Ionblade How to Deploy an AI Chatbot on an Ionblade GPU Server (Ollama + DeepSeek)

How to Deploy an AI Chatbot on an Ionblade GPU Server

(Ollama + DeepSeek) Introduction

Deploying your own AI chatbot has never been easier.

With Ionblade GPU servers, you get dedicated performance, full root access, and green-powered infrastructure. In this tutorial, we’ll show you how to set up Ollama and DeepSeek to run an AI chatbot in just a few steps.

Step 1: Choose the Right Ionblade GPU Server

Go to Ionblade AI Servers.
Select a GPU server that fits your AI workload:
- Recommended for LLMs: at least 1 NVIDIA GPU (e.g., RTX A6000 or similar)
- RAM: 32–64 GB
- Storage: NVMe SSD for fast read/write
Complete the checkout process and get your root SSH credentials.

Step 2: Connect to Your Server

Open a terminal (Linux/macOS) or PuTTY (Windows).
Connect via SSH:

ssh root@your-server-ip
Enter your root password provided by Ionblade.

Step 3: Prepare Your Server

Update your packages:

sudo apt update && sudo apt upgrade -y
Install Python, pip, and essential tools:

sudo apt install python3 python3-pip git -y
Optional: Create a virtual environment for your AI tools:

python3 -m venv ai-env
source ai-env/bin/activate

Step 4: Install Ollama

Clone or download Ollama (check the latest release):

git clone https://github.com/ollama/ollama.git
cd ollama
Install dependencies:

pip install -r requirements.txt
Start the Ollama server:

python server.py

Your Ollama instance should now be running on your server.

Step 5: Install DeepSeek

Clone DeepSeek repository:

git clone https://github.com/deepseek-ai/deepseek.git
cd deepseek
Install Python dependencies:

pip install -r requirements.txt
Run DeepSeek:

python app.py

DeepSeek will index your content and prepare it for querying via the chatbot.

Step 6: Connect Ollama + DeepSeek

In Ollama, point your model or queries to DeepSeek’s API.
Example:

from ollama import Ollama
client = Ollama(api_key="YOUR_API_KEY")
response = client.ask("What is Ionblade AI?")
print(response)
Test a few queries to make sure your AI chatbot is responding correctly.

Step 7: Secure Your Server

Create a non-root user for AI workloads.
Enable firewall (UFW):

sudo ufw allow ssh
sudo ufw allow 5000 # Ollama port
sudo ufw enable
Regularly update packages.

Step 8: Optional Enhancements

Add GPU monitoring with nvidia-smi.
Configure systemd service to auto-start Ollama and DeepSeek on boot.
Integrate with a front-end interface (web chat) or Slack/Discord bot.

Conclusion

In just a few steps, your AI chatbot is live on a dedicated Ionblade GPU server. You have full control, green-powered infrastructure, and the power to train or fine-tune models as needed.

Next steps:

Experiment with larger LLMs
Automate queries with your applications
Monitor GPU usage and performance