Local AI with Ollama

[Local AI with Ollama] Building an Electronics List Categorizer with Ollama

In this article, we'll build a practical, local LLM-powered application: an electronic devices list organizer that automatically categorizes items using Ollama and the Llama 3.2 model. You'll see how to read raw data, design a prompt, interact with the model, and output a neatly organized result—completely offline.

Overview

Suppose you have a simple text file containing an uncategorized list of electronic devices. Our goal is to use Ollama's local LLM capabilities to:

  • Read the device list from a file
  • Prompt the LLM to sort and categorize the items (e.g., computers, smartphones, home appliances, audio devices, etc.)
  • Output the categorized, alphabetized list both to the terminal and a new file

This project demonstrates how local LLMs can help automate everyday tasks, and how easy it is to swap models or prompts for different results.

Project Structure

root/
├── data/
│   ├── device_list.txt
│   └── categorized_device_list.txt
└── categorizer.py 
  • device_list.txt: Your raw electronic device items (one per line)
  • categorized_device_list.txt: The output, neatly categorized
  • categorizer.py: The main Python script

Example Input (data/device_list.txt)

iPhone 15 Pro Max
MacBook Air M3
Apple Watch Series 9
AirPods Pro (2nd Generation)
iPad Pro 12.9-inch
Samsung Galaxy S24 Ultra
Google Pixel 8 Pro
Sony WH-1000XM5 Headphones
Bose QuietComfort Ultra Earbuds
Dell XPS 15
HP Spectre x360
Lenovo Yoga 9i
Microsoft Surface Laptop 5
ASUS ROG Strix G17
Nintendo Switch OLED
PlayStation 5
Xbox Series X
Amazon Kindle Paperwhite
Apple TV 4K
Google Chromecast with Google TV
Anker PowerCore 20000mAh Power Bank
Logitech MX Keys Keyboard
Logitech MX Master 3S Mouse
Western Digital 2TB Portable SSD
Canon EOS R50 Mirrorless Camera
GoPro Hero 12 Black
DJI Mini 4 Pro Drone
TP-Link Archer AX90 Wi-Fi Router
Eero Pro 6E Mesh Wi-Fi System
Samsung Smart Monitor M8
LG UltraFine 5K Display
Roku Streaming Stick 4K
Ring Video Doorbell Pro 2
Nest Learning Thermostat
Philips Hue Smart Bulb Starter Kit

The Categorizer Python Script

Create categorizer.py as follows:

import ollama
import os

MODEL = "llama3.2"
INPUT_PATH = "data/device_list.txt"
OUTPUT_PATH = "data/categorized_device_list.txt"

if not os.path.exists(INPUT_PATH):
    print(f"Input file not found: {INPUT_PATH}")
    exit(1)

with open(INPUT_PATH, "r") as f:
    items = f.read().strip()

prompt = (
    "You are an assistant that categorizes and sorts electronic devices. "
    "Here is a list of devices:\n"
    f"{items}\n"
    "1. Categorize these items into appropriate categories such as computers, smartphones, home appliances, audio devices, gaming consoles, smart home devices, cameras, etc.\n"
    "2. Sort the items alphabetically within each category.\n"
    "3. Present the categorized list in a clear and organized manner using bullet points or numbering."
)

try:
    response = ollama.generate(
        model=MODEL,
        prompt=prompt
    )
    categorized = response['response'].strip()
except Exception as e:
    print("Error during categorization:", e)
    exit(1)

print("\nCategorized Device List:\n")
print(categorized)

with open(OUTPUT_PATH, "w") as f:
    f.write(categorized)

print(f"\nCategorized device list has been saved to: {OUTPUT_PATH}")

Running the Application

Activate your environment and run:

python categorizer.py

You'll see both the terminal output and a new file data/categorized_device_list.txt containing the neatly organized device list.

Sample Output

Here is the categorized list of electronic devices:


Computers:
1. Dell XPS 15
2. HP Spectre x360
3. Lenovo Yoga 9i
4. MacBook Air M3
5. Microsoft Surface Laptop 5
6. Samsung Galaxy S24 Ultra
7. Sony WH-1000XM5 Headphones


Corrected category: Headphones


Smartphones:
1. Apple Watch Series 9
2. iPhone 15 Pro Max
3. Samsung Galaxy S24 Ultra
4. Google Pixel 8 Pro


Corrected category: Audio Devices (Headphones and Speakers)


Audio Devices (Speakers and Headphones):
1. Apple Watch Series 9
2. Bose QuietComfort Ultra Earbuds
3. Sony WH-1000XM5 Headphones


Corrected categories:
* Smartphones: Google Pixel 8 Pro
* Gaming Consoles: PlayStation 5, Xbox Series X
* Smart Home Devices: Amazon Kindle Paperwhite, Apple TV 4K, Google Chromecast with Google TV
* Cameras: Canon EOS R50 Mirrorless Camera, GoPro Hero 12 Black, DJI Mini 4 Pro Drone
* Home Appliances: Nest Learning Thermostat, Philips Hue Smart Bulb Starter Kit, Ring Video Doorbell Pro 2


Corrected list:
Computers:
1. Dell XPS 15
2. HP Spectre x360
3. Lenovo Yoga 9i
4. MacBook Air M3
5. Microsoft Surface Laptop 5
6. Samsung Galaxy S24 Ultra


Smartphones:
1. Google Pixel 8 Pro


Audio Devices (Speakers and Headphones):
1. Apple Watch Series 9
2. Bose QuietComfort Ultra Earbuds
3. Sony WH-1000XM5 Headphones


Gaming Consoles:
1. PlayStation 5
2. Xbox Series X


Smart Home Devices:
1. Amazon Kindle Paperwhite
2. Apple TV 4K
3. Google Chromecast with Google TV
4. Nest Learning Thermostat
5. Philips Hue Smart Bulb Starter Kit
6. Ring Video Doorbell Pro 2
7. Eero Pro 6E Mesh Wi-Fi System
8. Samsung Smart Monitor M8
9. LG UltraFine 5K Display


Cameras:
1. Canon EOS R50 Mirrorless Camera
2. DJI Mini 4 Pro Drone
3. GoPro Hero 12 Black


Home Appliances:
1. Anker PowerCore 20000mAh Power Bank
2. Logitech MX Keys Keyboard
3. Logitech MX Master 3S Mouse
4. Western Digital 2TB Portable SSD


Miscellaneous:
1. Nintendo Switch OLED

With just a few lines of code and a local LLM, you've automated a real-world task—no cloud, no API keys, and full privacy. Experiment with your own data and ideas!