Indexatron

I have thousands of family photos. Finding specific ones is a nightmare. “That photo from the wedding with Uncle Dave” - good luck.

Cloud services can do this, but uploading family photos to third parties feels wrong. This experiment proves that locally-run LLMs can analyse photos with useful metadata extraction - no cloud required.

The hypothesis

Local LLMs can analyse family photos with useful metadata extraction.

Status: Confirmed.

The stack

• Runtime: Ollama
• Vision Model: LLaVA:7b (~4.7GB)
• Embeddings: nomic-embed-text (~274MB)
• Language: Python 3.11+ with pydantic, Pillow, Rich

What it does

Feed it a photo, get back:

• Subject identification (people, objects, brands)
• Scene categorisation
• Era estimation from visual cues
• 768-dimensional semantic embeddings for similarity search