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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. This request contains the user’s message and relevant metadata.

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Relative Python imports in a Dockerized lambda function

Xebia

Relative Python imports can be tricky for lambda functions. But recently, I ran into the same issue with Dockerized lambda functions. py touch lib/functions/hello-world/requirements.txt touch lib/functions/hello-world/Dockerfile Now you will need to fill the Dockerfile, like this: FROM public.ecr.aws/lambda/python:3.12

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Careful model selection, fine-tuning, configuration, and testing might be necessary to balance the impact of latency and cost with the desired classification accuracy. This architecture workflow includes the following steps: A user submits a question through a web or mobile application. 70B and 8B.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. The generative AI playground is a UI provided to tenants where they can run their one-time experiments, chat with several FMs, and manually test capabilities such as guardrails or model evaluation for exploration purposes.

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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

Solution overview This section outlines the architecture designed for an email support system using generative AI. The following diagram provides a detailed view of the architecture to enhance email support using generative AI. The workflow includes the following steps: Amazon WorkMail manages incoming and outgoing customer emails.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

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Harness the power of MCP servers with Amazon Bedrock Agents

AWS Machine Learning - AI

Using a client-server architecture, MCP enables developers to expose their data through lightweight MCP servers while building AI applications as MCP clients that connect to these servers. In the first flow, a Lambda-based action is taken, and in the second, the agent uses an MCP server.