Run multiple LLM prompts simultaneously with individual checkpointing using AWS Lambda durable functions
This pattern demonstrates parallel invocation with AWS Lambda durable functions. Multiple LLM calls execute concurrently, with each response checkpointed independently.
The example sends multiple prompts about a topic in parallel, gathering different perspectives simultaneously.
Benefits: Faster execution through concurrent LLM calls. Individual checkpointing means partial failures don't require re-running successful calls. Automatic retry handling for each parallel operation.
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Usage Example with Python:
Parallel invocation with Lambda durable functions using Python.
import boto3
from aws_durable_execution_sdk_python import DurableContext, durable_execution
MODEL_ID = "us.amazon.nova-lite-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"]
PROMPTS = [
"Explain the benefits of",
"Describe the challenges of",
"Summarize the future of",
]
@durable_execution
def handler(event: dict, context: DurableContext):
topic = event.get("topic", "artificial intelligence")
result = context.map(
PROMPTS,
lambda ctx, prompt, idx, items: {
"prompt": prompt,
"response": converse(MODEL_ID, f"{prompt} {topic}"),
},
"Get perspectives",
)
return {"topic": topic, "perspectives": result.get_results()}
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