llm-eyes tool lets any blind LLM see via tiny local VLM
A GitHub project called llm-eyes bolts a tiny vision-language model (Qwen3.5-0.8B) onto any machine as a local vision service, enabling text-only models like DeepSeek V4 Flash, Qwen, and Llama to caption images, watch webcams, or read video. It runs on Mac (MLX), PC+NVIDIA (llama.cpp), and DGX Spark, and exposes an OpenAI-compatible API.
Entities
Related
LocalEyes gives blind LLMs vision via local Ollama models
LocalEyes is a new tool that enables text-only LLMs like DeepSeek, CodeLlama, and Qwen-Coder to process images locally using an Ollama vision model. It supports screen capture, clipboard reading, and image file analysis without cloud uploads or API keys, offering a private, fast, and free solution for developers using Claude Code.
OpenLive launches as open-source live voice and vision AI assistant
OpenLive is an open-source, on-device voice and vision AI assistant that provides real-time speech and sight capabilities. It serves as an open alternative to proprietary services like ElevenLabs, Gemini Live, and OpenAI Realtime, allowing users to bring their own model.
LLM hardware recipe database with filters and community usage tracking
A community-driven database that lists which LLM models run on which hardware, with performance details. Users can filter by hardware, submit new recipes, and mark which recipes they actively use to show popularity. It solves the problem of finding compatible model-hardware combinations for LLM deployment.
Local-first CLI that masks PII and secrets before sending to LLMs
LocalMask is a command-line tool that runs locally to detect and mask personally identifiable information (PII) and secrets before data is sent to large language models. It solves the privacy and compliance problem for developers and organizations that need to use LLMs without exposing sensitive data.
Interactive app teaching LLM pipeline from pattern matching to transformer training
An interactive web app that walks through every stage of the LLM pipeline, from basic pattern matching to training a transformer from scratch. It includes working code that users can run locally, making it an educational tool for developers and learners.