> For the complete documentation index, see [llms.txt](https://webai.gitbook.io/web-ai-whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://webai.gitbook.io/web-ai-whitepaper/introduction-of-webai.md). # Introduction of WebAI Creating a website generally requires an understanding of website coding languages such as HTML or CSS. For many people unfamiliar with these types of coding languages, starting up a fully functional website from scratch would require hours upon hours of time spent manually learning how to input individual elements - let alone create something aesthetically pleasing without risking errors or compatibility issues between different browsers and devices. Some software suites exist that allow for user-friendly design operations; however this type of approach still requires considerable time investment along with knowledge of basic design principles - not everyone has an eye for aesthetics.\ \ **Web AI** is an innovative project that uses Artificial Intelligence (AI) technology to create customized websites from scratch. It utilizes deep learning algorithms and natural language processing (NLP) to analyze user requests and generate attractive, user-friendly websites according to their preferences. With its intuitive design, Web AI simplifies the website creation process and enables users to develop professional-looking websites for any purpose without manual coding. Whether you need a personal portfolio or a comprehensive ecommerce site, Web AI puts the power of web development into the hands of users with minimal effort. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://webai.gitbook.io/web-ai-whitepaper/introduction-of-webai.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.