Daily
Generate fresh model output every morning
Each day a new result from the model and prompt you chose lands in your inbox as a link.
- Runs
- Daily
- Apps
- Replicate
- AI
- Not needed
- Access
- API key
Send this to your assistant
Create a ClickRuntime automation: every day at 8am, run black-forest-labs/flux-schnell on Replicate with the prompt "a calm watercolor landscape, morning light" and email me the image link.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
People who use Replicate to generate images, music or short videos often want something fresh on a routine: a daily image for a newsletter header, a morning social media graphic, a prompt they like to run each day to see how a model behaves. Doing it manually means opening the site, pasting the prompt, waiting and saving the result, which turns a good idea into a chore.
Every morning at the time you choose, ClickRuntime starts a Replicate prediction with your prompt and the model you picked. It asks Replicate to wait for the result and checks again if the job is not done, then emails you a link to the generated output so it is waiting in your inbox when you start work.
Creators, marketers and hobbyists with a repeating creative task will find it saves the same small effort every day.
What you get out of it
Fresh creative material every day
An image or clip arrives without you having to remember to ask. For a daily newsletter or a content calendar, that removes the blank-page moment from the start of the day.
Model behavior can be tracked
Running the same prompt daily shows how a model performs over time, and when its version changes. People who care about output quality can notice a drift or an improvement early.
Your prompt is saved and reused
Once the prompt works well, it runs the same way every time. You avoid rewriting it, losing track of the version that gave the best results, or changing it by accident.
Cost stays predictable
One prediction per day is easy to budget for. You know your spend on this task in advance, and you can switch to a cheaper model if the numbers add up.
Output reaches you where you work
The email contains the link, so the image can go straight into a draft or a chat. There is no extra visit to the Replicate website to download the file.
How it works
What happens, step by step
Every morning, ClickRuntime sends your saved prompt, such as a calm watercolor landscape, to the image model you chose on Replicate.
It waits for Replicate to finish the image.
You get an email with the prompt and a link to today's image. If the run fails, the email gives the error instead.
Before it runs live
- Connect Replicate
What you get
Build your own
Need it to work differently?
Your own rules
Conditions, thresholds, filters and exceptions, written the way you'd explain them to a colleague.
Any number of apps
One automation can read from one app and update several others. Over 248 apps are ready, and anything with an API works too.
AI where it helps
Summaries, classification, extraction and drafts use ClickRuntime's built-in AI, with no extra key.
On a schedule or on each event
Runs as often as every 5 minutes, or the moment an app sends an event, and keeps track of what it already handled.
Changes you can ask for
- Run it at a different time, more or less often, or only on weekdays
- Add an AI step, for example to summarize, sort or draft a reply
- Add another app, for example also send it to Slack
- Combine it with other Replicate steps into one automation
Under the hood
The code that runs this automation
import time
from clickruntime import on_trigger, credentials, notify, http
PROMPT = "a calm watercolor landscape, morning light"
@on_trigger
def run(event):
headers = {"Authorization": f"Bearer {credentials.secret('REPLICATE_API_TOKEN')}", "Prefer": "wait"}
p = http.post("https://api.replicate.com/v1/models/black-forest-labs/flux-schnell/predictions",
headers=headers, json={"input": {"prompt": PROMPT}}, timeout=70).json()
while p["status"] in ("starting", "processing"):
time.sleep(3)
p = http.get(p["urls"]["get"], headers=headers).json()
if p["status"] != "succeeded":
notify.email_me("Replicate run failed", f"{p['id']}: {p.get('error')}")
return {"status": p["status"]}
notify.email_me("Today's image", f"{PROMPT}\n{p['output'][0]}")
return {"image": p["output"][0]}FAQ
Common questions
Does it wait for the image to finish generating?
Can the prompt change each day?
How long are the generated files available?
What permissions does it need?
Does it need AI?
How many runs does it use?
Can I change how it works?
Related
You might also like
Get a daily list of failed predictions
Each morning you see which runs failed in the past day, which model they used and the error, so you can fix them before rerunning.
See how it worksHear when a Replicate job finishes or fails
As soon as a long prediction completes, you get its status and output link in Slack, with no repeat alerts.
See how it worksKnow the moment your website goes down
Your team hears in Slack when the site stops responding or slows down, and again when it's back.
See how it worksKeep exploring
Set up “Generate fresh model output every morning” from your assistant
Copy the prompt above, or connect your assistant first. Free plan, no credit card.