dde0ecb9cd
Voice AI Features: - LiveKit Agents integration for real-time voice calls - Julia AI agent (Python) deployed to LiveKit Cloud - Token server for authentication - Debug screen with voice call testing - Voice call screen with full-screen UI Agent Configuration: - STT: Deepgram Nova-2 - LLM: OpenAI GPT-4o - TTS: Deepgram Aura Asteria (female voice) - Turn Detection: LiveKit Multilingual Model - VAD: Silero - Noise Cancellation: LiveKit BVC Files added: - julia-agent/ - Complete agent code and token server - app/voice-call.tsx - Full-screen voice call UI - services/livekitService.ts - LiveKit client service - contexts/VoiceTranscriptContext.tsx - Transcript state - polyfills/livekit-globals.ts - WebRTC polyfills 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
143 lines
7.1 KiB
Markdown
143 lines
7.1 KiB
Markdown
<a href="https://livekit.io/">
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<img src="./.github/assets/livekit-mark.png" alt="LiveKit logo" width="100" height="100">
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</a>
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# LiveKit Agents Starter - Python
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A complete starter project for building voice AI apps with [LiveKit Agents for Python](https://github.com/livekit/agents) and [LiveKit Cloud](https://cloud.livekit.io/).
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The starter project includes:
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- A simple voice AI assistant, ready for extension and customization
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- A voice AI pipeline with [models](https://docs.livekit.io/agents/models) from OpenAI, Cartesia, and AssemblyAI served through LiveKit Cloud
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- Easily integrate your preferred [LLM](https://docs.livekit.io/agents/models/llm/), [STT](https://docs.livekit.io/agents/models/stt/), and [TTS](https://docs.livekit.io/agents/models/tts/) instead, or swap to a realtime model like the [OpenAI Realtime API](https://docs.livekit.io/agents/models/realtime/openai)
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- Eval suite based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/build/testing/)
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- [LiveKit Turn Detector](https://docs.livekit.io/agents/build/turns/turn-detector/) for contextually-aware speaker detection, with multilingual support
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- [Background voice cancellation](https://docs.livekit.io/home/cloud/noise-cancellation/)
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- Integrated [metrics and logging](https://docs.livekit.io/agents/build/metrics/)
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- A Dockerfile ready for [production deployment](https://docs.livekit.io/agents/ops/deployment/)
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This starter app is compatible with any [custom web/mobile frontend](https://docs.livekit.io/agents/start/frontend/) or [SIP-based telephony](https://docs.livekit.io/agents/start/telephony/).
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## Coding agents and MCP
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This project is designed to work with coding agents like [Cursor](https://www.cursor.com/) and [Claude Code](https://www.anthropic.com/claude-code).
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To get the most out of these tools, install the [LiveKit Docs MCP server](https://docs.livekit.io/mcp).
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For Cursor, use this link:
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[](https://cursor.com/en-US/install-mcp?name=livekit-docs&config=eyJ1cmwiOiJodHRwczovL2RvY3MubGl2ZWtpdC5pby9tY3AifQ%3D%3D)
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For Claude Code, run this command:
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```
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claude mcp add --transport http livekit-docs https://docs.livekit.io/mcp
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```
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For Codex CLI, use this command to install the server:
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```
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codex mcp add --url https://docs.livekit.io/mcp livekit-docs
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```
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For Gemini CLI, use this command to install the server:
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```
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gemini mcp add --transport http livekit-docs https://docs.livekit.io/mcp
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```
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The project includes a complete [AGENTS.md](AGENTS.md) file for these assistants. You can modify this file your needs. To learn more about this file, see [https://agents.md](https://agents.md).
