Ran into an issue with the previous model for having mllama archetecture so I changed it
2.1 KiB
Getting Started With AI
StepForge keeps AI local. It talks to your own Ollama server on your machine and does not send guide content to the cloud.
1. Install Ollama
Install Ollama from https://ollama.com and make sure the service is running.
On most systems you can verify it with:
ollama --version
2. Pull a lightweight model
The recommended default is:
ollama pull llama3.2:1b
That model is small enough to feel responsive on modest hardware, but still good enough for human-sounding titles and short text blocks.
If you want StepForge to send the screenshot itself to the model, pull a vision-capable model instead:
ollama pull gemma3
That model can inspect pictures as well as text, so it is better when you want the AI to read the UI directly from the screenshot.
If you need something even smaller, try:
ollama pull qwen3:0.6b
or:
ollama pull gemma3:270m
Those are lighter, but they are usually weaker at writing polished step text.
3. Open StepForge settings
In StepForge, open Settings and find the AI section.
Set:
Enable AI text fillingto onOllama hostto your local Ollama serverOllama modeltollama3.2:1bfor text-only mode, orllama3.2-visionif you want screenshot-aware AI
The default host is:
http://127.0.0.1:11434
4. Test the connection
Use the Test connection button in the AI settings section.
If the model is installed, StepForge should confirm the host and model.
5. Use AI manually
AI is never automatic. After capture, use the AI button next to:
- the step title
- the step description
- each text, code, and table block
You can also use More -> Generate all text fields with AI to fill the whole step in one pass.
Notes
- Capture titles are still generated automatically without AI.
- AI generation only works when
Enable AI text fillingis turned on. - The app always uses local OCR around the click area first, then local AI only when you ask for it.
- When the selected Ollama model supports vision, StepForge also sends the screenshot to the model so it can cross-check OCR and visual context.