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LLMs.txt：AI时代网站内容访问控制的革命性标准

2026/2/2
LLMs.txt：AI时代网站内容访问控制的革命性标准
AI Summary (BLUF)

LLMs.txt is a new standard file similar to robots.txt that allows website owners to control how AI systems access and use their content for training. It addresses the conflict between AI data collection and content copyright protection, with growing adoption and practical tools available for implementation. (LLMs.txt是一种类似于robots.txt的新型标准文件，允许网站所有者控制AI系统如何访问和使用其内容进行训练。它解决了AI数据采集与内容版权保护之间的矛盾，目前正在被广泛采用，并有实用工具可供实施。)

引言

随着人工智能和大型语言模型（LLMs）的快速发展，如何有效管理这些AI系统对网络内容的访问成为一个日益重要的问题。就像robots.txt文件控制传统网络爬虫一样，LLMs.txt文件应运而生，为AI系统提供访问规则。本文将全面介绍LLMs.txt的规范、作用、商业价值、发展现状及未来趋势，并重点推荐实用的生成工具。

With the rapid advancement of artificial intelligence and large language models (LLMs), effectively managing how these AI systems access web content has become an increasingly critical issue. Just as the robots.txt file governs traditional web crawlers, the LLMs.txt file has emerged to provide access rules for AI systems. This article offers a comprehensive overview of the LLMs.txt specification, its functions, commercial value, current development status, future trends, and highlights practical generation tools.

一、什么是 LLMs.txt？

1.1 定义与规范

LLMs.txt（官网：https://llmstxt.org/ ）是一种类似于robots.txt的文本文件，专门用于指导大型语言模型（LLMs）如何访问和利用网站内容。与robots.txt控制传统网络爬虫不同，LLMs.txt专门针对AI/LLM类爬虫，允许网站所有者明确指定哪些内容可以被AI爬取用于训练，哪些内容应该被排除在外。

LLMs.txt (official website: https://llmstxt.org/) is a text file similar to robots.txt, specifically designed to guide large language models (LLMs) on how to access and utilize website content. Unlike robots.txt, which controls traditional web crawlers, LLMs.txt targets AI/LLM crawlers, allowing website owners to explicitly specify which content can be crawled by AI for training and which should be excluded.

它由AI研究者和网络标准组织提出，旨在解决AI训练数据采集与网站内容版权保护之间的矛盾。主要包括：

Proposed by AI researchers and web standards organizations, it aims to resolve the conflict between AI training data collection and website content copyright protection. Key aspects include:

  • 文件应放置在网站根目录下（如 https://example.com/llms.txt）

    The file should be placed in the website's root directory (e.g., https://example.com/llms.txt).

  • 使用简单的文本格式，易于解析

    It uses a simple text format for easy parsing.

  • 支持通配符和路径匹配

    It supports wildcards and path matching.

  • 可以指定允许或禁止特定AI系统访问

    It can specify which AI systems are allowed or disallowed from accessing content.

基本规范

LLMs.txt文件通常放置在网站的根目录下（如：https://example.com/llms.txt），其语法结构与robots.txt类似：

The LLMs.txt file is typically placed in the website's root directory (e.g., https://example.com/llms.txt), and its syntax structure is similar to robots.txt:

User-agent: [AI Crawler Name]
Allow: [Allowed Path]
Disallow: [Disallowed Path]

主要AI爬虫标识

目前常见的AI爬虫User-agent包括：

Common AI crawler User-agent identifiers currently include:

  • ChatGPT-User
  • Google-Extended
  • Anthropic-ai
  • CCBot
  • FacebookBot

国内主要AI爬虫标识（User-Agent）

Major Domestic AI Crawler Identifiers (User-Agent)

  • 百度系AI爬虫

    Baidu AI Crawlers

    • User-Agent: BaiduSpider（通用爬虫，可能用于AI训练）

      User-Agent: BaiduSpider (General-purpose crawler, potentially used for AI training)

    • 扩展标识: 百度可能未明确区分搜索爬虫和AI训练爬虫，但部分AI相关服务可能使用类似 Baidu-AI 或 Baidu-LLM 的变体。

      Extended Identifiers: Baidu may not explicitly distinguish between search crawlers and AI training crawlers, but some AI-related services might use variants like Baidu-AI or Baidu-LLM.

