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

Highlights

💡 What makes srz different? Unlike cloud-dependent AI tools that require subscriptions and upload private reading data, srz runs 100% locally with zero telemetry—pairing instant streaming synthesis and unified multi-format ingestion with embedded offline DuckDB search.

%%{init: {"flowchart": {"minNodeWidth": 210, "minNodeHeight": 54}}}%%
flowchart LR
    subgraph Sources["     Input Sources"]
        S1["🌐 Web & YouTube URLs"]
        S2["📄 PDFs & Documents"]
        S3["📚 Book Synopses"]
        S4["📰 Live News Feeds"]
    end

    subgraph Core["    srz Core (100% Private)"]
        C["⚡ Ingest & Chunking Pipeline\n🔒 100% Local LLM Inference\n📝 Summary Presets & Synthesis"]
    end

    subgraph Highlights["     Key Highlights"]
        H1["⚡ Rich Terminal Paging"]
        H2["💬 Grounded Q&A Chat"]
        H3["🖥️ TUI Dashboard View"]
        H4["📖 Clean Reader Views"]
    end

    S1 --> C
    S2 --> C
    S3 --> C
    S4 --> C

    C --> H1
    C --> H2
    C --> H3
    C --> H4

• 🔒 100% Local & Private: Runs on your device with zero fees and no API keys.
• 🎯 3 Summary Presets: Choose concise, bulleted, or detailed summaries.
• ⚡ Zero-Worry Dynamic Sizing: Automatically probes server context (n_ctx) and concurrency slots to size chunks and eliminate OOM crashes.
• 💬 Interactive Q&A: Chat and ask questions about any document or read with token-budgeted memory.
• 🖥️ Terminal Dashboard: Browse, search, filter, and read past summaries.

Prerequisites: LLM Backend Server

srz requires an OpenAI API-compliant LLM server. While cloud provider APIs (OpenAI, Anthropic, Google, Groq, etc.) are supported, running a local LLM is strongly preferred for complete privacy, zero subscription fees, and offline capability:

• macOS: Llama-macOS (recommended local default; connects out-of-the-box on port 9931).
• Windows: Llama-Windows (recommended local default; connects out-of-the-box on port 9931).
• Linux: llama.cpp (recommended local default; run llama-server).
• Other Backends: Compatible with Ollama, LM Studio, vLLM, or cloud providers (OpenAI, Anthropic, Google Gemini, Groq, etc.).

See Configuring Your LLM Backend below for step-by-step setup instructions and profile templates.

Installation

Quick Install

macOS & Linux:

curl -LsSf https://raw.githubusercontent.com/NewGuy012/srz/master/scripts/install.sh | sh

Windows:

powershell -ExecutionPolicy ByPass -c "irm https://raw.githubusercontent.com/NewGuy012/srz/master/scripts/install.ps1 | iex"

Homebrew (macOS & Linux)

brew install NewGuy012/tap/srz

Build from Source (Cargo)

If you prefer building with Rust from source:

cargo install --path .

Usage

Hardware Recommendation

Run srz recommend to inspect your system's RAM/CPU and get the optimal model and context window:

srz recommend

Summarize

srz "https://en.wikipedia.org/wiki/Rust_(programming_language)" # Web article
srz "https://youtu.be/5C_HPTJg5ek"          # YouTube video
srz assets/document.pdf                     # PDF document
srz news "Rust language updates"            # Live news digest

Ask & Chat

srz ask "What are the main findings?"  # Ask latest read
srz ask assets/document.pdf "Summary"  # Ask document
srz ask -i                             # Interactive chat

Library, Search & Telemetry

srz browse         # Terminal dashboard
srz find "keyword" # Search past summaries

Cache & Storage Maintenance

srz cache clean    # Clean cache files
srz doctor         # Backend diagnostics

Run srz --help to see all available subcommands and flags.

Configuring Your LLM Backend

srz connects to any OpenAI-compatible API. Local inference is preferred for privacy and zero cost, but cloud providers are fully supported.

Local LLMs (Preferred)

• macOS & Windows (Default): Install Llama-macOS (macOS) or Llama-Windows (Windows). Launch the app and load the model—srz connects automatically to http://localhost:9931/v1 with zero setup (default model: ggml-org/gemma-4-E4B-it-GGUF:Q8_0).
  • In Llama GUI, simply select the simplified model card shown by srz recommend:
    • Model: gemma-4
    • Badges: E4B Q8_0 (or 26B-A4B Q8_0 for 64GB+ workstations)
    • Context: 32k ctx (or 64k ctx / 128k ctx)

Cloud Providers (Optional)

srz works with any OpenAI-compatible provider (OpenAI, Gemini, Groq, Anthropic):

export OPENAI_BASE_URL="https://api.openai.com/v1" OPENAI_MODEL="gpt-4o-mini" OPENAI_API_KEY="sk-..."

Hardware-Tailored Configuration (srz config init)

Run srz config init to auto-generate a ~/.config/srz/config.toml tailored to your machine's hardware:

base_url = "http://localhost:9931/v1"
model = "ggml-org/gemma-4-E4B-it-GGUF:Q8_0"
context_window = 32768

[profiles.openai]
base_url = "https://api.openai.com/v1"
model = "gpt-4o-mini"
api_key = "sk-..."

Switch profiles on the fly with --profile:

srz "The Rust Programming Language" --profile openai

Documentation

For full guides, tutorials, architecture specifications, and complete command references, visit the srz Documentation Site.