Image to Video API

The flow embedded on this page is a working image-to-video pipeline, not a diagram. A sticky note explains the run. An Image Prompt input carries the description of the starting still, and a Motion Prompt input carries the camera and movement direction. The Source Frame node renders the still with Nano Banana Lite, and that image output is wired straight into the Animate Clip node.

Animate Clip is a Kling Video image-to-video node. It takes the rendered frame plus the motion prompt and produces the clip. In the preview it is left unexecuted on purpose, because video nodes are billed per run and are never auto-run in an embedded flow. Publish the graph and every node becomes callable as one hosted endpoint, the same shape as a Hailuo API call.

Most image-to-video APIs assume you already have the still. That means two systems: one to generate the image, one to animate it, plus the plumbing to move a file between them. Here the Source Frame render and the Animate Clip node sit on the same canvas, wired output to input, so a single published call creates the frame and hands it straight to the video model.

Because the model is just a node, you can point Animate Clip at any hosted image-to-video model and keep the request identical. That is the same reason teams reach for a chain models pattern or a batch bulk video ad API: loop one endpoint over a feed of frames instead of gluing SDKs together. It sits a step past a plain text to video call, because you control the exact starting image.

Wireflow is the generation layer, not the creative brain. It animates the frame you describe, but it does not decide the motion direction or judge which shot is on brand. The clips are short, a few seconds per generation, not full edited sequences. Assembling several clips with captions or audio is a separate Compose Video step, not part of this single-clip flow.

It also does not host every model on the market, so the swap list is only the image-to-video models Wireflow actually runs, not whatever a competitor offers. There are no local or offline runs and no custom Python nodes. If you need one clip once, the canvas UI is faster than wiring an integration. The API pays off when the same image-to-video step runs again and again, the way a video API for coding agents is meant to.