VShell

VShell is a powerful command-line interface (CLI) tool that leverages a Large Language Model (LLM) to process input files and generate a README file that will explain the source code functionaility and how to use it. Just imagine if someone give you a source code, and you want to have an overall idea about what it does, then use my application, it will give you a picture of it.Besides, it integrates with the OpenAI Chat Completions API (Groq) to deliver enhanced functionality for your data processing needs.

Demo

https://github.com/user-attachments/assets/cd0679f1-82b6-4547-9291-a6374744fd70

Features

• Accepts multiple input files as well as folders that has subfolders and files within as command-line arguments for streamlined batch processing.
• Streams output directly to the terminal via stdout by adding -s/--stream flag.
• Supports the option to save results to a specified output file instead of displaying them in the terminal.
• Integrates seamlessly with OpenAI’s Chat Completions API (Groq) to process input data.
• Logs detailed information about errors and debugging to stderr for easy troubleshooting.
• Supports the use of a .env file to configure API keys and other setup values automatically.
• Allows optional configuration of model parameters such as temperature for chat completion processing through a configuration file.

Installation

• Step 1: Install package

  npm install vshell

• Step 2: Create .env file and create GROQ_API_KEY

  GROQ_API_KEY=<your_api_key>

How to use

There are some examples included in the Code section of this package on npmjs. Or you can run it using one of your own files placed in the root directory, or any other directory you might make

To run VShell, use the following command syntax: vshell file_name(s) <options>

Options

• -V, --version : Output the version number.
• -d, --debug : Enable detailed debug output.
• -u, --update : Update VShell to the latest version.
• -m, --model : Specify the LLM model to use.
• -T, --temperature : Set the temperature parameter for the model (Groq) (default: 0.2).
• -o, --output : Specify an output file to save the results.
• -h, --help : Display help for VShell commands.
• -t, --token-usage : Speicfy specify the usage of token for prompt and response
• -s, --stream: Stream the output to stdout in real time

TOML config

VShell supports reading a .toml configuration file in the user's home directory to use as pre-set options when provided

If you do not want to provide options when typing on command line, then create a .config.toml in the home directory, and provide options to use:

# temperature <number>: Set model temperature (0.1 to 2)
temperature = 0.5

# output: Specify output file to save result
output = output.md

# tokenUsage <boolean>: Get token usage information
tokenUsage = true

# debug <boolean>: Enable detailed debug message
debug = true

# stream <boolean>: Stream the output to console screen
stream = true

Example

To process README.md with a custom temperature setting and save the result to output.txt, use: vshell ./README.md -t 0.5 -o output.txt This version improves the clarity and professionalism of the README while retaining all the necessary details.