Gpt Home
Open-source AI home assistant using local LLMs on a Raspberry Pi.
A fascinating proof-of-concept for local AI home assistants, but its deprecated status and technical complexity limit its practicality. For those willing to tinker, it offers a blueprint for privacy-first smart home control.
- Privacy-conscious smart home enthusiasts who want a self-hosted AI assistant
- Makers and tinkerers with a Raspberry Pi looking to experiment with local LLMs
- Developers curious about LangGraph-based agent orchestration for home automation
- Hobbyists seeking an open-source foundation to build their own voice assistant
- Users wanting a plug-and-play commercial assistant like Alexa or Google Home
- Non-technical users unfamiliar with Docker, CLI, or Linux
- Those needing ongoing active development or customer support
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In short
Gpt Home — Open-source AI home assistant using local LLMs on a Raspberry Pi. Best for Privacy-conscious smart home enthusiasts who want a self-hosted AI assistant, Makers and tinkerers with a Raspberry Pi looking to experiment with local LLMs, Developers curious about LangGraph-based agent orchestration for home automation. Free to use.
Viability Score
How likely is Gpt Home to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Local LLM inference via LiteLLM
- LangGraph-based agent orchestration
- Raspberry Pi compatibility
- Voice control capability
- Home automation workflows
- Spotify integration (separate container)
- 100% offline, no cloud dependency
- Docker containerized deployment
- Open-source (MIT license)
- Custom agent graph editing with LangGraph
- Supports multiple LLM backends via LiteLLM
- Lightweight enough for Raspberry Pi 4
About Gpt Home
GPT-Home is an open-source, self-hosted AI home assistant designed to run on a Raspberry Pi. It leverages LiteLLM for local LLM inference and LangGraph for agent orchestration, providing a privacy-focused alternative to commercial smart home assistants. The project is now deprecated; development has moved to separate backend, frontend, and Spotify containers. Key features include voice control via local LLMs, custom home automation workflows, Spotify integration (in a separate container), and full Docker containerized deployment. It operates without any cloud dependency, ensuring data stays local. Designed for makers and tinkerers, GPT-Home offers a blueprint for privacy-first smart home control, though it requires comfort with Docker, CLI, and Raspberry Pi setup. Compared to commercial assistants like Alexa or Google Home, GPT-Home sacrifices ease-of-use for complete data sovereignty.
Behind the Verdict
GPT-Home is an intriguing project for anyone who wants to experiment with running a local LLM-powered assistant at home, especially if privacy is a priority. It nails the core concept: voice commands processed entirely on-device via LiteLLM, with LangGraph providing structured agent workflows. The deprecated status is a double-edged sword—you get a stable snapshot, but no ongoing updates or bug fixes. Development has moved to three separate containers (backend, frontend, Spotify), so new users should start there. We'd reach for this only if you're a developer comfortable stitching together Docker containers and debugging CLI errors. For a smarter alternative, consider Rhasspy or Mycroft if you want active open-source communities, or just use Home Assistant with a local voice pipeline—they're more polished and still privacy-respecting. Where it bites: the lack of a frontend in this repo, minimal documentation, and no pre-built integrations beyond Spotify. In practice, you'll likely spend more time configuring than actually using the assistant. Best to treat it as learning material or a foundation to fork.
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Use Cases
- Control lights and smart devices via voice commands using local LLM
- Automate home tasks like reminders and weather queries
- Integrate with Spotify for music playback control
- Experiment with LangGraph-based multi-step agent workflows
- Run a fully offline AI assistant on a Raspberry Pi
Limitations
- The project is deprecated; no further updates are planned.
- Setup requires Docker and familiarity with the command line.
- Limited language support and no official documentation beyond the GitHub repo.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
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