LLMRTC Docs

Introduction to LLMRTC Docs

LLMRTC is an open-source TypeScript SDK designed for building real-time voice and vision AI applications. It integrates WebRTC for low-latency audio and video streaming with large language models (LLMs), speech-to-text (STT), and text-to-speech (TTS) capabilities, all through a unified, provider-agnostic API. This allows developers to create seamless, interactive AI experiences without being locked into a specific cloud provider or infrastructure.

The SDK is structured into three main packages: @llmrtc/llmrtc-core for shared functionality, @llmrtc/llmrtc-backend for the Node.js server that handles WebRTC and provider orchestration, and @llmrtc/llmrtc-web-client for browser-based audio/video capture and playback. LLMRTC is ideal for developers looking to build voice assistants, customer support systems, multimodal agents, and on-device AI applications with minimal latency and high flexibility.

Takeaways

• Real-time voice and vision capabilities with sub-second latency
• Provider-agnostic architecture that supports multiple LLMs, STT, and TTS services
• Tool calling and playbooks for multi-stage conversational flows
• Streaming pipeline that improves user experience by starting responses before full generation
• Session resilience with automatic reconnection and history preservation
• Comprehensive observability with hooks and metrics tracking
• Support for both cloud and local providers, enabling flexible deployment options

How LLMRTC Works

LLMRTC operates by combining WebRTC for real-time communication with AI model execution. On the backend, it manages audio and video streams, performs voice activity detection, and orchestrates interactions between different AI providers (e.g., using Claude for LLM, Whisper for STT, and ElevenLabs for TTS). The frontend SDK enables users to interact via voice, with real-time feedback and seamless integration of AI-generated responses.

The core workflow involves:

1. User input (audio or visual) captured by the web client
2. Streaming to the backend server for processing
3. Execution of AI models and tools
4. Generation of output (text or audio) sent back to the user
5. Continuous interaction with hooks for logging, debugging, and custom behavior

Core Benefits and Applications

LLMRTC also provides extensive documentation, including quickstart guides, tutorials, and examples, making it accessible for developers at all levels.