Gemini Code Assist Standard 和 Enterprise 如何使用您的数据
使用集合让一切井井有条
根据您的偏好保存内容并对其进行分类。
本文档介绍了 Gemini Code Assist Standard 和 Enterprise 版(提供 AI 赋能的辅助功能)如何借助生成式 AI 技术遵守 Google 的隐私保护承诺。当您在开发环境中使用 Gemini Code Assist 标准版或企业版时,Google Cloud 会根据我们的服务条款和云端数据处理附录处理您的提示。
如需详细了解 Gemini Code Assist Standard 和 Enterprise 版本,请参阅 Gemini Code Assist 概览。
Google 的隐私保护承诺
Google 是业界首家发布 AI/机器学习隐私权承诺的公司之一,该承诺概述了客户应拥有最高级别安全性并能够控制其在云中存储的数据的这一信念。该承诺会延伸到 Gemini Code Assist Standard 和 Enterprise 版生成式 AI 产品。Google 通过健全的数据治理实践(包括审核 Google Cloud 在其产品开发中使用的数据),帮助确保 Google 团队遵循这些承诺。如需详细了解 Google 如何处理数据,请参阅客户数据处理附录 (CDPA) 或适用于您的 Google Cloud 服务的数据处理协议。
您提交和接收的数据
您向 Gemini 提出的问题(包括您提交给 Gemini 以进行分析或完成的任何输入信息或代码)称为“提示”。您从 Gemini 收到的答案或代码补全结果称为“回答”。
Gemini Code Assist Standard 和 Enterprise 版不会将您的提示或其回答用作训练模型的数据。某些功能仅通过 Gemini for Google Cloud 可信测试员计划提供,您可以选择是否共享数据,但这些数据将用于改进产品,而非用于训练 Gemini 模型。
借助 Gemini Code Assist Enterprise 中的代码自定义功能,您可以直接从 Gemini Code Assist 获取基于贵组织的私有代码库的代码建议。当您使用代码自定义功能时,我们会安全地访问和存储您的专用代码。此访问权限和存储空间对于提供您所请求的代码自定义服务至关重要。如需配置和使用代码自定义功能,请参阅配置和使用 Gemini Code Assist 代码自定义功能。
借助 Gemini Code Assist 工具,开发者无需离开 IDE 即可连接到外部服务,以获取任务、总结设计文档等。Gemini Code Assist 工具不会在工具之间共享数据。当您向某个工具发送提示时,其他工具无法访问该提示或回答。工具只能访问在提示中使用 @TOOL_NAME
语法直接发送给它们的数据。
由于 Gemini 是一项不断发展的技术,因此它可能会生成看似合理但实际上不正确的输出。我们建议您先验证 Gemini 的所有输出,然后再使用。如需了解详情,请参阅 Gemini Code Assist 和 Responsible AI。
提示的加密
当您向 Gemini 提交问题时,您的数据会在传输过程中加密,然后作为输入数据传送到 Gemini 中的底层模型。如需详细了解 Gemini 数据加密,请参阅默认静态加密和传输加密。
通过 Gemini 生成的节目数据
Gemini 使用第一方 Google Cloud 代码以及所选第三方代码进行训练。您需要对代码的安全性、测试和有效性负责,包括 Gemini 为您提供的任何代码补全、生成或分析。
在建议中直接引用某个来源的长篇内容时,Gemini 还会提供来源引用,以帮助您遵守所有许可授权要求。
由于 Gemini 中的回答是通过在多行代码上进行训练的模型生成的,因此您应对 Gemini 提供的代码采取与对待任何其他代码相同的谨慎态度。请确保您正确测试代码,并检查是否存在安全漏洞、不兼容问题和其他潜在问题。
后续步骤
如未另行说明,那么本页面中的内容已根据知识共享署名 4.0 许可获得了许可,并且代码示例已根据 Apache 2.0 许可获得了许可。有关详情,请参阅 Google 开发者网站政策。Java 是 Oracle 和/或其关联公司的注册商标。
最后更新时间 (UTC):2025-08-31。
[null,null,["最后更新时间 (UTC):2025-08-31。"],[[["\u003cp\u003eGemini, an AI-powered assistant, adheres to Google's privacy commitment for generative AI technologies, ensuring high security and control over user data.\u003c/p\u003e\n"],["\u003cp\u003eGemini does not utilize user prompts or responses to train its models, maintaining the privacy of user interactions.\u003c/p\u003e\n"],["\u003cp\u003eCode customization features in Gemini securely access and store an organization's private code to provide tailored code suggestions.\u003c/p\u003e\n"],["\u003cp\u003eData submitted to Gemini is encrypted in-transit to ensure secure communication and protect sensitive information.\u003c/p\u003e\n"],["\u003cp\u003eUsers are responsible for the security, testing, and effectiveness of the code generated or suggested by Gemini, as it's trained on diverse code sources.\u003c/p\u003e\n"]]],[],null,["# How Gemini Code Assist Standard and Enterprise use your data\n\nThis document describes how Gemini Code Assist Standard and\nEnterprise editions, which offer AI-powered assistance, conform to\n[Google's privacy commitment](https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-unveils-ai-and-ml-privacy-commitment)\nwith generative AI technologies. When you use Gemini Code Assist\nStandard or Enterprise editions in a development environment, Google Cloud\n[handles your prompts](#submit-receive-data) in accordance with our [terms of\nservice](https://cloud.google.com/terms) and [Cloud Data Processing Addendum](https://cloud.google.com/terms/data-processing-addendum).\n\nFor more information about Gemini Code Assist Standard and\nEnterprise editions, see the\n[Gemini Code Assist overview](/gemini-code-assist/docs/overview).