datapipe

Use when asked to create, scaffold, or build a NEW datapipe pipeline or project (any size — plain ETL/ingest, ML training with metrics, LLM-processing steps, annotation loops, viewers/UI), usually in an empty directory outside the datapipe repo. Also when a user describes a recurring data-processing task ("files keep arriving and I need to...") and no pipeline exists yet.

Use when working in examples/ocr, or running / debugging the OCR→FiftyOne datapipe example (multi-LLM structured OCR on passport/id-doc images).

Use when working in the epoch8 datapipe repo with the examples/* folders, when asked to run or debug any datapipe example pipeline on your own data, or when unsure which example or setup skill applies.

Use when setting up or running examples/detection_tags — a self-contained datapipe detection demo built around tags (per-scenario metrics), split into two parts around a checkpoint (train a baseline, then add a tagged TRAIN batch and retrain, watching the tag metric rise), with a FiftyOne view and injected ground truth (no Label Studio). Also for "add a tagged batch, retrain, watch the tag metric rise" and for rehearsing that retraining demo from a saved checkpoint.

Use when setting up or running examples/e2e_template (image_detection or image_keypoints) — datapipe YOLO/Label Studio pipelines — or debugging their install, stages, training, or FiftyOne output.

Use when working in examples/embedder_fiftyone, or running / debugging the embedder→FiftyOne datapipe example (DINOv2/DINOv3 image embeddings, UMAP, similarity search).

Use when working in examples/sam_cvat, or when setting up / running / debugging the datapipe SAM3→CVAT pre-annotation example, on the cats-n-dogs demo data or on your own images.