CLI-CHING

CLI-CHING is a command-line interface tool for consulting the I Ching (Book of Changes). It provides a digital means of casting hexagrams and receiving interpretations, blending ancient wisdom with modern technology. It does not cast for you, you must bring 3 coins and report their results back to the application, which will help you convert them into the correct line.

https://github.com/user-attachments/assets/133a7d1d-a4bc-4131-b675-4de0b2466ddb

Features

• Simple command-line interface
• Flexible coin toss input
• Hexagram visualization
• AI-powered interpretations
• History of recent consultations
• Supports quick queries via command-line arguments

Installation

1. Ensure you have Node.js installed on your system.
2. Clone this repository:

   git clone https://github.com/yourusername/cli-ching.git
   cd cli-ching

3. Install the required dependencies:

   npm install

Usage

Basic Usage

Run the script with:

node index.js

Follow the prompts to enter your question and coin tosses.

Quick Query

You can also start a consultation with a question directly from the command line:

node index.js -q "Will my project succeed?"

Coin Tossing

When prompted, enter the results of your coin tosses using T for tails and H for heads. For example:

• TTT (3 tails)
• TTH, THT, or HTT (2 tails, 1 head)
• THH, HTH, or HHT (1 tail, 2 heads)
• HHH (3 heads)

The order doesn't matter, so HTT is the same as TTH.

Interpreting Results

The tool will display your hexagram, including any changing lines. It will then provide an AI-generated interpretation based on your question and the resulting hexagram.

Configuration

CLI-CHING automatically saves your consultations to a .iching-throws file in your home directory. The three most recent consultations are displayed when you start the tool.

Dependencies

• axios: For making HTTP requests to the AI interpretation service
• figlet: For generating ASCII art text
• readline: For handling user input (built into Node.js)

AI Interpretation

The tool uses a local LLM (Language Model) running on http://localhost:1234 for generating interpretations. Ensure your LLM server is running before using the interpretation feature.

Customization

You can modify the getInterpretation function in index.js to use a different AI service or to implement your own interpretation logic.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.