    • 用途: 用于文心一言（ERNIE）等大模型的数据采集。

      Purpose: Used for data collection for large models like ERNIE.

  • 字节跳动（今日头条/豆包）

    ByteDance (Toutiao/Doubao)

    • User-Agent: Bytespider（通用爬虫，可能覆盖AI训练）

      User-Agent: Bytespider (General-purpose crawler, potentially covering AI training)

    • 潜在标识: 豆包（Doubao）等AI产品可能使用 ByteDance-AI 或 Doubao-Bot。

      Potential Identifiers: AI products like Doubao may use ByteDance-AI or Doubao-Bot.

  • 阿里巴巴/达摩院

    Alibaba/DAMO Academy

    • User-Agent: AliSpider 或 Alibaba-Security（通用爬虫）

      User-Agent: AliSpider or Alibaba-Security (General-purpose crawlers)

    • AI相关: 通义千问（Qwen）可能使用 Qwen-Bot 或 Alibaba-LLM。

      AI-related: Qwen may use Qwen-Bot or Alibaba-LLM.

  • 腾讯（混元大模型）

    Tencent (Hunyuan Large Model)

    • User-Agent: TencentBot 或 QQBot（通用爬虫）

      User-Agent: TencentBot or QQBot (General-purpose crawlers)

    • AI相关: 混元大模型可能使用 Hunyuan-AI 或 WeChat-LLM。

      AI-related: The Hunyuan large model may use Hunyuan-AI or WeChat-LLM.

  • 科大讯飞（星火大模型）

    iFlytek (Spark Large Model)

    • User-Agent: iFlytekSpider 或 Spark-Bot（需观察实际使用情况）。

      User-Agent: iFlytekSpider or Spark-Bot (Actual usage needs to be observed).

  • 360搜索与AI

    360 Search and AI

    • User-Agent: 360Spider（可能用于360智脑训练）。

      User-Agent: 360Spider (Potentially used for training 360 ZhiNao).

  • 其他厂商

    Other Vendors

    • 商汤（SenseTime）: 可能使用 SenseBot。

      SenseTime: May use SenseBot.

    • MiniMax: 可能使用 MiniMax-Bot。

      MiniMax: May use MiniMax-Bot.

    • 月之暗面（Kimi）: 可能使用 Moonshot-AI。

      Moonshot AI (Kimi): May use Moonshot-AI.

1.2 与 robots.txt 的区别

1.2 Differences from robots.txt

特性 robots.txt LLMs.txt
目标用户 传统网络爬虫 大型语言模型（LLMs）
Target Audience Traditional web crawlers Large Language Models (LLMs)
主要用途 控制网页抓取 控制内容被AI学习和使用
Primary Purpose Controlling webpage crawling Controlling content for AI learning and use
规范成熟度 已有标准（robots.txt规范） 正在形成社区规范
Specification Maturity Established standard (robots.txt protocol) Community-driven规范 in formation
指令集 简单指令（Allow/Disallow） 更丰富的访问控制指令
Instruction Set Simple directives (Allow/Disallow) Richer access control directives

二、LLMs.txt 的作用与价值

二、The Role and Value of LLMs.txt

2.1 核心作用

2.1 Core Functions

  1. 内容保护：防止敏感或专有内容被AI系统未经授权学习使用。

    Content Protection: Prevents sensitive or proprietary content from being learned and used by AI systems without authorization.

  2. 版权控制：明确哪些内容可以合法用于AI训练。

    Copyright Control: Clarifies which content can be legally used for AI training.

  3. 质量管控：引导AI系统优先使用高质量内容。

    Quality Control: Guides AI systems to prioritize high-quality content.

  4. 商业策略：通过选择性开放内容实现差异化竞争。

    Business Strategy: Enables differentiated competition through selective content openness.

