feat: batch LLM OCR — multiple images in one API call + downscaling

Browse Source

- Add run_ocr_llm_batch() — sends N images in a single vision API call
  with structured JSON prompt, up to 20 images per batch
- Add _resize_for_llm() — downscales images to 1600px max dimension
  before sending to LLM, reducing per-image token cost
- Update bulk_process() to pre-read all files and batch-OCR in one call
- Graceful fallback: if batch JSON parsing fails, retries individually
- Frontend shows llm_batch engine badge

Without batch: N photos = N API calls (each with full prompt overhead)
With batch: N photos = ceil(N/20) API calls + image downscaling savings

...

This commit is contained in:

Shawn

2026-05-25 17:26:10 -04:00

parent 3a67070063

commit 70d8374ca6

3 changed files with 155 additions and 12 deletions

Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL

Download Patch File Download Diff File Expand all files Collapse all files

__pycache__/server.cpython-311.pyc

BIN

Binary file not shown.