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Using Local Models with Sortio
Learn how to set up Ollama for local AI models with Sortio.
Installing Ollama
Sortio uses Ollama to run AI models locally on your computer. Follow these steps to install Ollama:
Installation Options
Download Ollama
Visit ollama.com/download and select your platform (macOS, Windows, or Linux)
Install and Run
Follow the installation instructions for your operating system
Verify Installation
Once installed, Ollama will run in the background ready to serve models
Installing a Model
After installing Ollama, you'll need to download a model. Choose one based on your computer's capabilities:
Recommended: Llama 3.3 or Deepseek-r1
Best performance for most file organization tasks
$ ollama pull llama3.3Alternative: DeepSeek
Another excellent option for file organization
$ ollama pull deepseekFor Limited Resources
If your computer has less RAM or processing power
$ ollama pull llama3.2Using with Sortio
Once you've installed Ollama and a model, connecting it with Sortio is simple:
Start Ollama
Ensure Ollama is running in the background on your computer
Open Settings
Go to Sortio's Settings menu and navigate to the AI Models section
Select Model
Choose your installed model from the dropdown menu
Enhanced Privacy
Using local models ensures your files never leave your computer. All AI processing happens locally, providing complete privacy and offline functionality.
Performance & Reliability
Sortio includes several features to ensure local model processing is fast and reliable:
Intelligent Batching
When sorting large numbers of files, Sortio automatically batches requests to your local model. This optimizes memory usage and ensures consistent performance even with hundreds of files.
Automatic Retry Logic
If a request to Ollama fails due to a temporary issue (network hiccup, model busy, etc.), Sortio automatically retries with exponential backoff. This makes sorting more resilient without requiring manual intervention.
Clear Error Messages
When something goes wrong, Sortio provides actionable error messages that help you understand the issue. Whether Ollama isn't running, the model isn't loaded, or there's a configuration problem, you'll know exactly what to fix.
Tip: Model Performance
For the best balance of speed and accuracy, we recommend llama3.3 or deepseek-r1 models. If you're sorting very large batches of files, smaller models like llama3.2 may complete faster while still providing good results.
Troubleshooting Local Models
If you're experiencing issues with local models, use these diagnostic commands to identify and solve the problem.
Diagnostic Commands
Run these commands in your Terminal (macOS/Linux) or Command Prompt (Windows) to check if Ollama is working correctly.
1
Check if Ollama is Running
$ curl http://localhost:11434/api/tagsSuccess: Returns JSON with your installed models
Failed: "Connection refused" means Ollama isn't running
2
List Installed Models
$ ollama listSuccess: Shows table of installed models with sizes
Empty: No models installed - run ollama pull llama3.2
3
Test Model Response
$ ollama run llama3.2 "Say hello"Success: Model responds with a greeting
Failed: Model may need to be re-downloaded
4
Start Ollama (if not running)
$ ollama serveThis starts the Ollama server. Keep this terminal window open, or use the Ollama app which runs in the background.
Hardware Requirements
- Memory: 8GB RAM minimum, 16GB+ recommended for larger models
- GPU: Dedicated GPU recommended for optimal performance
- Storage: At least 10GB free space for model files
- CPU: Modern multi-core processor (4+ cores recommended)
- 8GB RAM: llama3.2:1b, llama3.2:3b, deepseek-r1:1.5b
- 16GB RAM: llama3.2, deepseek-r1:8b
- 24GB+ VRAM: llama3.3:70b, deepseek-r1:70b
Common Issues
The diagnostic tool above can help identify common issues. Here are additional troubleshooting steps for specific problems:
- Ollama not starting: Check your system resources; Ollama requires at least 8GB of RAM to function properly.
- Very slow responses: Your model may be too large for your hardware. Try a smaller model like "llama3:8b" instead.
- Permission errors: Make sure Sortio has network permissions to access localhost in your system's security settings.
Still Having Issues?
If you're still experiencing problems after running diagnostics and following the troubleshooting steps, contact our support team at marcus@getsortio.com.