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## Dev Setup
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Clone the repository and install dependencies to a virtual environment:
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```console
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cd agent-starter-python
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uv sync
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```
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Sign up for [LiveKit Cloud](https://cloud.livekit.io/) then set up the environment by copying `.env.example` to `.env.local` and filling in the required keys:
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- `LIVEKIT_URL`
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- `LIVEKIT_API_KEY`
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- `LIVEKIT_API_SECRET`
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You can load the LiveKit environment automatically using the [LiveKit CLI](https://docs.livekit.io/home/cli/cli-setup):
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```bash
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lk cloud auth
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lk app env -w -d .env.local
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```
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## Run the agent
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Before your first run, you must download certain models such as [Silero VAD](https://docs.livekit.io/agents/build/turns/vad/) and the [LiveKit turn detector](https://docs.livekit.io/agents/build/turns/turn-detector/):
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```console
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uv run python src/agent.py download-files
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```
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Next, run this command to speak to your agent directly in your terminal:
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```console
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uv run python src/agent.py console
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```
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To run the agent for use with a frontend or telephony, use the `dev` command:
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```console
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uv run python src/agent.py dev
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```
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In production, use the `start` command:
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```console
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uv run python src/agent.py start
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```
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## Frontend & Telephony
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Get started quickly with our pre-built frontend starter apps, or add telephony support:
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| Platform | Link | Description |
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|----------|----------|-------------|
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| **Web** | [`livekit-examples/agent-starter-react`](https://github.com/livekit-examples/agent-starter-react) | Web voice AI assistant with React & Next.js |
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| **iOS/macOS** | [`livekit-examples/agent-starter-swift`](https://github.com/livekit-examples/agent-starter-swift) | Native iOS, macOS, and visionOS voice AI assistant |
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| **Flutter** | [`livekit-examples/agent-starter-flutter`](https://github.com/livekit-examples/agent-starter-flutter) | Cross-platform voice AI assistant app |
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| **React Native** | [`livekit-examples/voice-assistant-react-native`](https://github.com/livekit-examples/voice-assistant-react-native) | Native mobile app with React Native & Expo |
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| **Android** | [`livekit-examples/agent-starter-android`](https://github.com/livekit-examples/agent-starter-android) | Native Android app with Kotlin & Jetpack Compose |
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| **Web Embed** | [`livekit-examples/agent-starter-embed`](https://github.com/livekit-examples/agent-starter-embed) | Voice AI widget for any website |
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| **Telephony** | [📚 Documentation](https://docs.livekit.io/agents/start/telephony/) | Add inbound or outbound calling to your agent |
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For advanced customization, see the [complete frontend guide](https://docs.livekit.io/agents/start/frontend/).
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## Tests and evals
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This project includes a complete suite of evals, based on the LiveKit Agents [testing & evaluation framework](https://docs.livekit.io/agents/build/testing/). To run them, use `pytest`.
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```console
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uv run pytest
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```
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## Using this template repo for your own project
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Once you've started your own project based on this repo, you should:
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1. **Check in your `uv.lock`**: This file is currently untracked for the template, but you should commit it to your repository for reproducible builds and proper configuration management. (The same applies to `livekit.toml`, if you run your agents in LiveKit Cloud)
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2. **Remove the git tracking test**: Delete the "Check files not tracked in git" step from `.github/workflows/tests.yml` since you'll now want this file to be tracked. These are just there for development purposes in the template repo itself.
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3. **Add your own repository secrets**: You must [add secrets](https://docs.github.com/en/actions/how-tos/writing-workflows/choosing-what-your-workflow-does/using-secrets-in-github-actions) for `LIVEKIT_URL`, `LIVEKIT_API_KEY`, and `LIVEKIT_API_SECRET` so that the tests can run in CI.
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## Deploying to production
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This project is production-ready and includes a working `Dockerfile`. To deploy it to LiveKit Cloud or another environment, see the [deploying to production](https://docs.livekit.io/agents/ops/deployment/) guide.
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## Self-hosted LiveKit
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You can also self-host LiveKit instead of using LiveKit Cloud. See the [self-hosting](https://docs.livekit.io/home/self-hosting/) guide for more information. If you choose to self-host, you'll need to also use [model plugins](https://docs.livekit.io/agents/models/#plugins) instead of LiveKit Inference and will need to remove the [LiveKit Cloud noise cancellation](https://docs.livekit.io/home/cloud/noise-cancellation/) plugin.
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## License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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