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Whether retrieval can work with images depends on the models you picked for the knowledge base. Start from what you want retrieval to do with images:
  • Text-to-image search: a text question finds images in the knowledge base by what they show. Pick a vision-capable embedding model. A question like “the org chart” can then match a diagram by what it shows, even if it has no caption or alt text.
  • Image-to-image search: an attached image finds visually similar images in the knowledge base. Pick a vision-capable embedding model, so similar images match even when they share no text.
  • Image-to-text search: an attached image finds relevant text chunks. Pick a vision-capable reasoning model. It describes the image in words and searches that description against text.
For all three, pick vision-capable models for both embedding and reasoning. Either model can be changed later under Settings > Retrieval, but changing it re-indexes every document and costs tokens.
After switching from two text-only models, click Re-index on each document that has images once the change finishes.

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How Models Affect Image Behavior

Captions and alt text on images in Markdown and HTML files are searchable regardless of model choice, so well-captioned sources improve image retrieval in every combination.
  • Text inside images in PDF files is read when either model accepts images.
  • Text inside images in Word, PowerPoint, and Excel files isn’t read, so put anything users will search for in the surrounding text.
Last modified on October 28, 2026