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    Home»Artificial Intelligence»How to Build an AI Agent for Data Analytics Without Writing SQL | by Chengzhi Zhao | Jan, 2025
    Artificial Intelligence

    How to Build an AI Agent for Data Analytics Without Writing SQL | by Chengzhi Zhao | Jan, 2025

    Team_AIBS NewsBy Team_AIBS NewsJanuary 8, 2025No Comments2 Mins Read
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    Create a complete AI agent from the bottom up using LangChain and DuckDB

    Towards Data Science

    Picture by James A. Molnar on Unsplash

    SQL has historically served as the elemental language for almost all of information analytics duties. We frequently provide you with questions that want information to get solutions. SQL is important for changing enterprise necessities into executable code for information retrieval. Nonetheless, with AI, we are able to develop an AI agent able to addressing enterprise inquiries with out necessitating SQL experience.

    This put up will display the development of an AI agent from inception utilizing LangChain and DuckDB. After constructing your personal AI agent for SQL, you possibly can accomplish information analytics duties pretty shortly. Much more intriguingly, we are able to use a random dataset from Kaggle to check the AI’s means to investigate information in SQL.

    • DuckDB: DuckDB is an in-process SQL OLAP database administration system; it’s straightforward to put in & write analytics SQL queries from a CSV/JSON file in seconds.
    • LangChain: LangChain is a composable framework to construct with LLMs. Given the speedy progress of AI brokers, a key element of growing our brokers is utilizing a framework like LangChian to handle the LLM course of and perform particular…



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