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Vanna 的核心是一个 Python 包，它使用检索增强技术（Retrieval Augmentation）帮助您利用大语言模型（LLMs）为您的数据库生成准确的 SQL 查询。 内置 Web 应用 Vanna 带有一个内置的 Web 应用 (Flask)，你可以在 Jupyter notebook 中或独立启动它。 Drop in our web component, connect your existing auth, and start querying data securely.
To start, it allows you to spend less time writing sql and more time generating insights on your data 本文详细介绍了Vanna，一个基于RAG的开源Python工具，用于通过自然语言查询数据库。 文章涵盖了Vanna的简介、安装过程、训练方法、用户界面比较、选择原因以及应用案例。 With vanna, you can empower users across your organization—regardless of their sql expertise—to interact with your database using natural language, making data more accessible to everyone.
Vanna 是一个基于 MIT 许可 的开源 Python RAG（检索增强生成）框架，用于 SQL 生成和相关功能。 它允许用户在数据上训练一个 RAG “模型”，然后提问问题，这将生成在数据库上运行的 SQL 查询语句，并将查询结果通过表格和图表的方式展示给用户。
Vanna 是一个基于 AI 的智能 SQL 生成工具，能够通过自然语言理解（NLU）和 机器学习模型，将自然语言问题转换为 SQL 查询语句。 The core concept at its heart, vanna is simple Vanna还提供了个性化的配置，比如不同的向量数据库，LLM大模型以及不同的数据库。 我将在第三篇内容中，用案例去展示如何个性化的配置Vanna，体验不同大模型进行问题回答。
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