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Admin's Guide to TaleWeave AI

Contents

Hardware

Disk space

The amount of disk space required depends primarily on the LLM and Stable Diffusion checkpoints being used.

The game world is usually < 1MB and up to 2 copies of each world are kept on disk. The images rendered for various objects and events in the game can grow over time, but each image should be about 1MB, depending on the image size that you choose.

Approximate disk space requirements:

LLM / SD SD v1.5 (3-4GB) SDXL (6-8GB)
7-8b (4-6GB) 8-10GB 10-12GB
14b (8-10GB) 15GB 20GB
30b (16-20GB) 25GB 30GB
70b (30-40GB) 35GB 50GB

The exact size will vary by model, checkpoint, quantization, etc, and is likely to grow over time.

GPU and VRAM

Technically, you do not need a GPU to run TaleWeave AI. However, performance will be much better with at least one GPU. Running the LLM on CPU is not recommended and will impact the game's performance, but it is possible.

If you want to render images of the world while the characters are acting, you will need two GPUs or you will need to run image generation on the CPU.

The required amount of VRAM depends on which models you choose and their memory requirements, which is related to parameter size and quantization.

LLM / SD SD v1.5 SDXL
7-8b 1x 16GB 1x 24GB or 8GB + 16GB
14b 1x 24GB or 8GB + 16GB 2x 16-24GB
30b 1x 48GB or 8GB + 32GB 1x 48GB or 16GB + 32GB
70b* 8GB + 48GB 16GB + 48GB

Notes:

  1. 70b models need to be quantized to 4-bit or so to run on a 48GB GPU
  2. While it may be possible to run both text and image generation on the same GPU, two GPUs is recommended

Networking and ports

If you want to make the websocket server accessible over the internet, you will need at least one open port.

If you are using a load balancer, make sure it is compatible with websockets.

Setup

Clone the git repository

Clone the TaleWeave AI repository:

git clone https://github.com/ssube/TaleWeaveAI.git
cd TaleWeaveAI

This will clone the main branch, which is currently the development branch and may not be totally stable.

Set up a virtual environment

Set up a virtual environment to manage the dependencies:

# Create a virtual environment
python3 -m venv venv

# Activate the virtual environment
source venv/bin/activate

If you prefer using Conda or other tools, you can create an environment using their commands instead. Make sure they are compatible with pip packages.

Install the pip dependencies

Install the pip dependencies into your virtual environment:

# Install dependencies
pip install -r requirements.txt

Launch Ollama for text generation

Since TaleWeave AI is a text adventure, some kind of text generator is required. By default, TaleWeave AI is designed to work with locally-hosted LLM servers, like Ollama.

Ollama releases binaries for Linux, Mac, and Windows, along with a Docker container that works on RunPod and other GPU container services.

TODO

If you are using Ollama, you will need to set the following variables in your server environment:

PACKIT_DRIVER=ollama
OLLAMA_API=http://127.0.0.1:11434

If you are running Ollama with a GPU, you should also set the number of GPU layers and context length:

OLLAMA_NUM_GPU=100
OLLAMA_NUM_CTX=8192

These environment variables need to be set in the terminal where TaleWeave AI will be running, they are not used by the Ollama server.

Please see the Ollama docs for more details:

Using vLLM

You can use vLLM for text generation instead of Ollama. This has not been thoroughly tested, but anything server that is compatible with the OpenAI API should work, and vLLM seems to work in general. Some models are available for vLLM on the HuggingFace Hub that are not available for Ollama, and performance differs on different hardware. Use the server that works for you.

If you are using vLLM, you will need to set the following variables in your server environment:

PACKIT_DRIVER=openai

Please see the vLLM docs for more details:

Using OpenAI

Optional: Launch ComfyUI for image generation

Register

Register a Discord bot

Configure

Configure the Discord bot

Configure the server environment

Optional: Configure image generation

Optional: Configure websocket server

Optional: Configure world size

Run

Choose a world prompt or template

Launch the game

To start a game simulation using the "outback animals" example prompt and running both the Discord both and websocket server:

# Start the TaleWeave AI engine
python3 -m taleweave.main \
  --world worlds/outback-animals-1 \
  --world-template ./taleweave/prompts.yml:outback-animals \
  --discord  \
  --server \
  --rooms 3 \
  --turns 30 \
  --optional-actions=true \
  --actions taleweave.systems.sim:init_actions \
  --systems taleweave.systems.sim:init_logic

This will generate a relatively small world with 3 rooms or areas, run for 30 steps, then save the game and shut down.

The world will be saved to a file named worlds/outback-animals-1.json and the state will be saved after each step to another file named worlds/outback-animals-1.state.json. The world can be stopped at any time by pressing Ctrl-C, although the step in progress will be lost. The saved state can be resumed and played for any number of additional steps by running the server again with the same arguments.

Note: module.name:function_name and path/filename.yml:key are patterns you will see repeated throughout TaleWeave AI. They indicate a Python module and function within it, or a data file and key within it, respectively.

The sim_systems provide many mechanics from popular life simulations, including hunger, thirst, exhaustion, and mood. Custom actions and systems can be used to provide any other mechanics that are desired for your setting. The logic system uses a combination of Python and YAML to modify the prompts connected to rooms, characters, and items in the world, influencing the behavior of the language models.

Connect and play