ConceptsFlows

Edges

An edge decides when a node runs. It never carries data.

An edge is an arrow on the canvas. It means run the target after the source succeeds, and nothing else. Data reaches a node through its inputs, which can reference any other node’s output. If you’ve used n8n or a similar tool, where each arrow passes a payload to the next step, this is the part to unlearn.

val split val split as ground truth Train/val split Train detector Predict Evaluate

In this flow the arrows fix the order: split, train, predict, evaluate. The dotted lines are references, which aren’t drawn on the real canvas: Predict runs the new model on the validation split, and Evaluate compares its predictions with that same split as ground truth — neither is next to the node it reads the split from. Even the model Predict uses is a reference to the training node’s output. The arrow between them only says after.

Draw an edge by dragging from a handle on one node to another node. When a node’s run succeeds, OvalBee starts every node its outgoing flow edges point to, and each of those does the same when it succeeds. That chain is how work travels through a flow.

  • Branching. A node with several outgoing edges starts all of them.
  • Joining. A node with several incoming edges runs each time any of them finishes. When it should wait until all of its upstream branches are done, put a Wait node in front of it.
  • Failures stop the chain. A failed node doesn’t start anything downstream. Some nodes also end the chain on purpose when there’s nothing to do, for example when no new images arrived.
  • Loops are allowed. Rework cycles and retraining loops are normal. A loop keeps going until a node in it fails, stops the chain, or has nothing new to process.
  • Isolated runs ignore edges entirely. See Runs and automation.

Visual edges

A visual edge is drawn dashed and never starts anything. It exists for the reader: to show that rejected images go back to the pool, that two branches belong together, that a report is about a certain dataset.

Hold Alt while dragging to draw a visual edge, or right-click any edge and choose Convert to visual edge (and Convert to flow edge to turn it back).

The classic use is a rework loop. In a labeling flow, the path from Rejected back to the labeling pool is a visual edge: the drawing shows the loop, while a separate Move node returns the images when you run it or when its schedule comes due. The loop is visible, and it never spins by itself.

Edge labels

Double-click an edge, or right-click it and choose Edit edge label, to write a short label such as Accepted, Rejected or only if mAP improved. Labels are for people reading the flow and don’t change behavior.

Hover an edge to get a + button that inserts a new node in the middle of it.

  • References — how data actually gets from one node to another.
  • Runs and automation — manual, scheduled and isolated runs, and what happens downstream.
  • Flow editor — drawing, selecting and rearranging on the canvas.