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Additional controls

Update progress

Progress updates can be sent out from your worker while a job is in progress. Progress updates will be available when the status is polled. To send an update, call the runpod.serverless.progress_update function with your job and context of your update.

import runpod

def handler(job):
for update_number in range(0, 3):
runpod.serverless.progress_update(job, f"Update {update_number}/3")

return "done"

runpod.serverless.start({"handler": handler})

Refresh Worker

When completing long-running job requests or complicated requests that involve a lot of reading and writing files, starting with a fresh worker can be beneficial each time. A flag can be returned with the resulting job output to stop and refresh the used worker.

This behavior is achieved by doing the following within your worker:

# Requires runpod python version 0.9.0+
import runpod
import time

def sync_handler(job):
job_input = job["input"] # Access the input from the request.

results = []
for i in range(5):
# Generate a synchronous output token
output = f"Generated sync token output {i}"

# Simulate a synchronous task, such as processing time for a large language model

# Return the results and indicate the worker should be refreshed
return {"refresh_worker": True, "job_results": results}

# Configure and start the RunPod serverless function
"handler": sync_handler, # Required: Specify the sync handler
"return_aggregate_stream": True, # Optional: Aggregate results are accessible via /run endpoint

Your handler must return a dictionary that contains the refresh_worker: this flag will be removed before the remaining job output is returned.


Refreshing a worker does not impact billing or count for/against your min, max, and warmed workers. It simply "resets" that worker at the end of a job.