Knowledge Bases for Amazon Bedrock provides a managed service for implementing the Retrieval Augmented Generation (RAG) workflow from ingestion to retrieval and prompt augmentation without the need for custom integrations. However, in large or complex input text documents with PDF or .txt files, querying indexes may yield subpar results due to semantic relationships. New features in Knowledge Bases for Amazon Bedrock aim to improve response accuracy in RAG applications by offering advanced data chunking options, query decomposition, and improved CSV and PDF parsing. These features enhance the precision and control in RAG workflows.
Advanced parsing involves analyzing and extracting meaningful information from unstructured documents such as tables, text, images, and metadata. By focusing on semantic chunking and hierarchical chunking techniques, the service can divide data into meaningful and complete chunks, improving retrieval accuracy. Semantic chunking maintains semantic integrity for accurate results, while hierarchical chunking organizes data into a hierarchical structure, enabling more targeted retrieval.
The service also allows for custom processing logic using AWS Lambda functions for flexibility and control. Metadata customization for .csv files separates content and metadata fields, improving efficiency in data management. Query reformulation turns complex queries into sub-queries for more targeted retrieval, enhancing accuracy. These advanced features provide users with greater customization and accuracy in knowledge base management.
The authors Sandeep Singh, Mani Khanuja, and Chris Pecora contribute expertise in generative AI, machine learning, and system design, with a focus on developing innovative solutions for diverse industries. They emphasize the power of Knowledge Bases for Amazon Bedrock in enabling efficient decision-making and knowledge management in the era of data-driven insights, encouraging users to explore the full potential of the service for improved retrieval and knowledge management.
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https://aws.amazon.com/blogs/machine-learning/knowledge-bases-for-amazon-bedrock-now-supports-advanced-parsing-chunking-and-query-reformulation-giving-greater-control-of-accuracy-in-rag-based-applications/