Lokale LLMs
exo
Run frontier AI locally.
★ 47,7 Tsd. SterneApache-2.0
Anleitung ansehen →agent-safehouse ist ein Open-Source-Projekt aus der Kategorie Lokale LLMs von eugene1g (eugene1g/agent-safehouse auf GitHub). Es hat 2.092 Sterne auf GitHub und 99 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 30. September 2026 auf GitHub aktualisiert.
Sandbox for local AI agents so they only touch what they need.
Set it up on your machine.
Choose which paths the agent may access.
Run your coding agent inside the sandbox.
The agent operates within its allowed scope.
Agents see only approved paths.
Scope exactly what agents may touch.
Built for agents running on your machine.
Limits damage from agent errors.
Reduces prompt-injection blast radius.
Works with Claude Code on Mac.
Download the source and move into the project folder.
git clone https://github.com/eugene1g/agent-safehouse.git
cd agent-safehouseEvery 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 commandSimilar idea: isolation, but scoped to what an AI agent may read and write.
Apache 2.0 licensed — commercial use allowed with attribution.
Claude Code on macOS is the headline; check the docs for others.
Sandboxing adds some overhead; check the docs for details.
No sandbox is perfect; treat it as risk reduction, not a guarantee.
Run frontier AI locally.
Hundreds of models & providers. One command to find what runs on your hardware.
Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.
Local-first dashboard of tokens, models, and cost for coding agents.
AI OSINT agent with 20 tools and REPL — for authorized research only.
A local-first context and memory layer for your AI agents.
Die anderen Projekte der Kategorie Lokale LLMs mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls agent-safehouse nicht das Richtige ist.
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.
Verwandte Projekte der Kategorie Lokale LLMs im Katalog, die agent-safehouse bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
Local-first desktop where a commander LLM directs specialist coding agents.
Local API bridge to run Claude and Antigravity inside other coding clients.
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
StepFun's open 196B MoE model that activates 11B parameters per token, built for fast agentic reasoning.
Let any LLM actually watch a video — frames plus transcript, run locally.
One shared local memory hub so every AI agent remembers the same you.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.