cookbook/data_labeling/_06_image_classification/TEST_LOG.md
Tested 2026-07-18 against gemini-3.5-flash, agno 2.7.4.
Status: PASS
Description: Single-label scene-type classification with a Literal output schema (wildlife / landscape / sports / architecture / other) over four image URLs: a Google generative-AI wildlife sample, two gstatic webp gallery photos, and the agno-public Krakow basilica photo.
Result: All four images classified as expected: elephants/giraffes/zebras sunset -> wildlife, gstatic gallery/1.jpg -> landscape, gstatic gallery/2.jpg -> sports, krakow_mariacki.jpg -> architecture. Each run returned a validated Classification object; per-image latency 1.2-3.2s.
Status: PASS
Description: Multi-label scene tagging with a List[Literal] output schema over eight possible tags (outdoor, indoor, daytime, nighttime, people, vehicle, nature, architecture) on the Krakow basilica photo and the Google generative-AI wildlife sample.
Result: krakow_mariacki.jpg -> ['outdoor', 'nighttime', 'architecture']; elephants/giraffes/zebras sunset -> ['outdoor', 'daytime', 'nature']. Both tag sets coherent with image content; each run returned a validated Tagging object; per-image latency 2.8-5.6s.