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technologyreview.com·1h ago
Data Science
Towards AI·Jun 16·11 min read
Never Let the LLM Write the Joins
TL;DR
Many engineers struggle with integrating large language models (LLMs) into database queries due to security and accuracy concerns. A domain graph was built to represent three databases, capturing tables, columns, join paths, and security rules.
✦ Why It Matters
Engineers can leverage domain graphs to enhance the security and accuracy of LLM-generated database queries.
Key Takeaways
- Build a domain graph for database representation.
- Integrate security rules into the graph structure.
- Use in-memory snapshots for quick access.
- Ensure user permissions are respected in queries.
Full Summary
Engineers often face challenges when using large language models (LLMs) for database interactions, particularly regarding security and the accuracy of query results. To address this, a domain graph was developed that integrates three databases, providing a structured representation of tables, columns, join paths, and associated business meanings.
This graph is enriched with security rules and maintained in a fast in-memory snapshot for quick access. By utilizing this domain graph, engineers can facilitate safer conversations with databases, ensuring that users have appropriate permissions.
The methodology emphasizes the importance of understanding the underlying data structure and security implications when designing conversational analytics engines. As a result, this approach enhances the reliability of database queries generated by LLMs, ultimately leading to improved user trust and engagement.