Lists (22)
00. ⌨️ Dev Environments ⌨️
Technologies, tools, and configurations I use for my development environment.106 repositories
01. 🦙 Model: LLM 🦙
Repositories for Large Language Models (LLM), frameworks, and datasets.20 repositories
01. 💾 Stack: Backend 💾
Frameworks, libraries, and technologies for building and maintaining backend systems.50 repositories
01. 📡 Stack: DevOps 📡
Tools, platforms, and practices for DevOps, including CI/CD, automation, and infrastructure.64 repositories
01. 🛰️ Stack: MLOps 🛰️
A comprehensive list of tools and platforms for Machine Learning Operations (MLOps).122 repositories
01. 🐍 Stack: Python 🐍
Useful Python modules and libraries that I frequently use.115 repositories
01. 🚄 Stack: XPU 🚄
Libraries, tools, and frameworks for XPU (GPU, TPU, NPU, ...) programming, focusing on CUDA and kernel optimization.46 repositories
02. 🤖 Model: ML 🤖
Repositories for Machine Learning (ML) models, frameworks, and datasets.48 repositories
02. 🧑🏻🔧 Stack: Agent 🧑🏻🔧
Repositories related to AI Agents, including LLM-based autonomous agents and multi-agent systems.77 repositories
03. 🐥 Stack: Frontend 🐥
Frameworks, libraries, and tools for frontend development.22 repositories
98: 🧑🏭 Study: Agent 🧑🏭
A study list of repositories for learning about and experimenting with AI Agents.10 repositories
98. 💿 Study: Backend 💿
Educational resources and projects for learning backend development.27 repositories
98. 🔬 Study: DevOps 🔬
A study guide to DevOps, containing tutorials, guides, and example projects.18 repositories
98. 👶🏻 Study: Frontend 👶🏻
Learning resources for frontend technologies, frameworks, and design patterns.6 repositories
98. 🦾 Study: ML 🦾
Educational materials, tutorials, and projects for studying Machine Learning (ML).20 repositories
98. 🚀 Study: MLOps 🚀
A curated study list for understanding and implementing MLOps pipelines and practices.50 repositories
98. 🚅 Study: XPU 🚅
Resources dedicated to learning XPU (GPU, TPU, NPU, ...) programming, focusing on CUDA and GPU Kernels.18 repositories
99. 🐘 BOAZ 🐘
Projects and materials from my activities at BOAZ, Korea's first inter-university big data club.11 repositories
99. 🔭 Career 🔭
Resources for career development, interview preparation, and job searching.42 repositories
99. 🧗 Conferences 🧗
My speaking engagements, presentations, and materials from conferences.2 repositories
99. 💻 Etc. 💻
Miscellaneous repositories, tools, and interesting projects that don't fit into other categories.48 repositories
99. 📑 GitHub Pages 📑
Tools, themes, and examples for building static sites with GitHub Pages.21 repositories
Starred repositories
mini cli search engine for your docs, knowledge bases, meeting notes, whatever. Tracking current sota approaches while being all local
Early-stage Rust drop-in alternative frontend for vLLM
1 place to call all your agents - OpenCode, Hermes, Claude Managed Agents, Cursor Agents API, DeepAgents.
A collection of DESIGN.md files analysis by popular brand design systems. Drop one into your project and let coding agents generate a matching UI.
Send User Notifications on macOS from the command-line.
OmX - Oh My codeX: Your codex is not alone. Add hooks, agent teams, HUDs, and so much more.
Definition, proposals, and conformance tests for AI Conformance
Use Codex from Claude Code to review code or delegate tasks.
Mount Hugging Face Buckets and repos as local filesystems. No download, no copy, no waiting.
Open, Multi-Cloud, Multi-Cluster Kubernetes Orchestration
Teams-first Multi-agent orchestration for Claude Code
A Claude Code plugin that shows what's happening - context usage, active tools, running agents, and todo progress
Prometheus exporter for Starlette and FastAPI
Fastest enterprise AI gateway (50x faster than LiteLLM) with adaptive load balancer, cluster mode, guardrails, 1000+ models support & <100 µs overhead at 5k RPS.
🏠 Ask Claude about Korean apartment prices — powered by 국토교통부 open API
Browser automation CLI for AI agents
Official inference repo for FLUX.2 models
Collection of step-by-step playbooks for setting up AI/ML workloads on NVIDIA DGX Spark devices with Blackwell architecture.
Curated collection of AI inference engineering resources — LLM serving, GPU kernels, quantization, distributed inference, and production deployment. Compiled from the AER Labs community.
Kernel sources for https://huggingface.co/kernels-community
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
A compact implementation of SGLang, designed to demystify the complexities of modern LLM serving systems.