Локальные LLM
node-llama-cpp
Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level
★ 2,2 тыс. звёздMIT
Смотреть руководство →maid — проект с открытым исходным кодом из категории «Локальные LLM» от Mobile-Artificial-Intelligence (Mobile-Artificial-Intelligence/maid на GitHub). У него 2 713 звёзд на GitHub и 296 форков, он распространяется по лицензии MIT и последний раз обновлялся на GitHub 30 сентября 2026.
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…
One binary or app gets you a working local model setup.
Pick a size that fits your RAM/VRAM; smaller models run on laptops.
Use the built-in UI, or point OpenAI-compatible clients at it.
Airplane mode works — your prompts never leave the device.
RAG, tools, and agents build on the same base.
Smart compression runs big models on modest hardware.
Works on planes, in basements, behind firewalls.
Swap between hundreds of open models freely.
Existing tools plug in by changing one URL.
Ask questions over your PDFs, notes, and codebases.
Download the source and move into the project folder.
git clone https://github.com/Mobile-Artificial-Intelligence/maid.git
cd maidEvery 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 commandIt is an open-source project at Mobile-Artificial-Intelligence/maid with 296 forks. Check the repo's contributors and recent commits to see how active maintenance is.
MIT licensed — use it commercially, no strings attached.
Yes — with no network calls, there's nothing to leak.
Close on many tasks now; frontier cloud models still lead on hard reasoning.
8B models run on 16GB RAM; bigger models want a real GPU.
Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level
The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, an…
Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.
Atomic Agent is a local-first AI agent. Runs open-weight models on your own machine via llama.cpp.
⚡ Pure-Rust WebGPU inference engine — OpenAI-API compatible, GGUF native, runs on any GPU. No Python. No llama.cpp. Single binary.
DeepSeek-Coder-V2 — DeepSeek's open code model family that challenged closed-source code models.
Другие проекты из категории «Локальные LLM» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если maid вам не подходит.
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.
Соседние проекты из категории «Локальные LLM» в каталоге, ближайшие по числу звёзд к maid — продолжайте изучать полку по обе стороны от него.
Atomic Agent is a local-first AI agent. Runs open-weight models on your own machine via llama.cpp.
AI e-book reader with semantic search, RAG chat, notes, and text-to-speech.
Official repo for spec & SDK of MCP Apps protocol - standard for UIs embedded AI chatbots, served by MCP servers
Local-first widget tracking token usage and costs across 43+ AI coding tools.
RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in productio…
动手学Ollama，CPU玩转大模型部署，在线阅读地址：https://datawhalechina.github.io/handy-ollama/
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.