The purpose of the Text-to-SQL task is to bridge the gap between natural language and SQL queries. Current approaches mainly rely on large language models (LLMs), but employing them for Text-to-SQL ha ...
This application enables users to interact with an e-commerce SQL database using natural language queries. It leverages two specialized AI agents: SQL Agent: Converts natural language questions into ...
Data work in 2026 asks for more than chart building. Professionals are expected to clean data, query databases, explain trends, and present findings clearly across business, finance, product, and ...
Abstract: To leverage the advantages of LLM in addressing challenges in the Text-to-SQL task, we present XiYan-SQL, an innovative framework effectively generating and utilizing multiple SQL candidates ...
This document breaks down the implementation of the Send Chat History API for the Semantic Kernel orchestrator extension. The feature enables developers to send conversation history from Semantic ...
Abstract: Complex Text-to-SQL generation remains challenging due to the lack of explicit modeling of hierarchical schema structures and persistent semantic mismatches between natural-language queries ...
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