Why You Should Set Up Your Own Local AI Chatbot
AI chatbots have become increasingly popular, enabling human-like conversations to answer questions, offer advice, or assist with tasks. However, sharing sensitive information like personal details, health concerns, or financial data with cloud-based services can pose privacy risks.
Why You Should Run Your Own Local AI
Cloud-based AI chatbots like ChatGPT or Google Gemini are convenient but store your conversations on their servers and using them to train models and create user profiles for advertising. They can also face downtime, disrupting access. A local AI keeps your data private on your device, offering full control without relying on internet connections or external servers.
| Pros | Cons |
|---|---|
| Enhanced privacy—no data leaves your device | Requires decent hardware (e.g., a GPU) for faster performance |
| Works offline after initial setup | Large model downloads (several GBs) |
| Free to use (open-source models) | Setup can be technical for beginners |
| Full control over models and data | Models may not be as advanced as proprietary models like GPT-5 |
Setting Up Your Own Local AI With Ollama
Ollama is a user-friendly tool that allows you to run large language models (LLMs) locally on your computer. It’s available for macOS, Linux, and Windows, making it accessible for most users. Here’s a step-by-step guide to get started.
Step 1: Download and Install Ollama
- macOS: Visit ollama.com/download and download the macOS installer. It requires macOS 12 (Monterey) or later.
- Linux: Open your terminal and run:
curl -fsSL https://ollama.com/install.sh | sh. - Windows: Visit ollama.com/download and download the Windows installer. It requires Windows 10 or later.
After installation, open a terminal and type ollama to verify it’s working.
Step 2: Launch Your First Model
Ollama makes it easy to download and run models from its library. Start with a lightweight model like DeepSeek R1 for testing.
In your terminal, run:
ollama run deepseek-r1:8bThis command downloads the 8 billion parameter variant model (about 5 GB) and starts an interactive chat session. You can now type questions and get responses directly in the terminal.
You can find other models at ollama.com/models, such as GPT-OSS or Gemma.
Step 3: Set Up a GUI for Ollama
While the terminal interface is functional, a graphical user interface (GUI) makes the experience more like ChatGPT. One of the best options is Open WebUI, a web-based interface that supports Ollama.
To install Open WebUI (Docker Method):
- Install Docker if you don’t have it.
- Run this command in your terminal:
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main - Ensure Ollama is running in the background, if it isn’t run
ollama serve. - Open your browser and go to
http://localhost:3000and you’ll have a nice chat interface. - In Open WebUI, you can pull models from Ollama’s library and switch between them easily.
If you prefer a non-Docker install, look here.
Using Privacy-Focused AI on Low-Power Devices
If your computer lacks the storage or GPU power for running AI models locally, or you’re on a mobile device, we recommend using an online privacy-focused AI chatbot like Duck.ai, which offers:
- Anonymous access to models like Claude 3.5, GPT-5 mini, or Mistral.
- No chat storage by DuckDuckGo or model providers.
- No data used for AI training.