Haiper Image to Video

Haiper Image to Video takes one of your images and turns it into a short animated clip. The catch, and it's a good catch: the animation happens on Haiper's servers, not your machine. You hand them an image plus a prompt, they run their video model in the cloud, and the node downloads the finished MP4 to a local path. If you're on a laptop with 8GB of VRAM or just don't want to babysit a Wan install, this is the low-friction way to get image-to-video out of ComfyUI.

It's the official pack from Haiper itself (announced on r/comfyui in late 2024), which matters more than it usually does: custom nodes execute arbitrary Python on import, and the community has been burned by that. A vendor-signed pack you can trace back to the company's own repo is a different trust class than a random wrapper.

How it works

The node is thin - there's almost nothing local happening. It base64-encodes the first image in your source_image batch, POSTs it with your prompt to Haiper's image2video endpoint, then polls job status every 20 seconds and updates ComfyUI's progress bar. When the job reports succeed, it asks for a watermark-free URL and downloads the MP4.

That means two practical realities. First, your queue is busy for the whole generation - usually one to a few minutes - so plan around blocking. Second, the output is not a video tensor and it doesn't land in ComfyUI's output folder. The single output, output_video_path, is a STRING pointing at a file in a temp directory (/tmp/<random>/output-i2v.mp4). You'll wire it into VHS_LoadVideoPath from ComfyUI-VideoHelperSuite to actually see it, and into VHS_VideoCombine if you want it saved somewhere that survives a reboot. The pack's own example workflows show exactly this wiring.

The inputs that matter

You must set exactly two things:

• source_image (IMAGE) - your starting frame. Only the first image in a batch is used, so don't feed a batch expecting four videos.
• prompt - what happens in the clip, e.g. she is dancing.

Everything else is optional, and the defaults are sensible:

• duration - 1 to 6 seconds in the widget, but 4 and 6 are what the API actually documents. Video is billed per second, so this is also your cost dial.
• guidance_scale - the "under-the-hood" setting the author highlighted. Default 50, steps of 10. Higher = closer to your prompt, lower = more freedom for the motion model.
• seed - -1 means random; set a number to reproduce a result.
• resolution - 720 by default (540 and 720 are the priced tiers).
• is_public - defaults to False, and that's worth appreciating: Haiper's own API defaults to public, but this node keeps generations private to your account.
• is_enable_prompt_enhancer - an AI prompt-rewrite toggle. Note it defaults to off here, unlike the text nodes in this pack.

Install

Grab the API key first - you need one from haiper.ai/haiper-api, and Haiper requires you to top up prepaid credits before the API will accept anything. Then install the pack:

cd ComfyUI/custom_nodes
git clone https://github.com/Haiper-ai/ComfyUI-HaiperAI-API.git
cd ComfyUI-HaiperAI-API
pip install -r requirements.txt

Then edit the .env file in that folder (it ships with a placeholder key), set HAIPER_KEY=your_real_key, and restart ComfyUI. The key is read when the node module loads, so a restart is mandatory, not optional. No models to download - that's the whole point.

ComfyUI Manager works too: search for "Haiper" or "ComfyUI-HaiperAI-API". Fair warning, the README tells you to search "ComfyUI-HaiperAI-AP" and that string is missing a letter, so if Manager finds nothing, that's why.

Common issues

The failure mode beginners actually hit is a 401-style rejection right after setup - 99 times out of 100 the .env key is a placeholder, wasn't saved, or ComfyUI wasn't restarted. Missing or insufficient credits produces the same symptoms. And remember the temp-directory thing: reboot your machine and your "saved" video is gone. If you like a result, pipe it through VHS_VideoCombine before the OS cleans up after you.