Generate vector embeddings for your data using AWS Lambda as a processor for Amazon OpenSearch Ingestion

This article explains how to generate vector embeddings using AWS Lambda as a processor for Amazon OpenSearch Ingestion, leveraging Amazon Bedrock's Titan Text Embeddings Model.

• OpenSearch Ingestion now supports AWS Lambda processors for transforming data
• Solution demonstrates creating embeddings for IMDB movie dataset stored in Amazon S3
• Lambda function invokes Amazon Titan Embedding Model to generate vector embeddings
• Pipeline configuration batches events and transforms data before sending to OpenSearch Serverless
• Provides a serverless approach for embedding generation with automatic scaling

The solution creates a flexible, scalable pipeline for generating vector embeddings, enabling use cases like recommendation engines and personalized search.