🧠 How to Deploy TradingAgents.jl on a VPS — Complete Step-by-Step Guide

🧾 Introduction: Why Deploy TradingAgents.jl on a VPS?

TradingAgents.jl is a reinforcement learning environment built in Julia for designing, simulating, and testing trading strategies. Running it on a VPS offers several advantages over a local machine:

• 24/7 Stable Operation: Ideal for long-running training or simulation tasks.
• Remote Access: Easily manage from anywhere.
• Offloads Local Resources: Keeps your personal machine free for other work.

🧰 Prerequisites

Item	Description
A VPS	Recommended: Ubuntu 22.04 with at least 1 vCPU and 2GB RAM
SSH client	Use ssh on macOS/Linux or MobaXterm/PuTTY on Windows
Julia	Download from julialang.org

🧩 Step 1: Connect to VPS and Set Up Base Environment

1. SSH into Your VPS

ssh root@your-vps-ip

2. Update System Packages

sudo apt update && sudo apt upgrade -y

3. Install Dependencies

sudo apt install wget curl git build-essential python3-pip tmux -y

💾 Step 2: Install Julia

1. Download and Install Julia

wget https://julialang-s3.julialang.org/bin/linux/x64/1.10/julia-1.10.2-linux-x86_64.tar.gz
tar -xvzf julia-1.10.2-linux-x86_64.tar.gz
sudo mv julia-1.10.2 /opt/
sudo ln -s /opt/julia-1.10.2/bin/julia /usr/local/bin/julia

2. Verify Installation

julia --version
Expected output: julia version 1.10.2

📦 Step 3: Install TradingAgents.jl and Dependencies

Launch Julia:

julia

Inside the Julia REPL, run:

julia
using Pkg
Pkg.update()
Pkg.add("TradingAgents")
Pkg.add("IJulia")  # Optional for Jupyter notebook
Pkg.add("Flux")    # Required for training neural nets

🧪 Step 4: Test Example

Run this basic example in Julia REPL:

using TradingAgents
env = OrderBookEnv()
reset!(env)
step!(env, (LimitOrder(-1, 10.0, 1),))

📁 Step 5: Upload or Write Training Script

Save your agent training script as run_agent.jl. (You can use the full script I provided earlier.)

Upload Script from Local to VPS:

scp run_agent.jl root@your-vps-ip:/root/

🖥️ Step 6: Run Script with Tmux for Long Training

Use tmux to keep your session alive:

tmux new -s trading
julia run_agent.jl

To detach from tmux:

# Press Ctrl + B, then D

Reattach later with:

tmux attach -t trading

📊 (Optional) Step 7: Deploy Jupyter Notebook

1. Install Jupyter

pip3 install notebook

2. Run Jupyter

jupyter notebook --ip=0.0.0.0 --port=8888 --no-browser

Then access it via your browser:
http://your-vps-ip:8888

You can protect it with a token or password.

🧠 Step 8: After Deployment Tips

• Use BSON.jl to save trained models

• Log trading performance per episode

• Connect with live trading APIs (e.g., Binance) if deploying to real market

🧾 Summary: VPS Deployment Flowchart

1. Purchase a VPS (Ubuntu preferred)
2. SSH login
3. Install Julia + dependencies
4. Add TradingAgents.jl
5. Upload your training script
6. Use tmux to run long tasks
7. (Optional) Deploy Jupyter Notebook

📌 Appendix: Recommended VPS Providers (Julia-compatible)

Provider	Highlights	Link
LightNode	Hourly billing, 40+ global locations, Linux	https://www.lightnode.com/
Vultr	Developer-friendly, multiple global locations	https://www.vultr.com/
DigitalOcean	Great UI/UX, reliable for dev environments	https://www.digitalocean.com/