New · RAG on AWS Bedrock, end to end
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# Ground an LLM in your own docs on AWS
import boto3
bedrock = boto3.client("bedrock-agent-runtime")
answer = bedrock.retrieve_and_generate(
input={"text": question},
knowledgeBaseId="KB-WORDWYZZ",
model="anthropic.claude",
)
print(answer["output"]["text"])
# → cited, grounded, production-ready
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