Downloaded 55 times
![xebia.com
Content generation
boto3_bedrock = boto3.client('bedrock-runtime')
response = boto3_bedrock.invoke_model(
body = '{"inputText": "Create short email from John Smith to SuperHotels requesting for special offers of hotels in San Francisco."}',
modelId = 'amazon.titan-tg1-large'
)
response_body = json.loads(response.get('body').read())
print(response_body.get('results')[0].get('outputText'))
Dear SuperHotels,
I hope this email finds you well. I am reaching out to inquire about any special offers or discounts available at your hotels in
San Francisco. As a frequent traveler, I value quality accommodations and great value. I would be delighted to learn about
any current promotions or packages that you have to offer.
Thank you for your attention to this matter.
I look forward to hearing back from you soon.
Best regards,
John Smith](https://image.slidesharecdn.com/bedrockinactionslideshare-240411181624-366965c4/75/Amazon-Bedrock-in-Action-presentation-of-the-Bedrock-s-capabilities-7-2048.jpg)
![xebia.com
Agents
client = boto3.client('bedrock-agent-runtime’)
response = client.invoke_agent(
agentAliasId='AJJCWRSIB2',
agentId='3LZHTSX13Q',
inputText='Can you show the offers list?',
sessionId='abc123’
)
completion = ""
for event in response.get("completion"):
chunk = event["chunk"]
completion = completion + chunk["bytes"].decode()
Here are the available destinations/offers:
- Egypt, Hurghada
- Italy, Venice
- Mexico, Cancun](https://image.slidesharecdn.com/bedrockinactionslideshare-240411181624-366965c4/75/Amazon-Bedrock-in-Action-presentation-of-the-Bedrock-s-capabilities-19-2048.jpg)
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Similar to Amazon Bedrock in Action - presentation of the Bedrock's capabilities
Amazon Bedrock in Action - presentation of the Bedrock's capabilities
- 2. xebia.com Amazon Bedrock inAction Krzysztof Kąkol Chief of Data Engineering @ Xebia Poland
- 3. xebia.com Krzysztof Kąkol Chief ofData Engineering and Solutions Architect in Xebia Poland AWS Community Builder & AWS Ambassador https://www.linkedin.com/in/krzysztofkakol/ Other stuff: Classical and jazz pianist PhD in AI-driven sound processing
- 4. xebia.com Access a rangeof leading FMs through a single API Extend the power of LLMs with your data using retrieval augmented generation (RAG) Privately customize FMs with your own data Amazon Bedrock Build agents that execute complex business tasks by dynamically invoking APIs Get the best price performance without managing infrastructure Enable data security and compliance
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- 7. xebia.com Content generation boto3_bedrock =boto3.client('bedrock-runtime') response = boto3_bedrock.invoke_model( body = '{"inputText": "Create short email from John Smith to SuperHotels requesting for special offers of hotels in San Francisco."}', modelId = 'amazon.titan-tg1-large' ) response_body = json.loads(response.get('body').read()) print(response_body.get('results')[0].get('outputText')) Dear SuperHotels, I hope this email finds you well. I am reaching out to inquire about any special offers or discounts available at your hotels in San Francisco. As a frequent traveler, I value quality accommodations and great value. I would be delighted to learn about any current promotions or packages that you have to offer. Thank you for your attention to this matter. I look forward to hearing back from you soon. Best regards, John Smith
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- 14. xebia.com Retrieval Augmented Generation client= boto3.client('bedrock-agent-runtime’) response = client.retrieve_and_generate( input={ 'text’:”Who is Andy Dufresne?”, }, retrieveAndGenerateConfiguration={ 'type': 'KNOWLEDGE_BASE', 'knowledgeBaseConfiguration': { 'knowledgeBaseId': ’ABC12345', 'modelArn': 'arn:aws:bedrock:us-east-1::foundation-model/anthropic.claude-v2' } }, ) "output": { "text": ”...”}, "citations": [{ "generatedResponsePart": { "textResponsePart": { "text": ”...", "span": { "start": 0, "end": 198 } } }, "retrievedReferences": [ { "content": { "text": ”..." }, "location": { "type": "S3", "s3Location": { "uri": "s3://test-bedrock-kb-texts/shawshank_redemption.pdf" } } ...
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- 19. xebia.com Agents client = boto3.client('bedrock-agent-runtime’) response= client.invoke_agent( agentAliasId='AJJCWRSIB2', agentId='3LZHTSX13Q', inputText='Can you show the offers list?', sessionId='abc123’ ) completion = "" for event in response.get("completion"): chunk = event["chunk"] completion = completion + chunk["bytes"].decode() Here are the available destinations/offers: - Egypt, Hurghada - Italy, Venice - Mexico, Cancun
- 20. xebia.com • Amazon Bedrockgives access to plenty of different foundation models • You can easily orchestrate potentially difficult tasks (like RAGs or agents), all the heavy lifting is done by Bedrock • Bedrock enables high-level API which simplifies implementing even sophisticated LLM-related scenarios Summary
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