7 projects
A wildly popular educational repository that explains software architecture and system design concepts using visual diagrams and plain-language explanations. It covers API/web development, real-world engineering case studies from companies like Netflix and Uber, databases, messaging, and AI/ML fundamentals, aimed at interview prep and general understanding.
Union is a trust-minimized, zero-knowledge interoperability protocol for general message passing, asset transfers, NFTs, and cross-chain communication between blockchains. It is built in Rust without relying on trusted third parties, oracles, or multisigs, instead using consensus verification and ZK proofs.
Scrapling is a Python web scraping framework whose parser can "adaptively" relocate elements when a site's HTML changes, paired with stealth fetchers that bypass anti-bot systems like Cloudflare Turnstile and a Scrapy-style spider engine for concurrent, resumable, proxy-rotating crawls.
A large, curated collection of system design learning resources — real-world company case studies, fundamentals, interview prep, AI engineering notes, and software white papers — organized as a linked index pointing to deep-dive articles and a companion newsletter.
A curated, link-based reading list of the best system design articles, papers, talks, and engineering blogs on the internet, organized by topic — from video processing and distributed file systems to NoSQL internals, caching, consensus, and microservices. It functions as a study companion for interview preparation and learning large-scale architecture.
Chat UI is Hugging Face's open-source SvelteKit web app that provides a polished chat interface for any OpenAI-compatible LLM endpoint. It powers HuggingChat and supports MongoDB-backed history, MCP tool calling, and local heuristic model routing.
Anomalib is a deep-learning library focused on benchmarking, developing, and deploying anomaly detection algorithms, particularly for visual/image-based defect detection. It bundles state-of-the-art unsupervised and few-shot anomaly detection models with training, evaluation, and edge-deployment tooling.