SearXNG is a privacy-respecting metasearch engine that aggregates results from over 100 search engines (Google, Bing, DuckDuckGo, Wikipedia, academic sources, etc.) via HTTP requests. It runs as a Flask web application, supports multiple output formats (HTML, JSON, RSS), and includes a plugin system, bot detection, rate limiting, and user preferences stored in cookies. The architecture is a monolithic Python application with a separate TypeScript/Less frontend built with Vite. It uses Valkey/Redis for caching and rate limiting, and SQLite for persistent caches. The codebase is well-structured with a clear separation of concerns: engine modules implement a common request/response interface, result types are typed with msgspec, and plugins are registered via a simple hook system. It is actively maintained with CI/CD, Docker support, and comprehensive documentation.
The Obsidian Web Clipper is a browser extension that enables users to clip web content and save it as markdown notes in their Obsidian vault. It features a modular architecture with background scripts, content scripts, popup UI, and settings pages, plus a CLI component. The extension provides highlighting, reader mode, template-based formatting with variables and filters, AI-powered content processing, and cross-browser support for Chrome, Firefox, and Safari. Data flows from user interaction through the popup UI to content scripts that extract and process webpage data, which is then formatted via a template engine and saved to Obsidian. The system relies on webextension-polyfill for cross-browser compatibility, defuddle for content extraction, and various UI libraries for functionality.
Local Deep Research is a self-hosted, privacy-focused AI research assistant that performs deep, agentic research using multiple LLMs and web searches. It provides a full-stack web application (FastAPI + JavaScript), a programmatic API, and a Model Context Protocol (MCP) server. The system ingests user queries, decomposes them, executes parallel searches across web and academic sources (SearXNG, Google, arXiv, PubMed, Semantic Scholar, etc.), fetches and extracts content, evaluates evidence, and synthesizes reports with citations. It features per-user encrypted SQLCipher databases, a settings system with environment variable overrides, a RAG library with FAISS vector store, journal quality scoring, news subscriptions, and extensive security controls (egress policy, SSRF protection, credential scrubbing). The codebase is heavily tested with unit, integration, UI, accessibility, and security tests. It is a hybrid of a web application and a research data pipeline, but the dominant character is a production-grade application.
This repository is a comprehensive, curated collection of step-by-step privacy configuration guides for a wide range of software, services, and operating systems (e.g., browsers, messaging apps, social media, Windows, Android, macOS). It is purely documentation—no executable code, APIs, or data pipelines. The content is organized into Markdown files under 'Privacy Settings' and 'Extensions Settings', with a central README serving as an index. The guides are consistently formatted, include notes and tips, and are actively maintained with regular updates reflecting the latest stable versions. While not a software application, it serves as a high-quality reference for users seeking to harden privacy settings across their digital footprint.