roboflow

Author a new Roboflow Workflows block under `inference/core/workflows/core_steps/**`. Trigger on a new/changed `vN.py` or `vN_tensor.py` defining a `WorkflowBlockManifest` + `WorkflowBlock` pair; new `load_blocks()`/`KINDS_SERIALIZERS` entries in…

Load when a diff shows — (1) new/changed runtime code under inference/, inference_models/, inference_sdk/, inference_cli/ with no companion test (or a test that mocks the changed thing); (2) a new @pytest.mark.skipif/skip/slow or env-gated test (SKIP_*_TESTS,…

PRs touching inference/core/ foundation — inference/core/env.py, inference/core/version.py, inference/core/entities/**, inference/core/utils/** (image_utils.py, requests.py, environment.py), inference/core/roboflow_api.py, exceptions.py, logger.py, nms.py.…

Load when a diff touches `sv_detections_to_root_coordinates`, `scale_sv_detections`, `move_boxes`/`move_masks`, `POLYGON_KEY_IN_SV_DETECTIONS`, `add_inference_keypoints_to_sv_detections`, `serialise_sv_detections`, `mask_to_polygon`,…

Review PRs touching inference/core/workflows/core_steps/** (Workflow blocks — {category}/{block}/vN.py, common/, common/query_language/**, loader.py) or inference/core/workflows/execution_engine/entities/types.py (new kind). Diff signals — new block package,…

Review guidance for PRs touching inference/core/workflows/execution_engine/**, inference/core/workflows/errors.py, inference/core/workflows/prototypes/block.py, or .cursor/rules/execution-engine-version-changelog.mdc. Diff signals:…

Load when a PR changes a user/dev-visible contract or is release-bound. Triggers on diffs to `inference/core/version.py`, `EXECUTION_ENGINE_V1_VERSION`, `inference/core/interfaces/http/http_api.py` or `inference/core/entities/**`, a Workflow block manifest…

Trigger when the user asks to "add a model", "add a core / pre-trained model", "port a model from HuggingFace", "wrap a transformers model", or "expose X as a workflow block / model". Also when a diff adds a subfolder under…

Use when training Roboflow models, improving accuracy, or setting up a production feedback loop — covers architecture selection, model IDs, checkpoints, evaluation metrics, the iterative improvement playbook, and Active Learning through the Project Model…

Use when uploading locally trained model weights (YOLO, RF-DETR, YOLO-NAS, PaliGemma, Florence-2) to Roboflow — the client-side Python SDK upload flow, safe API key handling, per-family packaging requirements, and verifying the upload.

Use when connecting cloud storage (AWS S3 / S3-compatible or Google Cloud Storage) to Roboflow to mirror images into a workspace — creating storage credentials, defining datasources (bucket-mirror configs), selecting objects with glob rules, validating…

Use when uploading images, labeling, organizing datasets, creating Roboflow projects (detection/segmentation/keypoint/classification), tags, splits, versions, or RoboQL search.

Use when explaining where Roboflow features live in the app.roboflow.com web app, mapping intents like upload, annotate, train, deploy to specific page URLs.

Protocol-level facts for Roboflow REST and Inference APIs — URL patterns, auth, parameters, error codes, and SDK quick-start. For deployment strategy and Workflow execution patterns, see roboflow-inference.

Deployment option comparison (serverless, dedicated, self-hosted, batch) and Workflow execution patterns. For raw API URL patterns, auth, and request/response formats, see roboflow-api-reference.

Use when searching for or using public datasets/models on Roboflow Universe (universe.roboflow.com), the open repository of 1M+ computer vision datasets and 50K+ pre-trained models.