Tater is an AI assistant that connects to any OpenAI-compatible LLM, giving you a powerful set of AI-driven tools. It includes a WebUI for setup and private chats, and works across Discord, Telegram, IRC, Matrix, Home Assistant, HomeKit, and even the OG Xbox via XBMC4Xbox

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🌐 Tater Platform Overview

Platform	Description
discord	Full-featured Discord bot that runs compatible plugins and supports rich interactions, media output, and background jobs.
homeassistant	Native integration for Home Assistant, allowing Tater to act as a voice-enabled AI assistant through the Assist pipeline and control smart devices directly.
ha_automations	Lightweight Home Assistant automation-only endpoint for direct tool execution. Designed for fast, reliable automations like camera events, doorbell alerts, weather summaries, and dashboard sensors. Intended to be used with the Tater Automations custom component, which provides a native “Call Tater automation tool” action in Home Assistant.
ai_task	Built-in scheduled task runner for timed and recurring AI jobs, with delivery routed through notifier platforms (Discord, Telegram, Matrix, IRC, Home Assistant, and more).
homekit	Siri / Apple Shortcuts integration for HomeKit, enabling “Hey Siri, ask Tater…” voice commands, per-device conversation sessions, and plugin-backed actions.
irc	Lightweight IRC bot that responds to mentions and runs compatible plugins.
matrix	Modern Matrix client with end-to-end encryption support, Markdown rendering, and full plugin compatibility — bringing Tater to federated chat networks like Element and Cinny.
telegram	Telegram bot integration with chat allowlists, DM user restrictions, queued notifications, media delivery, and plugin-backed tool execution.
xbmc	OG Xbox integration for XBMC4Xbox, provided by the custom Cortana-powered skin and script at skin.cortana.tater-xbmc, enabling an on-console AI assistant with chat history, quick asks, and plugin-powered actions.
webui	Streamlit-based WebUI for chatting, configuring plugins, and managing settings.

🧩 Tater Plugin Ecosystem

Tater now uses a remote plugin store.
Plugins are no longer bundled with Tater — they are installed, updated, and restored automatically from the Tater Shop.

🛒 Tater Plugin Store

All plugins, versions, descriptions, and update history now live here:

👉 https://github.com/TaterTotterson/Tater_Shop

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🔍 Browsing Plugins

From the WebUI you can:

• Search by name or description
• Filter by platform (Discord, WebUI, Home Assistant, etc.)
• See installed vs store versions
• One-click install, update, remove
• Bulk “Update All”

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♻️ Auto-Restore

When Tater starts:

Any plugin that was enabled in Redis but missing on disk
is automatically re-downloaded from the store.

No config loss. No manual installs. No volume mapping required.

Note:

• Do not use a thinking model with tater
• Tater currently recommends using qwen3-next-80b, qwen3-coder-30b or Gemma3-27b

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Installation

Tater is available in the Unraid Community Apps store.

You can install both:

• Tater
• Redis Stack

directly from the Unraid App Store with a one-click template.

🏠 Home Assistant

A dedicated Home Assistant add-on repository is available here:

https://github.com/TaterTotterson/hassio-addons-tater

Add the Tater add-on repository

Click the button below to add the repository to Home Assistant:

Once added, the following add-ons will appear in the Home Assistant Add-on Store:

• Redis Stack – required for Tater memory, plugins, and automations
• Tater AI Assistant – the main Tater service

Install order

1. Install and start Redis Stack
2. Install Tater AI Assistant
3. Configure your LLM and Redis settings in the Tater add-on
4. Start Tater

This is the recommended setup for most users and provides the smoothest experience.

🔌 Home Assistant Integration (Optional Enhancements)

Tater AI supports deeper integration with Home Assistant through a couple of companion repositories. These extend Tater’s usefulness in smart home setups by enabling voice/text conversation control and native automation triggers.

📍 Tater-HomeAssistant

https://github.com/TaterTotterson/Tater-HomeAssistant

A Home Assistant custom integration that allows Tater to function as a Conversation Agent inside Home Assistant’s Assist pipeline. This enables voice or text interactions from Home Assistant to be routed directly to your Tater backend, where plugins can be executed and contextual responses returned.

