Create a live streaming generative AI tool with Amazon Bedrock, Amazon Managed Service for Apache Flink, and Amazon Kinesis Data Streams on AWS

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Generative artificial intelligence (AI) has seen significant growth in 2024, especially concerning large language models (LLMs) for intelligent chatbot solutions. Amazon Bedrock is a managed service that offers various foundation models (FMs) from renowned AI companies like AI21 Labs, Anthropic, Cohere, and others, allowing users to build generative AI applications securely and responsibly. This technology goes beyond chatbots and can be used for sentiment analysis of data from sources like customer reviews.

Businesses generate real-time data continuously through various streams, and processing this data promptly is crucial for deriving valuable insights. Apache Flink is a popular framework for stream processing, and AWS offers a managed service for Apache Flink through Amazon Managed Service for Apache Flink. By integrating generative AI into a streaming architecture on AWS using services like Managed Service for Apache Flink and Amazon Kinesis Data Streams, businesses can leverage real-time data for quick insights.

The solution involves creating a real-time streaming pipeline that sends review data to a Kinesis Data Stream, processes it with Managed Service for Apache Flink, invokes Amazon Bedrock for generative AI capabilities, and then visualizes the results in an OpenSearch Service dashboard. Prompt engineering techniques are used to guide the generative AI model’s responses and ensure consistent and structured output.

To set up this solution, users need to create the Flink application, deploy the AWS CDK stack, connect to OpenSearch Dashboards, and set up the streaming producer. The Flink application includes asynchronous calls to the Amazon Bedrock API using Anthropic Claude 3 Haiku. Error handling is important to properly handle failed reviews for reprocessing and troubleshooting.

After setting up the solution, users can observe sentiment analysis results in the OpenSearch dashboard generated from streaming review data. When finished, users can clean up resources by deleting the Python producer and destroying the AWS CDK stack. By following the sample code provided in the GitHub repository, businesses can incorporate generative AI capabilities into their streaming architecture.

Overall, this post provides a comprehensive guide on leveraging generative AI in a streaming architecture using Amazon Bedrock and Managed Service for Apache Flink, with a focus on prompt engineering and error handling. For more information on Managed Service for Apache Flink and Amazon Bedrock, users can refer to relevant resources provided by AWS.

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https://aws.amazon.com/blogs/big-data/build-a-real-time-streaming-generative-ai-application-using-amazon-bedrock-amazon-managed-service-for-apache-flink-and-amazon-kinesis-data-streams/