Arkon: Enterprise AI Knowledge Hub & MCP Server. Self-hosted knowledge base for teams to manage RAG contexts, access policies, and AI skills. Connect Claude and other LLMs via Model Context Protocol (MCP) for automated, secure organizational knowledge integration.
AgentQL is a suite of tools for connecting your AI to the web. Featuring a query language and Playwright integrations for interacting with elements and extracting data quickly, precisely, and at scale. Includes REST API, Python and JavaScript SDKs, browser debugger.
Key parameters and specifications
Key parameters and specifications
Parameter
Value
Language
Python
Category
AI Engineering
Subcategory
Bring agent to users
Keywords
Home assistant
Stars
1,501
Forks
149
Contributors
42
Created date
2024-05-14
Updated date
2026-10-16
Stars in 1 day
1
Stars in 7 days
11
Rank
5,505
Previous rank
18,684
Rank change
13,179
7-day stars rank
3,824
Previous 7-day stars rank
3,647
7-day stars rank change
-177
Total stars rank
8,089
Previous total stars rank
8,090
Total stars rank change
1
Country
Switzerland
README summary
Visit Website → Features Supports OpenRouter, OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure, Groq, Ollama, Open WebUI, 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
See the website for the latest features and examples. TIP] >LLM Vision is available in the default HACS repository. You can install it directly through HACS or click the button below to open it there. **Search for ** in Home Assistant Settings/Devices & services 4. **Press submit** to continue setup with default settings 5. **Set up the media folder** LLM Vision uses the more secure folder for storing snapshots. If you're running Home Assistant Container, you may need to mount a
folder to in your container settings. **Return to the LLM Vision Integration Page** 7. **Press 'Add Entry'** to add your first AI Provider Detailed setup instructions and documentation is available here: LLM Vision Documentation Blueprint With the easy to use blueprint, you'll get camera event notifications intelligently summarized by AI. LLM Vision can also store events in a timeline, so you can see what happened on your dashboard. Learn how to install the 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. Create new Issue >[KBD]: Support You can support this project by starring this GitHub repository. If you want, you can also buy me a coffee here:
Frequently asked questions
How many stars and forks are recorded?
valentinfrlch/ha-llmvision has 1,501 stars and 149 forks.
What is the repository rank?
valentinfrlch/ha-llmvision is ranked 5,505.
What language and category are recorded?
valentinfrlch/ha-llmvision has 1,501 stars, uses Python and belongs to AI Engineering.
Which repository is closest in rank?
valentinfrlch/ha-llmvision is compared with brave/brave-search-mcp-server, ranked 5,503 with 1,503 stars.
README
Visual intelligence for your home.
[🌟 Features](#features)
·
[⬇️ Quick Start Guide](#quick-start-guide)
·
[📖 Resources](#resources)
·
[🪲 How to report Bugs](#how-to-report-a-bug-or-request-a-feature)
·
[☕ Support](#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, Open WebUI, 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
See the website for the latest features and examples.
Quick Start Guide
[!TIP]
LLM Vision is available in the default HACS repository. You can install it directly through HACS or click the button below to open it there.
Install LLM Vision from HACS
Restart Home Assistant
Search for LLM Vision in Home Assistant Settings/Devices & services
Press submit to continue setup with default settings
Set up the media folder LLM Vision uses the more secure /media folder for storing snapshots. If you're running Home Assistant Container, you may need to mount a folder to /media in your container settings. See the docs for more details.
With the easy to use blueprint, you'll get camera event notifications intelligently summarized by AI. LLM Vision can also store events in a timeline, so you can see what happened on your dashboard.
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.
