Developer details on-prem text-to-SQL agent to prevent LLM join errors

A developer detailed how they built an on-premises text-to-SQL agent to query a large 900-table database, overcoming challenges with local LLMs inventing incorrect joins. The solution separates table selection from join logic, using vector search and reciprocal rank fusion for table retrieval. Known relationships are stored in a trust-weighted join graph, and an internal risk penalty determines the allowed join paths, ensuring accurate and safe SQL queries. AI

IMPACT Provides a practical, on-premise solution for reliable text-to-SQL querying over large schemas, addressing common LLM failure modes.

RANK_REASON Developer shares practical implementation details for a custom text-to-SQL agent.

Read on dev.to — LLM tag →

• BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
• ClickHouse
• LiteLLM
• Markdown
• pgvector
• PostgreSQL
• reciprocal rank fusion

• product
• infra

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →