Sioyek is a cross-platform PDF viewer optimized for reading research papers and technical books. Built with Qt, OpenGL, and MuPDF, it provides a rich set of features including multi-threaded rendering, annotation management (highlights, bookmarks, portals, freehand drawings), SyncTeX integration for LaTeX forward/inverse search, fuzzy text search, and a customizable command-driven interface. The architecture follows a modular design with a central MainWidget orchestrating UI state, a Document model for PDF handling, a PdfRenderer for threaded rendering, and a DatabaseManager for persistent annotation storage. The application supports both desktop and touch-optimized interfaces, with platform-specific code for Windows, macOS, Linux, and Android. While primarily an application, Sioyek incorporates data-oriented features such as SQLite-based annotation persistence, checksum-based document identification, and integration with external research tools (Google Scholar, arXiv). The repository also includes scripts for paper downloading, text-to-speech, and embedding annotations, as well as precomputed embedding data files (embedding.npy, linear.npy) likely used for text summarization or search enhancement. The codebase demonstrates strong engineering practices with reusable components like a fuzzy matching library (fzf), a SyncTeX parser, a type-safe configuration system, and a set of QML touch UI widgets. However, it also exhibits some technical debt in the form of global state, large monolithic files (main_widget.h), and platform-specific conditionals scattered throughout.
Qlib is an open-source, AI-oriented quantitative investment platform developed by Microsoft. It covers the full pipeline for quantitative research and trading: data ingestion and feature engineering (Alpha158, Alpha360, high-frequency), model training (traditional ML like LightGBM/XGBoost, deep learning in PyTorch including LSTM, GRU, Transformer, GATs, and reinforcement learning), backtesting with realistic costs and slippage, portfolio optimization, and online serving for production-like deployment. The platform is highly modular and config-driven, with a core library (qlib) and a separate contrib layer for community extensions. It includes a CLI (qrun) for running full workflows from YAML configs, extensive experiment tracking via MLflow, and a rich set of evaluation metrics. While primarily a library/application, it also functions as a research benchmark suite with many example models and data collectors for global markets. The codebase is active and well-maintained, though some components (e.g., TFT model, older RL code) show signs of technical drift due to dependency version locks and deprecated patterns.