2.2 商业价值

2.2 Commercial Value

  1. 数据资产保护：防止核心业务数据被AI系统免费获取。

    Data Asset Protection: Prevents core business data from being freely acquired by AI systems.

  2. 内容变现：通过控制访问权限实现内容付费模式。

    Content Monetization: Enables paywalled content models by controlling access permissions.

  3. 品牌保护：防止AI生成内容中出现不当引用或歪曲。

    Brand Protection: Prevents inappropriate citations or distortions in AI-generated content.

  4. 合规管理：满足GDPR等数据隐私法规要求。

    Compliance Management: Helps meet data privacy regulation requirements like GDPR.

三、LLMs.txt 的发展现状

三、Current Development Status of LLMs.txt

3.1 提出背景与倡导者

3.1 Background and Proponents

LLMs.txt的概念主要由以下群体推动：

The concept of LLMs.txt is primarily driven by the following groups:

  • 内容创作者社区：如作家、记者和出版商协会。

    Content Creator Communities: Such as associations of writers, journalists, and publishers.

  • 技术标准组织：如W3C相关工作组。

    Technical Standards Organizations: Such as relevant working groups within the W3C.

  • 搜索引擎公司：如Google、Bing等正在探索AI内容抓取规范。

    Search Engine Companies: Such as Google and Bing, which are exploring norms for AI content crawling.

  • 开源社区：GitHub上有多个相关提案讨论。

    Open-Source Communities: Multiple related proposals and discussions exist on GitHub.

3.2 采用现状

3.2 Adoption Status

目前LLMs.txt仍处于早期采用阶段，但已有：

Currently, LLMs.txt is still in the early adoption phase, but there are already:

  • 部分新闻网站开始部署。

    Some news websites beginning to deploy it.

  • 学术出版机构积极探索。

    Academic publishing institutions actively exploring it.

  • 内容聚合平台进行测试。

    Content aggregation platforms conducting tests.

  • 开源工具链逐步完善。

    Open-source toolchains gradually improving.

3.3 未来发展趋势

3.3 Future Development Trends

  1. 标准化进程加速：预计1-2年内形成行业广泛接受的规范。

    Accelerated Standardization: Industry-wide accepted specifications are expected to form within 1-2 years.

  2. 与法律框架结合：可能与数字版权法更紧密集成。

    Integration with Legal Frameworks: May become more tightly integrated with digital copyright laws.

  3. AI系统原生支持：主流LLMs将内置对LLMs.txt的解析。

    Native Support in AI Systems: Mainstream LLMs will build in parsing for LLMs.txt.

  4. 与区块链结合：可能实现内容使用授权的自动化验证。

    Integration with Blockchain: May enable automated verification of content usage authorization.

四、如何生成 LLMs.txt 文件

四、How to Generate an LLMs.txt File

4.1 手动生成方法

4.1 Manual Generation Method

基本语法示例：

Basic syntax example:

# LLMs.txt 示例
# LLMs.txt Example
User-agent: *
Disallow: /private/
Disallow: /user-content/

Allow: /public/articles/
Crawl-delay: 10

# 特定AI系统规则
# Rules for Specific AI Systems
User-agent: GPTBot
Disallow: /research/

User-agent: ClaudeBot
Allow: /blog/

4.2 推荐生成工具

4.2 Recommended Generation Tools

  1. LLMs.txt 在线生成器：https://www.pdftool.cc/zh/llms-txt-generator

    LLMs.txt Online Generator: https://www.pdftool.cc/zh/llms-txt-generator

    • 直观的图形界面

      Intuitive graphical interface

    • 支持robots.txt一键转换

      Supports one-click conversion from robots.txt

    • 实时语法验证

      Real-time syntax validation

    • 多语言支持

      Multi-language support

  2. 其他推荐工具：

    Other Recommended Tools:

    • LLMs.txt Builder (GitHub开源项目)

      LLMs.txt Builder (GitHub open-source project)

    • WebAI Access Control (商业工具)

      WebAI Access Control (Commercial tool)

    • SEO平台集成功能（如SEMrush）

      SEO platform integration features (e.g., SEMrush)

五、如何将 robots.txt 一键转换为 LLMs.txt？

五、How to Convert robots.txt to LLMs.txt with One Click?

