llm-functions/README.md

LLM Functions: Extend LLM with functions written in Bash.

This project allows you to enhance large language models (LLMs) with custom functions written in Bash. Imagine your LLM being able to execute system commands, access web APIs, or perform other complex tasks – all triggered by simple, natural language prompts.

Prerequisites

Make sure you have the following tools installed:

• argc: A bash command-line framewrok and command runner
• jq: A JSON processor
• curl: A command-line tool for transferring data with URLs

Getting Started with AIChat

1. Clone the repository:

git clone https://github.com/sigoden/llm-functions

2. Build function declarations:

Before using the functions, you need to generate a ./functions.json file that describes the available functions for the LLM.

argc build-declarations <function_names>...

Replace <function_names>... with the actual names of your functions. Go to the ./bin directory for valid function names.

💡 You can also create a ./functions.txt file with each function name on a new line, Once done, simply run argc build-declarations without specifying the function names to automatically use the ones listed in.

3. Configure your aichat application:

Symlink this repo directory to aichat functions_dir:

ln -s "$(pwd)" "$(aichat --info | grep functions_dir | awk '{print $2}')"

Then, add the following settings to your AIChat configuration file:

function_calling: true

AIChat will automatically load functions.json and execute functions located in the ./bin directory based on your prompts.

4. Start using your functions:

Now you can interact with your LLM using natural language prompts that trigger your defined functions. For example:

$ aichat -r "%function%" What's the weather in London?
Call Function: get_current_weather --location=London
London: ☀️   🌡️+18°C 🌬️↑4.7m/s

Writing Your Own Functions

Create a new Bash script in the ./bin directory with the name of your function (e.g., get-current-weather). Use the following structure within the script:

# @describe Get the current weather in a given location.
# @env TOMORROW_API_KEY! The tomorrow.io api key
# @option --location! The city and state, e.g. San Francisco, CA

main() {
    curl "https://wttr.in/$(echo "$argc_location" | sed 's/ /+/g')?format=4&M"
}

eval "$(argc --argc-eval "$0" "$@")"

After creating your function, don't forget to rebuild the function declarations (step 2) to include it in your LLM's capabilities.

License

The project is under the MIT License, Refer to the LICENSE file for detailed information.