srz (Summarize)

srz (Summarize) is a high-performance, modular Rust CLI tool for extracting and synthesizing structured summaries using local OpenAI-compliant LLMs (such as llama.cpp, Ollama, LM Studio, or vLLM) from:

• 🌐 Webpages & articles
• 📚 Books
• 📰 Live news digests & universal RSS/Atom feeds
• 📺 YouTube video transcripts
• 📄 PDF documents & local files
• ⌨️ Unix stdin streams

What Makes srz Different?

Most AI tools require subscriptions and send your private data to cloud servers. srz is built to be simple, fast, and completely private:

• 100% Private — Everything runs directly on your computer. Your files, documents, and reading history never leave your machine.
• One Tool for Any Content — Summarize web articles, YouTube videos, PDFs, books, and news feeds with a single command. Clutter and ads are removed automatically.
• Built-in Offline Search — Your summaries are saved locally so you can easily search and browse your past reading history anytime, even without an internet connection.

Documentation Guide

🧭 Where should I begin?

• Brand new to srz or local LLMs? Start with Installation and the Quick Start to run your first summary in under 2 minutes.
• Looking for specific flags, subcommands, or keybindings? Jump straight to the Command Reference.
• Curious how it works under the hood? Explore Architecture & Design and the deep-dive Rust Learning Guide.

Browse through the chapters:

• Installation: Quick one-line curl/PowerShell scripts, Homebrew tap, Cargo build, precompiled releases, and in-place self-upgrades.
• Quick Start: Connect your local LLM backend (Llama-macOS, Llama-Windows, llama.cpp, Ollama, LM Studio) and run your first summaries.
• Command Reference: In-depth guide covering CLI auto-detection, subcommands, flags, interactive TUI keybindings, and session management.
• Configuration: config.toml structure, named profiles, storage limits, and cache retention policies.
• Architecture & Design: Systems architecture, lifecycle sequence flows, ingestion pipelines, embedded DuckDB schema, BM25 ranking algorithm, performance optimizations, and security model.

Deep-Dive Guides & Audits

• 🦀 Rust Learning Guide: Architectural deep-dive and systems programming concepts using srz as a case study.
• 🛡️ Security Audit: Comprehensive security analysis, memory safety guarantees, and threat mitigations.
• 📋 Changelog: Release history, version highlights, and breaking changes.