Ollama
The simplest way to run open language models on your own machine.
ReadAny es un proyecto de LLM local de código abierto de codedogQBY (codedogQBY/ReadAny en GitHub). Tiene 2.704 estrellas en GitHub y 217 bifurcaciones, se publica bajo la licencia Custom y se actualizó por última vez en GitHub el 26 de septiembre de 2026.
AI e-book reader with semantic search, RAG chat, notes, and text-to-speech.
Get the app for your platform.
Import EPUBs and other e-book formats.
Ask questions or search semantically.
Keep library and notes synced via WebDAV.
Ask questions answered from your books.
Find passages by meaning, not keywords.
Embeddings stay on your device.
Annotate as you read.
Listen to your books read aloud.
Sync library across devices.
Download the source and move into the project folder.
git clone https://github.com/codedogQBY/ReadAny.git
cd ReadAnyEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandEPUB reading is the focus; check the docs for other formats.
Custom license — read the repo's license file first.
It supports Anthropic and other providers; check for local model options.
Your books are embedded locally and answers are grounded in their text.
Yes, WebDAV sync keeps library and notes consistent.
The simplest way to run open language models on your own machine.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
An open-source RAG-based tool for chatting with your documents.
Private AI chat and model studio that runs in your browser via WebGPU.
A cautious, explainable AI-like text risk analysis tool for local workflows and coding
Strata — one-click Qwen3.8-Flash-Next inference on consumer hardware: chat, code and images, locally, no account, MIT
Los demás proyectos de LLM local con más estrellas del catálogo de LibreAI: la lista realista de alternativas si ReadAny no es lo que buscas.
The simplest way to run open language models on your own machine.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
LLM inference in C/C++
A high-throughput and memory-efficient inference and serving engine for LLMs
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
Proyectos de LLM local cercanos en el catálogo, los más próximos en estrellas a ReadAny: sigue explorando a ambos lados.
Maid is a free and open source application for interfacing with llama.cpp models locally, and with Anthropic, DeepSeek, Ollama, Mistral and OpenAI models rem…
Local-first widget tracking token usage and costs across 43+ AI coding tools.
Atomic Agent is a local-first AI agent. Runs open-weight models on your own machine via llama.cpp.
动手学Ollama,CPU玩转大模型部署,在线阅读地址:https://datawhalechina.github.io/handy-ollama/
Official repo for spec & SDK of MCP Apps protocol - standard for UIs embedded AI chatbots, served by MCP servers
TokenSpeed — a speed-of-light LLM inference engine designed for agentic workloads, with TensorRT-LLM-level performance and vLLM-level usability
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.