5.1 转换原理

5.1 Conversion Principle

https://www.pdftool.cc/zh/llms-txt-generator 提供一键转换功能，其工作原理是：

https://www.pdftool.cc/zh/llms-txt-generator provides a one-click conversion feature. Its working principle is:

  1. 解析现有robots.txt文件结构。

    Parses the structure of the existing robots.txt file.

  2. 将标准指令映射到LLMs.txt对应规则。

    Maps standard directives to corresponding rules in LLMs.txt.

  3. 添加LLMs特有的指令扩展。

    Adds LLM-specific directive extensions.

  4. 生成兼容性报告。

    Generates a compatibility report.

5.2 转换步骤

5.2 Conversion Steps

  1. 访问 https://www.pdftool.cc/zh/llms-txt-generator。

    Visit https://www.pdftool.cc/zh/llms-txt-generator.

  2. 输入您的网站URL或直接粘贴robots.txt内容。

    Enter your website URL or directly paste your robots.txt content.

  3. 选择转换模式。

    Select the conversion mode.

  4. 预览生成的LLMs.txt。

    Preview the generated LLMs.txt.

  5. 复制或下载或直接部署到网站根目录。

    Copy, download, or directly deploy it to your website's root directory.

六、最佳实践建议

六、Best Practice Recommendations

  1. 渐进式实施：先监控再限制，逐步完善规则。

    Gradual Implementation: Monitor first, then restrict, and gradually refine rules.

  2. 定期审查：随着AI生态系统变化更新规则。

    Regular Review: Update rules as the AI ecosystem evolves.

  3. 文档化：在网站明显位置说明您的AI访问政策。

    Documentation: Clearly state your AI access policy in a prominent location on your website.

  4. 组合使用：与API访问控制、版权声明等配合使用。

    Combined Use: Use in conjunction with API access controls, copyright notices, etc.

  5. 基础保护：至少禁止AI爬虫访问隐私内容和付费内容。

    Basic Protection: At a minimum, disallow AI crawlers from accessing private and paid content.

  6. 精细控制：对不同类型的AI爬虫设置不同规则。

    Granular Control: Set different rules for different types of AI crawlers.

  7. 定期更新：随着AI生态发展及时更新规则。

    Regular Updates: Update rules promptly as the AI ecosystem develops.

  8. 监控验证：通过服务器日志检查AI爬虫遵守情况。

    Monitoring and Verification: Check AI crawler compliance through server logs.

  9. 法律声明：在网站条款中明确AI数据使用政策。

    Legal Statement: Clearly define AI data usage policies in your website's terms.

结语

Conclusion

LLMs.txt代表了网络内容管理的新范式，为网站所有者提供了控制AI系统访问的有效工具。随着AI技术的普及，这种新型访问控制文件的重要性将不断提升。LLMs.txt正在成为网站与AI生态系统交互的重要接口文件。通过合理配置LLMs.txt，网站所有者可以在享受AI技术红利的同时，有效保护自身内容价值。LLMs.txt 在线生成器等工具大大降低了技术门槛，使每个网站都能轻松应对AI时代的内容管理挑战。

LLMs.txt represents a new paradigm in web content management, providing website owners with an effective tool to control AI system access. As AI technology becomes more widespread, the importance of this new type of access control file will continue to grow. LLMs.txt is becoming a crucial interface file for interaction between websites and the AI ecosystem. By properly configuring LLMs.txt, website owners can effectively protect their content value while benefiting from AI technology. Tools like the LLMs.txt online generator significantly lower the technical barrier, enabling every website to easily meet the content management challenges of the AI era.

LLMs.txt很可能成为网站标准配置的一部分。建议网站管理员未雨绸缪，尽早部署适合自身业务需求的LLMs.txt策略，为未来的网络生态变化做好准备。

LLMs.txt is likely to become a standard part of website configuration. It is recommended that website administrators plan ahead and deploy an LLMs.txt strategy suited to their business needs as soon as possible, preparing for future changes in the web ecosystem.

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