natshell 0.1.11

Natural language shell interface — a local-first agentic TUI powered by a bundled LLM

NatShell

Natural language shell interface for Linux, macOS, and WSL — a local-first agentic TUI powered by a bundled LLM.

Type requests in plain English and NatShell plans and executes shell commands to fulfill them, using a ReAct-style agent loop with a small local model (Qwen3-4B via llama.cpp). Supports optional remote inference via Ollama or any OpenAI-compatible API.

Install

From PyPI

pip install natshell              # Remote/Ollama mode (no C++ compiler needed)
pip install natshell[local]       # Includes llama-cpp-python for local inference

From source (recommended for GPU acceleration)

git clone https://github.com/Barent/natshell.git && cd natshell
bash install.sh

The installer handles everything — Python venv, GPU detection (Vulkan/Metal/CPU), llama.cpp build, model download, and Ollama configuration. No sudo required. Missing system dependencies (C++ compiler, clipboard tools, Vulkan headers, etc.) are detected and offered for install automatically.

Development setup

git clone https://github.com/Barent/natshell.git && cd natshell
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pip install llama-cpp-python                # CPU-only
# CMAKE_ARGS="-DGGML_VULKAN=on" pip install llama-cpp-python --no-cache-dir  # Vulkan (Linux)
# CMAKE_ARGS="-DGGML_METAL=on" pip install llama-cpp-python --no-cache-dir   # Metal (macOS)
natshell

Usage

natshell                          # Launch with defaults (local model)
natshell --model ./my-model.gguf  # Use a specific GGUF model
natshell --remote http://host:11434/v1 --remote-model qwen3:4b  # Use Ollama/remote API
natshell --download               # Download the default model and exit
natshell --update                 # Self-update from git and reinstall
natshell --config path/to/config.toml  # Custom config file
natshell --verbose                # Enable debug logging

Features

Agent Loop

NatShell uses a ReAct-style agent loop — the model reasons about your request, calls tools (shell commands, file operations, etc.), observes results, and iterates until the task is complete. Up to 15 tool calls per request by default.

Inference Backends

• Local: Bundled llama.cpp via llama-cpp-python. Default model is Qwen3-4B (Q4_K_M, ~2.5 GB), auto-downloaded on first run.
• Remote: Any OpenAI-compatible API — Ollama, vLLM, LM Studio, etc.
• Fallback: If the remote server is unreachable, NatShell automatically falls back to the local model.
• Runtime switching: Switch models on the fly with /model commands without restarting.

GPU Acceleration

• Auto-detects GPUs via vulkaninfo, nvidia-smi, and lspci
• Prefers discrete GPUs over integrated on multi-GPU systems
• Supports Vulkan (Linux/AMD/NVIDIA), Metal (macOS), and CPU fallback
• Prints helpful reinstall instructions if GPU support is missing

Tools

The agent has access to 8 tools:

• execute_shell — Run any shell command via bash
• read_file — Read file contents
• write_file — Write or append to files (always requires confirmation)
• edit_file — Targeted search-and-replace edits (always requires confirmation)
• run_code — Execute code snippets in 10 languages (Python, JS, Bash, Ruby, Perl, PHP, C, C++, Rust, Go)
• list_directory — List directory contents with sizes and types
• search_files — Search file contents (grep) or find files by name
• natshell_help — Look up NatShell documentation by topic

TUI Commands

Command	Description
/help	Show available commands
/clear	Clear chat and model context
/cmd <command>	Execute a shell command directly (bypasses AI, respects safety)
/model	Show current engine and model info
/model list	List models available on the remote server
/model use <name>	Switch to a remote model
/model switch	Switch local GGUF model (opens command palette)
/model local	Switch back to local model
/model default <name>	Save default remote model to config
/plan <description>	Generate a step-by-step plan (PLAN.md) from natural language
/exeplan run PLAN.md	Execute a previously generated plan
/history	Show conversation message count

Keyboard Shortcuts

Key	Action
Ctrl+C	Quit
Ctrl+E	Copy entire chat to clipboard
Ctrl+L	Clear chat
Ctrl+P	Command palette (model switching)
Ctrl+Y	Copy selected text

Safety

Commands are classified into three risk levels by a fast, deterministic regex-based classifier:

• Safe — auto-executed (ls, cat, df, grep, etc.)
• Confirm — requires user approval (rm, sudo, apt install, docker rm, iptables, etc.)
• Blocked — never executed (fork bombs, rm -rf /, destructive dd/mkfs to disks, etc.)

