<p align="center">
<img src="assets/logo.svg" alt="srz - Rust CLI for Summarizing Webpages, Books, and Streams" width="760">
</p>
# `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** (Mozilla Readability extraction)
- 📺 **YouTube video transcripts**
- 📄 **PDF documents & local files**
- ⌨️ **Unix stdin streams**
- 📚 **Books**
- 📰 **Live news digests & universal RSS/Atom feeds**
> 📖 **Documentation**: Visit the [**srz Documentation Site**](https://newguy012.github.io/srz/) for full guides, tutorials, and command references.
## Highlights
```mermaid
%%{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.
- 📰 **Google News Feeds**: Summarize top stories and search topics by default.
- ⚡ **Terminal Paging**: Clean CLI output with auto-paging for long summaries.
- 💬 **Interactive Q&A**: Chat and ask questions about any document or read.
- 🖥️ **Terminal Dashboard**: Browse, search, filter, and read past summaries.
- 🔍 **Fast Offline Search**: Find past summaries instantly without internet.
- 🗄️ **Local Smart Cache**: Saves past reads locally for instant offline review.
- 📖 **Clean Reader Views**: Distraction-free HTML and Markdown with dark mode.
## 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](https://github.com/ggml-org/Llama-macOS) (recommended local default; connects out-of-the-box on port `9931`).
- **Windows**: [Llama-Windows](https://github.com/ggml-org/Llama-Windows) (recommended local default; connects out-of-the-box on port `9931`).
- **Linux**: [llama.cpp](https://github.com/ggml-org/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](#configuring-your-llm-backend) below for step-by-step setup instructions and profile templates.
## Installation
### Quick Install
**macOS & Linux**:
```bash
**Windows**:
```powershell
### Homebrew (macOS & Linux)
```bash
brew install NewGuy012/tap/srz
```
### Build from Source (Cargo)
If you prefer building with Rust from source:
```bash
cargo install --path .
```
## Usage
### Summarize
```bash
srz "https://en.wikipedia.org/wiki/Rust_(programming_language)" # Article
srz "https://youtu.be/5C_HPTJg5ek" # YouTube video
srz assets/document.pdf # PDF document
srz "The Rust Programming Language" --open # Book synopsis
srz news "Rust language updates" -t week # News digest
### Ask & Chat
```bash
srz ask "What are the main findings?" # Ask latest read
srz ask assets/document.pdf "Summary" # Ask document
srz ask -i # Interactive chat
srz ask --chats # List saved chats
srz ask --resume 1 # Resume chat session
srz ask --show-chat 1 # Show transcript
srz ask --delete-chat 1 # Delete chat session
```
### Library, Search & Telemetry
```bash
srz browse # Terminal dashboard
srz find "keyword" # Search past summaries
srz history # View recent reads
srz stats # Reading statistics
```
### Cache & Storage Maintenance
```bash
srz cache size # Check disk usage
srz cache prune --older-than 14d # Prune older cache
srz cache prune --max-size 500MB # Enforce size limit
srz cache clean # Clean cache files
srz cache clean --reset-db # Full database reset
srz doctor # Backend diagnostics
```
Run `srz --help` to see all available subcommands and flags.
## Features
- [**Universal Ingestion**](docs/OVERVIEW.md#2-key-cli-features--commands)
- [**Interactive Q&A (`srz ask`)**](docs/OVERVIEW.md#2-key-cli-features--commands)
- [**TUI Dashboard (`srz browse`)**](docs/OVERVIEW.md#2-key-cli-features--commands)
- [**3 Summary Presets**](docs/OVERVIEW.md#2-key-cli-features--commands)
- [**Offline BM25 Library Search**](docs/OVERVIEW.md#2-key-cli-features--commands)
> For full guides and tutorials, visit the [**Documentation Website**](https://newguy012.github.io/srz/). For architectural diagrams, lifecycle execution sequences, and in-depth subsystem specs, see [**`OVERVIEW.md`**](docs/OVERVIEW.md).
## 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](https://github.com/ggml-org/Llama-macOS) (macOS) or [Llama-Windows](https://github.com/ggml-org/Llama-Windows) (Windows). Launch the app and load a model—`srz` connects automatically to `http://localhost:9931/v1` with zero setup.
- **Linux**: Build or install [llama.cpp](https://github.com/ggml-org/llama.cpp) and launch `llama-server`:
```bash
llama-server -m model.gguf --port 9931
llama-server -m model.gguf --port 8080
export OPENAI_BASE_URL="http://localhost:8080/v1"
```
- **Diagnostics**: Run `srz doctor` to test server latency and `srz models` to list loaded models.
### Cloud Providers (Optional)
`srz` works with any OpenAI-compatible provider (OpenAI, Anthropic, Google, Groq, OpenRouter):
```bash
export OPENAI_BASE_URL="https://api.openai.com/v1" OPENAI_MODEL="gpt-4o-mini" OPENAI_API_KEY="sk-..."
# Or on the fly via CLI flag:
srz "1984" --base-url "https://api.openai.com/v1" --model "gpt-4o-mini" --api-key "sk-..."
```
### Profile Switching (`~/.config/srz/config.toml`)
Run `srz config init` to generate a starter config, then configure named profiles:
```toml
# Default local model
base_url = "http://localhost:9931/v1"
model = "ggml-org/gemma-4-E4B-it-GGUF:Q8_0"
# Storage limits and retention policies
[cache]
max_size_mb = 500 # Disk budget (LRU eviction past threshold)
pages_ttl_days = 7 # Scraped web content & news TTL
search_ttl_days = 14 # Book metadata & search candidates TTL
summaries_ttl_days = 90 # Generated LLM outputs TTL
auto_prune = true # Opportunistic 24h background pruning
# Cloud profile (e.g. OpenAI or Anthropic)
[profiles.openai]
base_url = "https://api.openai.com/v1"
model = "gpt-4o-mini"
api_key = "sk-..."
```
Switch profiles on the fly with `--profile`:
```bash
srz "The Rust Programming Language" # Default model
srz "The Rust Programming Language" --profile openai # Cloud profile
```
## Documentation & Architecture
- 🌐 [**Documentation Website**](https://newguy012.github.io/srz/): Comprehensive mdBook site covering installation, quick start, command reference, and configuration.
- 🏗️ [**Architecture Overview (`OVERVIEW.md`)**](docs/OVERVIEW.md): Detailed Mermaid architecture diagrams, execution sequence flows, storage schemas, and subsystem specifications.
- 🦀 [**Rust Learning Guide (`RUST_LEARNING_GUIDE.md`)**](docs/RUST_LEARNING_GUIDE.md): Hands-on case study exploring Rust systems programming concepts and patterns using real `srz` code.
## Running Tests & Static Analysis
```bash
# Run full automated test suite (119 tests)
cargo test
# Strict static analysis (warnings denied)
cargo clippy --all-targets -- -D warnings
```