smart-linux-assistant 0.5.0

An AI-powered Linux productivity assistant for command analysis, troubleshooting, and knowledge management.

Smart Linux Assistant

Smart Linux Assistant is an AI-powered Linux operations assistant that understands natural language, safely executes shell commands, retrieves Linux knowledge, explains errors, and assists users with troubleshooting. The current version implements the core command execution engine and foundational architecture for future AI capabilities.

Project Overview

Smart Linux Assistant is a command-line utility that executes shell commands and returns structured outcomes. The tool captures the command, exit code, stdout, stderr, execution timestamp, and duration to make downstream automation and logging straightforward.

System Architecture

• CLI (linux_assistant.cli.main) accepts user commands and options and delegates execution to CommandExecutor.
• CommandExecutor runs shell commands using subprocess.run and returns a CommandResult dataclass describing the outcome.
• Centralized logging is provided by linux_assistant.utils.logger, writing to logs/smart_linux_assistant.log with rotation.
• Runtime paths and directories are managed by linux_assistant.config.settings and can be initialized with initialize_app_filesystem().

Tech Stack

• Python 3.11+
• Typer (CLI)
• Standard library: subprocess, logging, shutil, dataclasses, pathlib, datetime

Prerequisites

1. Python 3.11 or newer.
2. Optional: a virtual environment tool (venv).
3. No Dockerfile or docker-compose are included in this repository.

Local Setup & Installation

1. Clone the repository:

git clone https://github.com/shubham-k-jha-dev/smart-linux-assistant
cd smart-linux-assistant

2. Create and activate a virtual environment:

# Linux/macOS
python3 -m venv .venv
source .venv/bin/activate

# Windows (PowerShell)
python -m venv .venv
.venv\\Scripts\\Activate.ps1

3. Install development dependencies:

pip install -r requirements-dev.txt

4. (Optional) Install the package in editable mode to enable the smart-linux CLI entrypoint:

pip install -e .

5. (Optional) Ensure runtime directories exist from Python:

from linux_assistant.config.settings import initialize_app_filesystem
initialize_app_filesystem()

Environment Variables

This project does not require any environment variables for its core CLI functionality. The repository includes an empty .env.example placeholder.

Variable	Description	Example
(none)	No required environment variables for CLI execution	-

Usage / API Reference

The project exposes the console scripts smart-linux and sla (configured in pyproject.toml).

• Run a shell command:

smart-linux run "echo hello"

• Options:

  • --timeout <seconds> — maximum seconds to allow command to run (default: 30)
  • --check — treat non-zero exit codes as errors and exit with that code
  • --suggest-fix — if the command fails, use AI to suggest a corrected version (requires --check; requires GROQ_API_KEY, same as explain/fix/search)

• Doctor command (checks common tools):

smart-linux doctor

• Get an AI-powered explanation of a command or error message:

smart-linux explain "permission denied when running ./script.sh"

Requires a free Groq API key set as an environment variable:

export GROQ_API_KEY="your-key-here"

Get a free key at console.groq.com.

• Fix a failing command:

smart-linux fix "ls /nonexistent"

• Options:

  • --timeout <seconds> — maximum seconds to allow the command to run (default: 30)

• This runs the command and, if it fails, uses the AI to suggest a corrected version. Requires the same GROQ_API_KEY environment variable as the explain command.

• Search for a Linux task in plain language:

smart-linux search "find the 10 largest files in the current directory"

• This returns a concrete command and brief explanation for the requested task. Requires the same GROQ_API_KEY environment variable as the explain command.

Example output

Successful command:

$ smart-linux run "echo hello"
hello

Failed command (example):

$ smart-linux run "ls nonexistent" --check
ls: cannot access 'nonexistent': No such file or directory

These outputs reflect the CLI behaviour: standard output is printed for successful commands; standard error is printed for failures and, when --check is used, the CLI exits with the command's exit code.

Failed command with an AI-suggested fix:

$ smart-linux run "gti status" --check --suggest-fix
gti: command not found

Suggested fix:
  git status

--suggest-fix requires --check (fix suggestions only apply to command failures detected via --check); calling it without --check exits immediately with an error.

Roadmap / Current Status

• Core CLI: implemented — run and doctor commands are provided in linux_assistant.cli.main.
• Command execution: implemented using linux_assistant.services.command_executor.CommandExecutor which returns CommandResult instances.
• Logging & configuration: implemented via linux_assistant.utils.logger and linux_assistant.config.settings.
• Packaging: console script entry points are declared in pyproject.toml.
• AI-powered explanations: implemented — smart-linux explain uses the Groq API (llama-3.3-70b-versatile) to generate plain-language explanations of commands and error messages, via linux_assistant.services.explainer.Explainer. Requires a user-supplied GROQ_API_KEY environment variable.
• AI-powered fix suggestions: implemented — smart-linux fix runs a failing command and suggests a corrected version; smart-linux run --check --suggest-fix offers the same suggestion inline as part of normal command execution. Both use linux_assistant.services.explainer.Explainer.suggest_fix().
• AI-powered search: implemented — smart-linux search answers natural-language questions about Linux tasks via linux_assistant.services.search.Searcher.
• Production hardening: implemented — API timeouts, retry logic, rate-limit-specific handling, input truncation, and documented OS/privacy limitations across all AI-backed commands.
• Additional AI features (command history awareness, documentation lookup) are planned but not yet implemented.

Known Limitations

• Tested and verified on Linux (native and WSL). Not yet tested on macOS or native Windows Python — behavior on those platforms is currently unverified, though the codebase avoids Linux-only APIs where possible.

Privacy Note

The explain, fix, and search commands send the command text, error output, or your query to Groq's API for processing. Avoid running these commands on text that contains secrets, passwords, or sensitive data, since that content leaves your machine.

Install from PyPI

If this package is published to PyPI, it can be installed with:

pip install smart-linux-assistant

Testing

Run the test suite with pytest:

pytest

License

MIT License — see LICENSE.

Contributing

• Run tests with pytest before opening a pull request.
• Follow standard Python packaging best practices.