Remove Construction Remove Lambda Remove Serverless
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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. The code runs in a Lambda function. Implement your business logic in this file.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

The solution presented in this post takes approximately 15–30 minutes to deploy and consists of the following key components: Amazon OpenSearch Service Serverless maintains three indexes : the inventory index, the compatible parts index, and the owner manuals index.

Lambda 129
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The Future of Serverless is … Functionless?

Stackery

I first heard about this pattern a few years ago at a ServerlessConf from a consultant who was helping a “big bank” convert to serverless. It will scale just fine… unless you hit your account-wide Lambda limit. 6.10, which is approaching EOL for AWS Lambda? They needed to ingest data from an API and put it in a DynamoDB table.

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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Lets look at an example solution for implementing a customer management agent: An agentic chat can be built with Amazon Bedrock chat applications, and integrated with functions that can be quickly built with other AWS services such as AWS Lambda and Amazon API Gateway. The agent has the capability to: Provide a brief customer overview.

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Use AWS Generative AI CDK Constructs To Speed up App Development

Dzone - DevOps

In this blog, we will use the AWS Generative AI Constructs Library to deploy a complete RAG application composed of the following components: Knowledge Bases for Amazon Bedrock : This is the foundation for the RAG solution. An S3 bucket: This will act as the data source for the Knowledge Base.

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Running Lambdas on your Laptop

Stackery

Serverless has the potential to bring massive ops advantages to projects of all sizes, but while it presents great business benefits, we need to spare a thought for how teams develop on serverless. A frequent response I’ve received since is ‘Why not use the SAM CLI tools to do local serverless?’ What does SAM Local let me do?

Lambda 58
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Revolutionize trip planning with Amazon Bedrock and Amazon Location Service

AWS Machine Learning - AI

If an image is uploaded, it is stored in Amazon Simple Storage Service (Amazon S3) , and a custom AWS Lambda function will use a machine learning model deployed on Amazon SageMaker to analyze the image to extract a list of place names and the similarity score of each place name. _validate_tools(tools) _output_parser = output_parser or cls._get_default_output_parser()