AI-Powered Tool Automatically Generates SQL Queries from Plain Language
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Structured Query Language (SQL) is complex and requires database knowledge, but AI can now generate SQL from natural language. However, challenges remain around ambiguity, needing to build for each database, and metadata complexity.
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This solution uses Amazon Bedrock's large language models, a retrieval augmented generation framework with AWS Glue metadata, a self-correction loop with Athena error messages, and Athena as the SQL engine.
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The self-correction loop allows the language model to fix SQL issues. Athena error messages provide feedback for more accurate corrections.
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The solution is tested on IMDB datasets to showcase the generation of SQL at varying complexity levels.
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After setup, the solution can work with diverse data sources like Amazon RDS, DynamoDB, and CloudWatch Logs since Athena has connectors to them for federated querying.