LLMCord - An LLM client as a discord bot

This bot allows you to use LLMs such as ChatGPT, LLaMA3, and Gemini 1.5 from Discord

Installation

Using pre-created executables

Download the executable for the latest release from Releases

NOTE: Currently MacOS and Linux are not supported

Manual

1. Clone this repo or download the source code from one of the Releases

$ git clone https://github.com/grqphical/LLMCord.git

2. Create a virtual environment

$ python -m venv venv

3. Activate the virtual environment

$ ./venv/Scripts/activate

NOTE On linux the path will be ./venv/bin/activate

4. Install dependencies

$ pip install -r requirements.txt

Usage

1. Create a new Discord Application at the Discord Developer Portal and configure it to be a bot. (Guide Here)
2. Create a .env file and add your bot's token as DISCORD_TOKEN
3. Create a file called llmcord.toml and add this to it:

system_prompt = "Use markdown if neccessary."
default_model = "llama3-70b"

[models.llama3-70b]
base_url = "https://api.groq.com/openai/"
model = "llama3-70b-8192"
token = "API_TOKEN_HERE"
client = "OpenAIClient"

NOTE I am using Groq AI here as an example so I have selected the OpenAIClient due to it's API being compatible with OpenAI however LLMCord also includes a Google Gemini 1.5 client that you can use as GeminiClient

Explanation of config

system_prompt - Allows you to control the system prompt of the AI

default_model - Specifies the default model REQUIRED

For each model you wish to make create it as a seperate table with a display name. In this case I chose llama3-70b. base_url - Base URL for the API REQUIRED

model - Which model to use REQUIRED

token - API token for API, REQUIRED IF NEEDED BY API

client - Which Client to use to send the request. The two included clients are OpenAIClient and GeminiClient. REQUIRED

Then finally run

$ python -m llmcord

Now you should be able to use LLMCord in any servers you have invited it to.

Contributing

See CONTRIBUTING.md

Plugins/Custom Clients

You are able to make your own API clients by creating a python script in the plugins/ folder. Simply create a class that inherits from plugins.BaseClient and implement the get_response method. Make sure it is a coroutine. In order to access the API use the aiohttp library as it is already installed and used by LLMCord.

Look in the plugins folder for examples of custom clients

Changelog

1.2.3

• Refactored code to work with Pyinstaller

• Pre built executables are now able to be distrubuted

1.2.2

• Moved commands into their own Cogs

• Added unit tests for Config and Context

• Fixed linting errors

• Added CI for unit tests

1.2.1

• Fixed error handling with certain edge cases when loading the configuration

• Added error handling when selecting an invalid/undefined model. Before it would just get stuck in an infinite loop

• Improved documentation

1.2.0

• Added custom logger

1.1.0

• Added support for custom clients

• Included OpenAIClient and GeminiClient by default

• Changed /list to now show every model on a different line

Running the test suite

Make sure to install both requirements.txt and requirements.tests.txt. Then run pytest to run the tests.

Roadmap

I may or may not add these features later on so feel free to make a PR and implement these features.

• Custom API Handlers (ability to define your own plugins to work with non-OpenAI compatible APIs)

• File uploads

• Integration with non LLM's (eg. DALL-E for image generation)

License

LLMCord is licensed under the MIT License