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AI-Powered Conversational Shell 🤖

This project is a modern, conversational command-line shell that understands natural language. You can type plain English like "list all the folders on my desktop" or standard Linux commands like ls -a, and the AI will translate it into the correct command for your operating system and execute it.

The user interface is built with Textual, providing a rich, app-like experience in your terminal. The core intelligence is powered by a locally-run, open-source Large Language Model using Ollama.

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Core Features

• Natural Language Understanding: Ask the shell to perform tasks in plain English.
• Cross-Platform Translation: Type Linux commands like ls on Windows, and the AI will correctly translate them to PowerShell's Get-ChildItem.
• Multi-Layered Architecture:
  • Layer 1 (Cache): Provides instant responses for common commands (ls, pwd, dir, etc.).
  • Layer 2 (Rule Engine): Uses regular expressions to quickly handle simple, structured requests (e.g., "create folder 'x' on desktop").
  • Layer 3 (LLM): Uses a local AI model (phi-3:mini) for complex and novel queries, taught via few-shot prompting.
• TUI Interface: A rich, user-friendly terminal interface built with Textual.
• Local & Private: All AI processing is done locally via Ollama, so your data and commands never leave your machine.

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Setup and Installation

Follow these steps to get the AI Shell running on your local machine.

Prerequisites

• Python 3.8+
• Ollama (Download here)

Installation Steps

1. Clone the Repository:

   git clone <your-repository-url>
   cd <your-repository-name>

2. Set Up Virtual Environment:

   • Create the environment:

     python -m venv venv

   • Activate the environment:
     • On Windows (PowerShell): .\venv\Scripts\Activate.ps1
     • On macOS/Linux: source venv/bin/activate

3. Install Dependencies:

   pip install -r requirements.txt

4. Download the AI Model: Pull the recommended model using Ollama. This will download a few gigabytes.

   ollama pull phi3:mini

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How to Use

1. Activate Your Virtual Environment (if you haven't already).

2. Launch the Application: Use the Textual runner to start the shell.

   textual run main.py

   For debugging, you can use textual run --dev main.py and press F12 to see console output.

3. Interact with the Shell: Once the application is running, you can type your requests into the input box at the bottom and press Enter.

   Example Queries:

   • ls -a
   • list all files on my desktop
   • create a new folder named "project_alpha" in my documents
   • list all text files sorted by size
   • To leave the application, simply type exit.