Локальные LLM
ramalama
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…
★ 3,1 тыс. звёздMIT
Смотреть руководство →lobehub — проект с открытым исходным кодом из категории «Локальные LLM» от lobehub (lobehub/lobehub на GitHub). У него 82 968 звёзд на GitHub и 15 955 форков, он распространяется по лицензии Custom и последний раз обновлялся на GitHub 3 октября 2026.
🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.
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.
Existing tools plug in by changing one URL.
Ask questions over your PDFs, notes, and codebases.
Pay nothing per token, ever.
Prompts and documents stay on your hardware, always.
RAG, tools, and agents build on the same base.
Smart compression runs big models on modest hardware.
Download the source and move into the project folder.
git clone https://github.com/lobehub/lobehub.git
cd lobehubEvery 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 commandAlso on this shelf: lemonai — Self-evolving general AI agent running fully locally, a Manus-style alternative. Nearby on the same shelf, getspecstory turns your AI coding chats into reusable skills with IDE extensions. Readers working through the Local LLM shelf also stop at opendroid, Autonomous Android agent that sees and taps your phone like a human.
It is an open-source project at lobehub/lobehub with 15,955 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Licensed under Custom — check the repo for commercial-use terms.
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.
A recent 8–32B instruct model is the sweet spot for most machines.
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…
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
Run frontier AI locally.
Sandbox for local AI agents so they only touch what they need.
Self-hosted local llm: turns phones into local ai agent runtimes with on-devic.
Pack and deploy local AI agents designed for your team in minutes.
Другие проекты из категории «Локальные LLM» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если lobehub 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
GPT4All — run local LLMs on any device: a free desktop chat client and Python SDK that run open models entirely on your CPU, no GPU or cloud required
Соседние проекты из категории «Локальные LLM» в каталоге, ближайшие по числу звёзд к lobehub — продолжайте изучать полку по обе стороны от него.
A high-throughput and memory-efficient inference and serving engine for LLMs
GPT4All — run local LLMs on any device: a free desktop chat client and Python SDK that run open models entirely on your CPU, no GPU or cloud required
LLM inference in C/C++
Run and fine-tune LLMs and diffusion models locally — faster training, smaller memory footprint.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
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…
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.