RAG・知識ベース
anything-llm
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
★ 66.7k スターMIT
ガイドを見る →argoは、xark-argoが公開しているオープンソースのローカルLLMプロジェクトです（GitHub: xark-argo/argo）。GitHubスターは829、フォークは80で、Customライセンスの下で公開されています。GitHubでの最終更新は2026年1月6日です。
Desktop AI agent platform with one-click models and offline-first RAG.
Get the desktop app or Docker image.
One-click model setup.
Add offline-first RAG sources.
Let the agent think and plan.
No manual model wrangling.
Local knowledge bases for research.
Autonomous thinking and planning.
Nothing leaves your machine.
Integrate hosted models too.
Windows, Mac, and Docker.
Download the source and move into the project folder.
git clone https://github.com/xark-argo/argo.git
cd argoEvery 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 commandThat is its positioning: Manus-style agentic work on your desktop.
Custom license — read the repo's license file first.
Check the docs for the one-click model catalog.
Offline-first design; closed LLM integration is optional.
The last push shown is early 2026; check recent commits.
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
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LibreAIカタログに掲載されたローカルLLMプロジェクトの中で最もスターの多いもの — argoが合わなかった場合に検討したい、現実的な候補リストです。
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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
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カタログの中でargoとスター数が近いローカルLLMプロジェクト — 前後の棚もそのまま見て回れます。
Local security auditor for AI API relays — catches injection and swaps.
Local-first desktop workspace designed for running.
Early proposal and implementation for connecting LLMs to web pages.
Local-first dashboard of tokens, models, and cost for coding agents.
Browse and resume your AI coding-agent sessions on macOS.
Check if your GPU can fine-tune an LLM — memory estimates and LoRA recipes.