Key benefits:

• Use Tater as a native voice and text assistant within Home Assistant
• Routes Assist queries directly to your running Tater AI backend
• Supports plugins that implement handle_homeassistant(...)
• Maintains conversation context for more natural, multi-turn interactions

This integration is required if you want Tater to participate directly in Home Assistant conversations or voice control.

⚙️ tater_automations

https://github.com/TaterTotterson/tater_automations

A Home Assistant automation-focused custom component that exposes Tater’s tools as native Home Assistant automation actions. This allows Home Assistant automations to call specific Tater tools directly, without REST calls, scripts, or YAML workarounds.

Key benefits:

• Adds a native “Call Tater automation tool” action in Home Assistant automations
• Designed for fast, reliable, automation-only execution
• Ideal for camera events, alerts, summaries, and AI-driven logic
• Integrates cleanly into Home Assistant’s automation editor and UI

This component is required if you want to trigger Tater tools directly from Home Assistant automations.

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Local Installation (Advanced)

Prerequisites

• Python 3.11
• Redis-Stack
• OpenAI API–compatible LLM app (such as Ollama, LocalAI, LM Studio, Lemonade, or OpenAI API)
• Docker (optional, for containerized deployment)

Setting Up Locally

1. Clone the Repository

git clone https://github.com/TaterTotterson/Tater.git

2. Navigate to the Project Directory

cd Tater

3. Install Dependencies

Using pip, run:

pip install -r requirements.txt

4. Configure Environment Variables

Create a .env file in the root directory.
Below are example configurations for local LLM backends (Ollama, LM Studio, LocalAI) and ChatGPT (GPT-4o, etc.).

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Example: Local backend (Ollama, LM Studio, LocalAI)

LLM_HOST=127.0.0.1  
LLM_PORT=11434  
LLM_MODEL=gemma3-27b-abliterated  
REDIS_HOST=127.0.0.1  
REDIS_PORT=6379  

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Example: ChatGPT (GPT-4o, etc.)

LLM_HOST=https://api.openai.com  
LLM_PORT=  
LLM_MODEL=gpt-4o  
LLM_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx  
REDIS_HOST=127.0.0.1  
REDIS_PORT=6379  

Note: When using ChatGPT, leave LLM_PORT blank.
Tater will automatically connect using HTTPS without appending a port number.

5. Run the Web UI

Launch the web UI using Streamlit:

streamlit run webui.py

Docker

1. Pull the Image

Pull the prebuilt image with the following command:

docker pull ghcr.io/tatertotterson/tater:latest

2. Configuring Environment Variables

Ensure you supply the required environment variables. You can pass these using the -e flag when starting the container.

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Example: Local backend (Ollama, LM Studio, LocalAI)

docker run -d --name tater_webui \
  -p 8501:8501 \
  -p 8787:8787 \
  -p 8788:8788 \
  -p 8789:8789 \
  -p 8790:8790 \
  -e LLM_HOST=127.0.0.1 \
  -e LLM_PORT=11434 \
  -e LLM_MODEL=gemma3-27b-abliterated \
  -e REDIS_HOST=127.0.0.1 \
  -e REDIS_PORT=6379 \
  ghcr.io/tatertotterson/tater:latest

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Example: ChatGPT (GPT-4o, etc.)

docker run -d --name tater_webui \
  -p 8501:8501 \
  -p 8787:8787 \
  -p 8788:8788 \
  -p 8789:8789 \
  -p 8790:8790 \
  -e LLM_HOST=https://api.openai.com \
  -e LLM_PORT= \
  -e LLM_MODEL=gpt-4o \
  -e LLM_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxx \
  -e REDIS_HOST=127.0.0.1 \
  -e REDIS_PORT=6379 \
  ghcr.io/tatertotterson/tater:latest

Note: When using ChatGPT, leave LLM_PORT blank.
Tater will automatically connect using HTTPS without appending a port number.

3. Access the Web UI

Once the container is running, open your browser and navigate to:

http://localhost:8501

The Streamlit-based web UI will be available for interacting with Tater.

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