Bedrock knowledge base retrieval with opensearch

Good afternoon!

1. Default Behavior and Limitations:

• OpenSearch typically returns up to 10,000 documents by default
• When your filter returns more than 10,000 chunks, you might indeed miss some relevant content
• This could potentially impact the quality and completeness of answers

2. Possible Solutions:

a) Pagination Approach:

• Implement pagination in your queries
• Break down large result sets into smaller batches
• Process multiple pages of results to ensure complete coverage

b) Optimize Chunking Strategy:

• Review your chunking strategy to create larger, but still meaningful chunks
• This reduces the total number of chunks while preserving context
• Aim for a balance between chunk size and semantic completeness

c) Refine Filtering Criteria:

• Make filters more specific to reduce the result set
• Use additional metadata fields to narrow down the search space
• Implement hierarchical filtering when possible

d) Use Composite Indexes:

• Configure OpenSearch to use composite indexes
• This can help handle larger datasets more effectively

3. Best Practices:

• Monitor the size of your knowledge base
• Track query performance and result counts
• Implement error handling for cases where results might be truncated
• Consider implementing warning systems when approaching document limits

4. Alternative Approaches:

• Consider splitting very large knowledge bases into logical subdivisions
• Use multiple knowledge bases if the data can be logically separated
• Implement pre-filtering at the application level

To directly answer your question - yes, there is a risk of missing relevant information if your filtered results exceed 10,000 chunks. It's important to implement one or more of the above solutions to ensure comprehensive coverage of your knowledge base.