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Combine keyword and semantic search for text and images using Amazon Bedrock and Amazon OpenSearch Service

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Familiarity with AWS Identity and Access Management (IAM) , Amazon Elastic Compute Cloud (Amazon EC2) , OpenSearch Service, and SageMaker. Familiarity with Python programming language. About the Authors Renan Bertolazzi is an Enterprise Solutions Architect helping customers realize the potential of cloud computing on AWS.

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Integrate generative AI capabilities into Microsoft Office using Amazon Bedrock

AWS Machine Learning Blog

To set up the integration, follow these steps: Create an AWS Lambda function with Python runtime and below code to be the backend for the API. Make sure that we have Powertools for AWS Lambda (Python) available in our runtime, for example, by attaching a Lambda layer to our function.

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Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning Blog

MLflow has integrated the feature that enables request signing using AWS credentials into the upstream repository for its Python SDK, improving the integration with SageMaker. The changes to the MLflow Python SDK are available for everyone since MLflow version 1.30.0. mlflow/runs/search/", "arn:aws:execute-api: : : / /POST/api/2.0/mlflow/experiments/search",

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Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

AWS Machine Learning Blog

The following code snippet demonstrates how to call the retrieve_and_generate API using the Boto3 library in Python. Streamlit sample app To showcase the interaction between doctors and the knowledge base, we developed a user-friendly web application using Streamlit , a popular open source Python library for building interactive data apps.

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