Visual intelligence for your home.
Features · ⬇️ Quick Start Guide · Resources · How to report Bugs · ☕ Support
LLM Vision is a Home Assistant integration that uses multimodal large language models to analyze images, videos, live camera feeds, and Frigate events. It can also keep track of analyzed events in a timeline, with an optional Timeline Card for your dashboard.
## Features - Supports OpenRouter, OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure, Groq, [Ollama](https://ollama.com/), [Open WebUI](https://github.com/open-webui/open-webui), [LocalAI](https://github.com/mudler/LocalAI) and any provider with OpenAI compatible endpoints. - Answers questions and provides descriptions of images, video files, live camera feeds, and Frigate events based on your prompt. - Remembers people, pets and objects - Keeps a timeline of camera events, so you can display them on your dashboard or ask Assist about them. - Seamlessly updates sensors based on data extracted from camera streams, images or videos[Learn how to install the blueprint](https://llm-vision.gitbook.io/getting-started/setup/blueprint) ## Resources Check the docs for detailed instructions on how to set up LLM Vision and each of the supported providers, get inspiration from examples or join the discussion on the Home Assistant Community and Discord. For technical questions see the discussions tab. ## How to report a bug or request a feature > [!IMPORTANT] > **Bugs:** If you encounter any bugs and have followed the instructions carefully, file a bug report. Please check open issues first and include debug logs in your report. Debugging can be enabled on the integration's settings page. > **Feature Requests:** If you have an idea for a feature, create a feature request. > > >[KBD]: https://github.com/valentinfrlch/ha-llmvision/issues/new/choose ## Support You can support this project by starring this GitHub repository. If you want, you can also buy me a coffee here:
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