How to run Codeassist using Ubuntu WSL

Reruitmens

Minimum Specification CPU : 4 core RAM : 8GB (12GB recommended) Good internet speed

Installation

Install Dependencies

sudo apt update && sudo apt upgrade -y

sudo apt install screen curl iptables build-essential git wget lz4 jq make gcc nano automake autoconf tmux htop nvme-cli libgbm1 pkg-config libssl-dev libleveldb-dev tar clang bsdmainutils ncdu unzip libleveldb-dev -y

Docker

sudo apt update -y && sudo apt upgrade -y
for pkg in docker.io docker-doc docker-compose podman-docker containerd runc; do sudo apt-get remove $pkg; done

sudo apt-get update
sudo apt-get install ca-certificates curl gnupg
sudo install -m 0755 -d /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg
sudo chmod a+r /etc/apt/keyrings/docker.gpg

echo \
  "deb [arch="$(dpkg --print-architecture)" signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu \
  "$(. /etc/os-release && echo "$VERSION_CODENAME")" stable" | \
  sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

sudo apt update -y && sudo apt upgrade -y

sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

sudo docker run hello-world

Python

sudo apt install python3 python3-pip python3-venv python3-dev -y

UV

echo 'export PATH="$HOME/.local/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc

Verify UV instalation

uv --version

Clone Codeassist Repository

git clone https://github.com/gensyn-ai/codeassist.git
cd codeassist

Running

To run CodeAssist, simply execute the following command:

uv run run.py

If you see this, wait a minut then enter your hugging face token

HuggingFace Token

To start CodeAssist, you will need to have a HuggingFace token. Follow these instructions and generate a token with Write access.

Login

After you see http://localhost:3000 on terminal open http://localhost:3000 then login, after login complete mission

Note if you are running swarm you can change port 3000 to 3001 on

nano run.py

Or running with

uv run run.py --port 3001

and open http://localhost:3001