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To start, it allows you to spend less time writing sql and more time generating insights on your data Vanna是一个为用户提供更便捷地与SQL数据库交互的工具。 它通过允许用户使用自然语言来查询数据库，然后将这些语言转换成SQL语句，从而实现数据库信息的查询和获取。 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 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。 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。 Vanna 2.0 includes powerful enterprise features for production use
Lifecycle hooks — add quota checking, custom logging, content filtering at key points in the request lifecycle
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。 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。 Vanna的核心是一个Python包，它使用检索增强功能来帮助您使用llm为数据库生成准确的SQL查询。 Vanna的工作分为两个简单的步骤——在你的数据上训练一个RAG“模型”，然后问一些问题，这些问题将返回SQL查询，这些查询可以设置为自动在你的数据库上运行。 The core concept at its heart, vanna is simple
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