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New · RAG on AWS Bedrock, end to end

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rag_query.py
# 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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7
Articles published
320
Total views
2
AWS certifications held
2
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