Composable Workflows

Every ImagePipeline endpoint is an independent primitive. They share the same async job model and accept each other's result_url as input, so you can chain them in any order.

Common pipelines

Workflow	Steps
Identity	Generate → Lock → Try-on → Animate
Content	Generate → Faceswap → Background → Upscale
Brand	Generate → Background → Branding → Upscale

Chaining pattern

Each step waits for the previous job to complete, then feeds its result_url into the next request.

import os, time, requests

API = "https://api.imagepipeline.io"
H = {"X-API-Key": os.environ["IMAGEPIPELINE_API_KEY"]}

def run(endpoint, body):
    job = requests.post(f"{API}/{endpoint}", json=body, headers=H).json()
    jid = job["job_id"]
    while True:
        s = requests.get(f"{API}/{endpoint}/status/{jid}", headers=H).json()
        if s["status"] in ("completed", "failed", "cancelled"):
            if s["status"] != "completed":
                raise RuntimeError(s.get("error", s["status"]))
            return s["result_url"]
        time.sleep(1.5)

# Generate → Background → Upscale
img   = run("generate/image/v1",        {"prompt": "product on a plain table"})
staged = run("background/change/image/v1", {"input_image": img, "prompt": "marble kitchen counter"})
final = run("upscale/image/v1",         {"input_image": staged, "width": 2048, "height": 2048})
print(final)

tip

For long chains in production, use webhooks and a small state machine instead of blocking polls — each step kicks off the next on callback.