\n\nGoogle's privacy commitment\n---------------------------\n\nGoogle was one of the first in the industry to publish an [AI/ML privacy\ncommitment](https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-unveils-ai-and-ml-privacy-commitment),\nwhich outlines our belief that customers should have the highest level of\nsecurity and control over their data that's stored in the cloud. That commitment\nextends to Gemini Code Assist Standard and Enterprise edition\ngenerative AI products. Google helps ensure that its teams are following these\ncommitments through robust data governance practices, which include reviews of\nthe data that Google Cloud uses in the development of its products. You\ncan find more details about how Google processes data in\n[Customer Data Processing Addendum (CDPA)](https://cloud.google.com/terms/data-processing-addendum)\nor the data processing agreement applicable to your Google Cloud service.\n\nData you submit and receive\n---------------------------\n\nThe questions that you ask Gemini, including any input information or\ncode that you submit to Gemini to analyze or complete, are called\n*prompts* . The answers or code completions that you receive from Gemini\nare called *responses*.\n\nGemini Code Assist Standard and Enterprise editions don't use\nyour prompts or its responses as data to train its models. Some features are\nonly available through the\n[Gemini for Google Cloud Trusted Tester Program](https://cloud.google.com/gemini-for-cloud/ttp/welcome),\nwhich lets you optionally share data, but the data is used for product\nimprovements, not for training Gemini models.\n\n[Code customization](/gemini-code-assist/docs/code-customization-overview) in\nGemini Code Assist Enterprise lets you get code suggestions based\non your organization's private codebase directly from\nGemini Code Assist. When you use code customization, we securely\naccess and store your private code. This access and storage is essential for\ndelivering the code customization service you've requested. To configure and use\ncode customization, see\n[Configure and use Gemini Code Assist code customization](/gemini-code-assist/docs/code-customization).\n\n[Gemini Code Assist tools](/gemini-code-assist/docs/tools-agents/tools-overview)\nlet developers connect to external services without leaving the IDE in order to\nget tasks, summarize design documents and more. Gemini Code Assist\ntools don't share data between tools. When you send a prompt to one tool, other\ntools don't have access to that prompt or the response. Tools only have access\nto data sent directly to them using the `@TOOL_NAME` syntax in a prompt.\n\nBecause Gemini is an evolving technology, it can generate output that's\nplausible-sounding but factually incorrect. We recommend that you validate all\noutput from Gemini before you use it. For more information, see\n[Gemini Code Assist and responsible AI](/gemini-code-assist/docs/responsible-ai).\n\nEncryption of prompts\n---------------------\n\nWhen you submit prompts to Gemini, your data is encrypted in-transit as\ninput to the underlying model in Gemini. For more information on\nGemini data encryption, see\n[Default encryption at rest](https://cloud.google.com/docs/security/encryption/default-encryption)\nand [Encryption in transit](https://cloud.google.com/docs/security/encryption-in-transit).\n\nProgram data generated from Gemini\n----------------------------------\n\nGemini is trained on first-party Google Cloud code as well as\nselected third-party code. You're responsible for the security, testing, and\neffectiveness of your code, including any code completion, generation, or\nanalysis that Gemini offers you.\n\nGemini also provides source citations when suggestions directly quote\nat length from a source to help you comply with any license requirements.\n\nBecause responses in Gemini are generated from a model that's trained\non many lines of code, you should exercise the same care with\nGemini-provided code that you would with any other code. Make sure that\nyou test the code properly and check for security vulnerabilities,\nincompatibilities, and other potential issues.\n\nWhat's next\n-----------\n\n- Learn about the [security, privacy, and compliance of Gemini Code Assist](https://cloud.google.com/gemini/docs/codeassist/security-privacy-compliance)."]]