallWebRTC: `uv run bot.py`
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### Client
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1. **Navigate to client directory**:
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```bash
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cd client
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```
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2. **Install dependencies**:
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```bash
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npm install
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```
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3. **Run development server**:
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```bash
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npm run dev
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```
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4. **Open browser**:
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http://localhost:5173
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## Project Structure
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```
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code-helper/
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├── server/ # Python bot server
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│ ├── bot.py # Main bot implementation
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│ ├── pyproject.toml # Python dependencies
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│ ├── .env.example # Environment variables template
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│ ├── .env # Your API keys (git-ignored)
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│ └── ...
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├── client/ # Vanilla application
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│ ├── src/ # Client source code
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│ ├── package.json # Node dependencies
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│ └── ...
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├── .gitignore # Git ignore patterns
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└── README.md # This file
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```
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## Observability
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This project includes observability tools to help you debug and monitor your bot:
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## Learn More
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- [Pipecat Documentation](https://docs.pipecat.ai/)
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- [Pipecat GitHub](https://github.com/pipecat-ai/pipecat)
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- [Pipecat Examples](https://github.com/pipecat-ai/pipecat-examples)
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- [Discord Community](https://discord.gg/pipecat)

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