Additional safety features:

• Commands chained with &&, ||, ;, &, or | are split and each sub-command is classified independently
• Subshell expressions ($(...)) and backtick expansions are flagged for confirmation
• Sensitive file paths (SSH keys, /etc/shadow, .env) require confirmation for read_file
• Sensitive environment variables (API keys, tokens, credentials) are filtered from subprocesses
• Sudo passwords are cached for 5 minutes with automatic expiry
• LLM output is escaped to prevent Rich markup injection in the TUI
• API keys sent over plaintext HTTP trigger a warning

Safety modes are configurable: confirm (default), warn, or yolo. All patterns are customizable in config.

Configuration

Default configuration is bundled with the package. Copy it to ~/.config/natshell/config.toml to customize:

python -c "from pathlib import Path; import natshell; p = Path(natshell.__file__).parent / 'config.default.toml'; print(p.read_text())" > ~/.config/natshell/config.toml

Or if installed from source, copy src/natshell/config.default.toml directly.

Sections

• [model] — GGUF path, HuggingFace repo/file for auto-download, context size (0 = auto-detect from model), GPU layers, device selection
• [remote] — URL, model name, API key for OpenAI-compatible endpoints
• [ollama] — Ollama server URL and default model (used by /model list and /model use)
• [agent] — max steps (15), temperature (0.3), max tokens (2048)
• [safety] — mode, confirmation regex patterns, blocked regex patterns
• [ui] — theme (dark/light)

Environment Variables

• NATSHELL_API_KEY — API key for remote inference (alternative to storing in config file)

Cross-Platform Support

Feature	Linux	macOS	WSL
Shell execution	bash	bash	bash
GPU	Vulkan	Metal	Vulkan
Clipboard	wl-copy, xclip, xsel	pbcopy	clip.exe
Package manager	apt, dnf, pacman, zypper, apk, emerge	brew	apt
System context	lscpu, free, ip, systemctl	sw_vers, sysctl, vm_stat, ifconfig	lscpu, free, ip
Safety patterns	Linux + generic	macOS-specific (brew, launchctl, diskutil)	Linux + generic

Clipboard auto-detects the best backend with fallback to OSC52 terminal escape sequences for remote/VM sessions.

Architecture

src/natshell/
├── __main__.py              # CLI entry point, model download, engine wiring
├── app.py                   # Textual TUI application
├── config.py                # TOML config loading with env var support
├── config.default.toml      # Bundled default configuration
├── gpu.py                   # GPU detection (vulkaninfo/nvidia-smi/lspci)
├── platform.py              # Platform detection (Linux/macOS/WSL)
├── agent/
│   ├── loop.py              # ReAct agent loop with safety checks
│   ├── system_prompt.py     # Platform-aware system prompt builder
│   ├── context.py           # System info gathering (CPU, RAM, disk, network, etc.)
│   ├── context_manager.py   # Conversation context window management
│   └── plan.py              # Plan generation and execution
├── inference/
│   ├── engine.py            # Inference engine protocol + CompletionResult types
│   ├── local.py             # llama-cpp-python backend with GPU support
│   ├── remote.py            # OpenAI-compatible API backend (httpx)
│   └── ollama.py            # Ollama server discovery and model listing
├── safety/
│   └── classifier.py        # Regex-based command risk classifier
├── tools/
│   ├── registry.py          # Tool registration and dispatch
│   ├── execute_shell.py     # Shell execution with sudo, env filtering, truncation
│   ├── read_file.py         # File reading
│   ├── write_file.py        # File writing
│   ├── edit_file.py         # Targeted search-and-replace edits
│   ├── run_code.py          # Code execution in 10 languages
│   ├── list_directory.py    # Directory listing
│   ├── search_files.py      # Text/file search
│   └── natshell_help.py     # Self-documentation by topic
└── ui/
    ├── widgets.py           # TUI widgets (messages, command blocks, modals)
    ├── commands.py          # Command palette providers
    ├── clipboard.py         # Cross-platform clipboard integration
    └── styles.tcss          # Textual CSS stylesheet

Development

source .venv/bin/activate
pytest                    # Run tests (353 tests)
ruff check src/ tests/    # Lint

License

MIT