wehub-resource-sync
87 lines
3.7 KiB
Markdown
87 lines
3.7 KiB
Markdown
# Realtime Twilio Integration
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This example demonstrates how to connect the OpenAI Realtime API to a phone call using Twilio's Media Streams. The server handles incoming phone calls and streams audio between Twilio and the OpenAI Realtime API, enabling real-time voice conversations with an AI agent over the phone.
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## Prerequisites
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- Python 3.10+
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- OpenAI API key with [Realtime API](https://platform.openai.com/docs/guides/realtime) access
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- [Twilio](https://www.twilio.com/docs/voice) account with a phone number
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- A tunneling service like [ngrok](https://ngrok.com/) to expose your local server
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## Setup
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1. **Start the server:**
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```bash
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uv run server.py
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```
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The server will start on port 8000 by default.
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2. **Expose the server publicly, e.g. via ngrok:**
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```bash
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ngrok http 8000
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```
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Note the public URL (e.g., `https://abc123.ngrok.io`)
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3. **Configure your Twilio phone number:**
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- Log into your Twilio Console
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- Select your phone number
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- Set the webhook URL for incoming calls to: `https://your-ngrok-url.ngrok.io/incoming-call`
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- Set the HTTP method to POST
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## Usage
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1. Call your Twilio phone number
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2. You'll hear: "Hello! You're now connected to an AI assistant. You can start talking!"
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3. Start speaking - the AI will respond in real-time
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4. The assistant has access to tools like weather information and current time
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## How It Works
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1. **Incoming Call**: When someone calls your Twilio number, Twilio makes a request to `/incoming-call`
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2. **TwiML Response**: The server returns TwiML that:
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- Plays a greeting message
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- Connects the call to a WebSocket stream at `/media-stream`
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3. **WebSocket Connection**: Twilio establishes a WebSocket connection for bidirectional audio streaming
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4. **Transport Layer**: The `TwilioRealtimeTransportLayer` class owns the WebSocket message handling:
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- Takes ownership of the Twilio WebSocket after initial handshake
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- Runs its own message loop to process all Twilio messages
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- Handles protocol differences between Twilio and OpenAI
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- Automatically sets G.711 μ-law audio format for Twilio compatibility
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- Manages audio chunk tracking for interruption support
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- Wraps the OpenAI realtime model instead of subclassing it
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5. **Audio Processing**:
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- Audio from the caller is base64 decoded and sent to OpenAI Realtime API
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- Audio responses from OpenAI are base64 encoded and sent back to Twilio
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- Twilio plays the audio to the caller
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## Configuration
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- **Port**: Set `PORT` environment variable (default: 8000)
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- **OpenAI API Key**: Set `OPENAI_API_KEY` environment variable
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- **Agent Instructions**: Modify the `RealtimeAgent` configuration in `server.py`
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- **Tools**: Add or modify function tools in `server.py`
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## Troubleshooting
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- **WebSocket connection issues**: Ensure your ngrok URL is correct and publicly accessible
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- **Audio quality**: Twilio streams audio in mulaw format at 8kHz, which may affect quality
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- **Latency**: Network latency between Twilio, your server, and OpenAI affects response time
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- **Logs**: Check the console output for detailed connection and error logs
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## Architecture
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```
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Phone Call → Twilio → WebSocket → TwilioRealtimeTransportLayer → OpenAI Realtime API
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↓
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RealtimeAgent with Tools
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↓
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Audio Response → Twilio → Phone Call
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```
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The `TwilioRealtimeTransportLayer` acts as a bridge between Twilio's Media Streams and OpenAI's Realtime API, handling the protocol differences and audio format conversions. It wraps the OpenAI realtime model to provide a clean interface for Twilio integration.
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