4 posts tagged with "soviet.recipes project"

An AMD Ryzen AI Max+ 395 laptop with its integrated Radeon 8060S GPU and unified memory can run open-weight models from 4B parameters up to a 120B mixture-of-experts model, no cloud GPU needed. gpt-oss-120b generates around 35-40 tokens per second, and the 20B and 4B models are faster still. That's enough for the soviet.recipes project: this hardware can host a model large enough to attempt vision-language OCR locally.

Docling already does most of what a batch text-extraction harness does: it iterates over documents, swaps OCR backends, handles per-document errors, and exports structured output. So the code worth writing for the soviet.recipes project is a thin pipeline around Docling that adds the three things Docling leaves to me: image preprocessing before extraction, a neutral slot for engines Docling does not wrap, and consistent scoring across every approach I test. So far I've built the engine slot and the batch loop that drives it; preprocessing and scoring are designed but not written yet.

Docling with the EasyOCR engine extracted the Cyrillic text and page structure from a scanned Soviet cookbook, but it dropped text where the pages curved away from the camera. That data loss makes this configuration insufficient on its own for the soviet.recipes project. I tested four sample pages configured for Russian and English, using Kiro.dev to write the script.

Phase 1 of the soviet.recipes project is done: every page of the cookbook is now captured as a set of 224 high-resolution DSLR images. Now I'm planning how to turn those images into machine-readable text.