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Reply to u/noir_dreams - Ollama Support Available Now! 🎉

Hey u/noir_dreams!

You asked about Ollama support for local email classification and getting past API limits - great news, I just released a test version with exactly that!

Your Questions Answered

Ollama + Locally Sorted AI? ✅ Done!
Get past API limits/tickets? ✅ Completely unlimited - runs locally
Model flexibility (gemma, gpt-oss-20b, etc.)? ✅ Any Ollama model works!

Recommended Models for Email Classification

Based on testing, these work great:

  • tinyllama (~1GB) - Super fast, good for quick sorting
  • phi (~2.7GB) - Better accuracy, still reasonably fast
  • gemma (~2.5GB) - Solid balance of quality and speed
  • llama3.2 (~5GB) - High quality, best accuracy
  • qwen (~4GB) - Another solid option

All run locally on your machine with zero rate limits. Classify unlimited emails!

Setup (30 seconds)

  1. Install Ollama: https://ollama.com/download
  2. Pull your model: ollama pull gemma
  3. Download test XPI: AutoSort+ v1.2.3.1-ollama-test
  4. Open Thunderbird → Drag XPI into Add-ons page
  5. Settings → Provider: Ollama → Model: gemma
  6. Click "Test Connection"
  7. Done! Right-click emails → "Analyze with AI"

Why This is Cool

  • 🏠 100% Local - No data leaves your computer
  • 🆓 No API Keys or Limits - Classify as many emails as you want
  • 🔒 Privacy First - Your emails stay yours
  • 💪 Your Choice - Use any model: gemma, phi, tinyllama, llama3.2, qwen, etc.

If You Hit Issues

Check Ollama is running:

curl http://localhost:11434/api/tags

Should return your installed models

Enable debug mode:

  • Ctrl+Shift+J in Thunderbird
  • Look for [Ollama] messages during analysis
  • Post console errors in GitHub issues

Common fixes:

  • Make sure Ollama daemon is running
  • Pull the model first: ollama list
  • Check full debugging guide in release notes

This is a TEST Release

⚠️ Please test and report back! This is experimental but working. Uses a new tab injection approach to bypass Thunderbird's fetch restrictions.

Specifically looking for:

  • What model works best for your email?
  • Performance on your system?
  • Any bugs or errors?

Download: v1.2.3.1-ollama-test on GitHub
Full Guide: See release notes for detailed setup and debugging
Models Tested: tinyllama, phi, gemma, llama3.2, qwen

Looking forward to hearing your results! 🚀