Beyond Home Automation – LLM on the Edge Makes Your Smart Home Smarter

Imagine what would happen if a large language model and Home Assistant were combined? Yes, we would get a smart home assistant. It’s not just the popular voice chatbot of recent times, but also functions as a smart furniture controller. Here, we’ll discuss how to build your own smart home assistant!

Basic Concepts


Chatbots are automated dialogue systems based on artificial intelligence technology, capable of mimicking human communication methods. They interact with users through text or voice, offering a variety of services such as information retrieval, customer service, and entertainment. These bots can understand and respond to user queries or commands, making the conversation process more natural and efficient.

Home Assistant

Home Assistant is an open-source smart home automation platform. It allows users to connect and control a wide range of smart devices, from lighting and temperature control to security and entertainment systems. It provides highly customizable and automated home management solutions, enhancing the convenience and smartness of home living.

Implementation Process

The diagram above illustrates the hardware and software devices and workflows involved in the entire project. The hardware includes reComputer J4012 and reSpeaker, while the software primarily consists of Riva, Langchain, OpenAI, and Home Assistant.

The main workflow is as follows:

  • After the microphone receives the user’s audio input, the Riva ASR Server converts this input into text format.
  • The Langchain tool calls the OpenAI API to obtain chat content from the large language model.
  • Intelligent furniture control commands are generated based on the chat content and executed using the Home Assistant API.
  • The Riva TTS Server converts the content generated by the large language model into audio signals, which are then output through the speaker.

We have uploaded the relevant code to GitHub. Please refer to the tutorial on GitHub to complete the installation.

Application Example

In the application example, we use the large language model to understand and execute voice commands, controlling the indoor lighting system.

In fact, this project has tremendous potential. It can control not just the lighting, but also all smart devices in the home, thereby creating a more advanced integrated smart home solution. You are just one reComputer away from completing this project.


By integrating large language models with Home Assistant, we can achieve not only home automation but also a more intelligent, interactive, and personalized home assistant experience. As technology continues to advance, the future of smart homes will become increasingly intelligent and human-centric, bringing greater convenience and enjoyment to our lives.

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February 2024