Pause AI workflow for human approval before continuing using AWS Lambda durable functions
This pattern demonstrates human-in-the-loop workflows with AWS Lambda durable functions. The workflow suspends execution while awaiting human review without consuming compute resources.
The example extracts fields from a document using an LLM, then waits for human approval before proceeding.
Benefits: Pay only for active compute time, not wait periods. Workflows can suspend for up to one year. No infrastructure to manage while waiting for human input.
Select language:
Usage Example with Python:
Human review workflow with Lambda durable functions using Python.
import json
import boto3
from aws_durable_execution_sdk_python import DurableContext, durable_execution
from aws_durable_execution_sdk_python.config import Duration, WaitForCallbackConfig
from pydantic import BaseModel
MODEL_ID = "us.amazon.nova-pro-v1:0"
bedrock = boto3.client("bedrock-runtime")
def converse(model_id: str, prompt: str) -> str:
response = bedrock.converse(
modelId=model_id,
messages=[{"role": "user", "content": [{"text": prompt}]}],
)
return response["output"]["message"]["content"][0]["text"]
class ReviewResult(BaseModel):
approved: bool
notes: str | None = None
def send_for_review(callback_id: str, document: str, extracted_fields: str):
print(f"Review needed for document. Callback ID: {callback_id}")
print(f"Extracted fields: {extracted_fields}")
@durable_execution
def handler(event: dict, context: DurableContext):
document = event.get("document", "Sample invoice with amount $1,234.56")
extracted_fields = context.step(
lambda _: converse(
MODEL_ID,
f'Extract key fields from this document as JSON: "{document}"',
),
"extract fields",
)
review_result_str = context.wait_for_callback(
lambda callback_id, _: send_for_review(callback_id, document, extracted_fields),
"Await Human review",
WaitForCallbackConfig(timeout=Duration.from_days(7)),
)
review_result = ReviewResult(**json.loads(review_result_str))
if not review_result.approved:
return {
"status": "rejected",
"notes": review_result.notes,
"extractedFields": extracted_fields,
}
return {"status": "approved", "extractedFields": extracted_fields}
Created by:
