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How to use LLMs to generate accurate SQL for real-world data

๐Ÿค– Chat with your SQL database ๐Ÿ“Š. Accurate Text-to-SQL Generation via LLMs using Agentic Retrieval ๐Ÿ”„. We recently embarked on an experiment to see if large language models (specifically LLMs) could help in generating SQL queries for real-world datasets.

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  1. A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL

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  2. Interact with your SQL database, Natural Language to SQL using LLMs

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  3. (2) Train Your AI: Fine-tune an LLM (including GPT-4) specifically for your data, increasing accuracy and lowering latency (3) Trust the Answer: See confidence scores with each AI-generated query, stay in control.

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  4. Natural-SQL-7B

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    a strong text-to-SQL model

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  5. Data management with LLMs

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