
llmcord
Make Discord your LLM frontend ● Supports any OpenAI compatible API (Ollama, LM Studio, vLLM, OpenRouter, xAI, Mistral, Groq and more)
Stars: 472

llmcord is a Discord bot that transforms Discord into a collaborative LLM frontend, allowing users to interact with various LLM models. It features a reply-based chat system that enables branching conversations, supports remote and local LLM models, allows image and text file attachments, offers customizable personality settings, and provides streamed responses. The bot is fully asynchronous, efficient in managing message data, and offers hot reloading config. With just one Python file and around 200 lines of code, llmcord provides a seamless experience for engaging with LLMs on Discord.
README:
llmcord transforms Discord into a collaborative LLM frontend. It works with practically any LLM, remote or locally hosted.
Just @ the bot to start a conversation and reply to continue. Build conversations with reply chains!
You can:
- Branch conversations endlessly
- Continue other people's conversations
- @ the bot while replying to ANY message to include it in the conversation
Additionally:
- When DMing the bot, conversations continue automatically (no reply required). To start a fresh conversation, just @ the bot. You can still reply to continue from anywhere.
- You can branch conversations into threads. Just create a thread from any message and @ the bot inside to continue.
- Back-to-back messages from the same user are automatically chained together. Just reply to the latest one and the bot will see all of them.
llmcord supports remote models from:
Or run a local model with:
...Or use any other OpenAI compatible API server.
- Supports image attachments when using a vision model (like gpt-4o, claude-3, llava, etc.)
- Supports text file attachments (.txt, .py, .c, etc.)
- Customizable personality (aka system prompt)
- User identity aware (OpenAI API and xAI API only)
- Streamed responses (turns green when complete, automatically splits into separate messages when too long)
- Hot reloading config (you can change settings without restarting the bot)
- Displays helpful warnings when appropriate (like "
⚠️ Only using last 25 messages" when the customizable message limit is exceeded) - Caches message data in a size-managed (no memory leaks) and mutex-protected (no race conditions) global dictionary to maximize efficiency and minimize Discord API calls
- Fully asynchronous
- 1 Python file, ~200 lines of code
-
Clone the repo:
git clone https://github.com/jakobdylanc/llmcord
-
Create a copy of "config-example.yaml" named "config.yaml" and set it up:
Setting | Description |
---|---|
bot_token | Create a new Discord bot at discord.com/developers/applications and generate a token under the "Bot" tab. Also enable "MESSAGE CONTENT INTENT". |
client_id | Found under the "OAuth2" tab of the Discord bot you just made. |
status_message | Set a custom message that displays on the bot's Discord profile. Max 128 characters. |
max_text | The maximum amount of text allowed in a single message, including text from file attachments. (Default: 100,000 ) |
max_images | The maximum number of image attachments allowed in a single message. Only applicable when using a vision model. (Default: 5 ) |
max_messages | The maximum number of messages allowed in a reply chain. When exceeded, the oldest messages are dropped. (Default: 25 ) |
use_plain_responses | When set to true the bot will use plaintext responses instead of embeds. Plaintext responses have a shorter character limit so the bot's messages may split more often. Also disables streamed responses and warning messages.(Default: false ) |
allow_dms | Set to false to disable direct message access.(Default: true ) |
permissions | Configure permissions for users , roles and channels , each with a list of allowed_ids and blocked_ids . Leave allowed_ids empty to allow ALL. Role and channel permissions do not affect DMs. You can use category IDs to control grouped channel permissions.
|
Setting | Description |
---|---|
providers | Add the LLM providers you want to use, each with a base_url and optional api_key entry. Popular providers (openai , ollama , etc.) are already included. Only supports OpenAI compatible APIs.
|
model | Set to <provider name>/<model name> , e.g:- openai/gpt-4o - ollama/llama3.3 - openrouter/anthropic/claude-3.5-sonnet
|
extra_api_parameters | Extra API parameters for your LLM. Add more entries as needed. Refer to your provider's documentation for supported API parameters. (Default: max_tokens=4096, temperature=1.0 ) |
system_prompt | Write anything you want to customize the bot's behavior! Leave blank for no system prompt. |
-
Run the bot:
No Docker:
python -m pip install -U -r requirements.txt python llmcord.py
With Docker:
docker compose up
-
If you're having issues, try my suggestions here
-
Only models from OpenAI API and xAI API are "user identity aware" because only they support the "name" parameter in the message object. Hopefully more providers support this in the future.
-
PRs are welcome :)
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