text-to-SQL with Bedrock and Aurora PostgreSQL pgvector integration #604
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Issue #, if available:
Description of changes:
Comprehensive sample showing text-to-SQL generation and semantic search using Amazon Bedrock, Aurora PostgreSQL Serverless with pgvector extension.
Key capabilities:
• Natural language to SQL conversion using Claude Sonnet
• Semantic vector search with PostgreSQL pgvector and Amazon Titan embeddings
• Automated query strategy selection between SQL and vector operations
Files Added
bedrock-text2sql-aurora-pgvector/text2sql-postgresql.ipynb- Main implementation notebookbedrock-text2sql-aurora-pgvector/infra.py- Infrastructure deployment scriptbedrock-text2sql-aurora-pgvector/clean.py- Resource cleanup scriptbedrock-text2sql-aurora-pgvector/config.json- Configuration settingsbedrock-text2sql-aurora-pgvector/ecommerce_schema.sql- Database schemabedrock-text2sql-aurora-pgvector/ecommerce_data.sql- Sample dataBy submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.