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

AWS Machine Learning

The custom Google Chat app, configured for HTTP integration, sends an HTTP request to an API Gateway endpoint. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. Run the script init-script.bash : chmod u+x init-script.bash./init-script.bash

APIs 127
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Benchmarking Amazon Nova and GPT-4o models with FloTorch

AWS Machine Learning

Amazon Bedrock APIs make it straightforward to use Amazon Titan Text Embeddings V2 for embedding data. The implementation used the universal gateway provided by the FloTorch enterprise version to enable consistent API calls using the same function and to track token count and latency metrics uniformly. get("message", {}).get("content")

Benchmark 110
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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning

The solution also uses Amazon Cognito user pools and identity pools for managing authentication and authorization of users, Amazon API Gateway REST APIs, AWS Lambda functions, and an Amazon Simple Storage Service (Amazon S3) bucket. To launch the solution in a different Region, change the aws_region parameter accordingly.

APIs 134
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Secure a generative AI assistant with OWASP Top 10 mitigation

AWS Machine Learning

These steps might involve both the use of an LLM and external data sources and APIs. Agent plugin controller This component is responsible for the API integration to external data sources and APIs. The LLM agent is an orchestrator of a set of steps that might be necessary to complete the desired request.

APIs 116
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Build a Multi-Agent System with LangGraph and Mistral on AWS

AWS Machine Learning

By using the power of LLMs and combining them with specialized tools and APIs, agents can tackle complex, multistep tasks that were previously beyond the reach of traditional AI systems. Whenever local database information is unavailable, it triggers an online search using the Tavily API. Its used by the weather_agent() function.

APIs 123
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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. We will start by using the SageMaker Studio UI and then by using APIs. To get started, set-up a name for your experiment.

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Generate customized, compliant application IaC scripts for AWS Landing Zone using Amazon Bedrock

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Scripts 132