Cherryberry

Welcome to CHERRYBERRY, your friendly AI text adventure!

This game is an experiment in using LLMs for text-mode gameplay. It's able to generate locations as you go, as well as process player actions and manage inventory (somewhat). The gameplay is limited, so treat it as a demo.

The game is saved frequently into JSON (hence the sluggishness), but it's safe to exit with CTRL-C anytime. If anything goes wrong, CTRL-C, and edit the files in the save directory.

Happy experimenting 😊

Demo

This demo has been recorded on an M1 Mac with 32 GB RAM. The demo is in real time (not sped up). You can see the model is a bit weak at times, and needs some corrections, but it's consistent enough for lightweight gameplay.

(41MB download, might take a tick ⌛)

Running

Download an LLM to your local machine. Recommended model is LLaMA2-13B-Psyfighter2-GGUF, the Q4_K_M variant. Why is it recommended you may ask? Because this is the model I've made the game with 😂

Mac M*

These instructions tested on Mac M1

My preferred installation option is via micromamba. Install micromamba, then:

micromamba create -n cherryberry -f environment.yml
micromamba activate cherryberry

If your system has python already installed, then you should be able to skip the above step, or you can replace it with venv installation.

Install dependencies:

CMAKE_ARGS="-DLLAMA_METAL=on" poetry install

If you don't like poetry, you can also install the dependencies manually using pip - have a look at the list in pyproject.toml.

python3 -m cherryberry \
	--model ../models/LLaMA2-13B-Psyfighter2.Q4_K_M.gguf \
	--n_ctx 4096 \
	--n_batch 512 \
	-ngl 1 \
	--threads 4

Linux/CUDA

These instructions tested on Ubuntu 20, with 3060 which is CUDA 8

My preferred installation option is via micromamba. Install micromamba.

Open up environment-cuda.yml and adjust cudnn and cudatoolkit-dev versions to match your GPU, then:

# This will take ages and download the Nvidia world.
micromamba create -n cherryberry -f environment-cuda.yml
micromamba activate cherryberry

If your system has python and CUDA dependencies already installed (for Nvidia, try to run nvcc), then you should be able to skip the above step, or you can replace it with venv installation.

Install dependencies:

CMAKE_ARGS="-DLLAMA_CUBLAS=on" poetry install 

If you don't like poetry, you can also install the dependencies manually using pip - have a look at the list in pyproject.toml.

python3 -m cherryberry \
	--model ../models/LLaMA2-13B-Psyfighter2.Q4_K_M.gguf \
	--n_ctx 4096 \
	--n_batch 512 \
	-ngl 200 \
	--threads 4

Change ngl and threads to suit. ngl should be set to the actual number of layers to offload to GPU.

Force LlamaCpp recompilation

If you are running into problems with compiling LlamaCpp for your target, go to llama-cpp-python and LlamaCpp instructions). In particular, I'm not sure how to install this in Windows.

Warning: poetry will compile LlamaCpp only on the first install, if you change the compile time flags (LLAMA_METAL, LLAMA_CUBLAS etc) you can force recompilation with:

poetry remove llama-cpp-python
CMAKE_ARGS="-DLLAMA_CUBLAS=on" poetry add llama-cpp-python
# Note this messes around with pyproject.toml and poetry.lock

Debug mode

To run the game in the debug mode:

# In one terminal window:
textual console
# In another
textual run --dev cherryberry.py --debug --model ...