Skip to content
View WebPAI's full-sized avatar

    Block or report WebPAI

    Block user

    Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

    You must be logged in to block users.

    Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
    Report abuse

    Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

    Report abuse
    WebPAI/README.md

    Welcome to WebPAI 👋

    WebPAI (Web Development Powered by AI) aims to build an AI platform for more reliable and practical automated webpage generation.

    The rapid advancements in generative AI, particular multi-modal large language models, now excelling in multimodal understanding and code generation. This progress introduces a new front-end development paradigm, where multimodal LLMs can automatically convert visual designs into GUI code implementations, facilitating the software product delivery process.

    This project collects a set of research resources and releases open datasets for webpage generation studies.

    Project Contents

    ProjectPaper TitleMaintainer
    DCGenAutomatically Generating UI Code from Screenshot: A Divide-and-Conquer-Based Approach@yxwan123
    Interaction-to-codeInteraction2Code: How Far Are We From Automatic Interactive Webpage Generation?@xjywhu
    MRWebMRWeb: An Exploration of Generating Multi-Page Resource-Aware Web Code from UI Designs@yxwan123
    DesignBenchDesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation@xjywhu@DonaldLamNL
    EfficientUICoderEfficientUICoder: Efficient MLLM-based UI Code Generation via Input and Output Token Compression@xjywhu@starry1001
    TDDevAutomatically Generating Web Applications from Requirements Via Multi-Agent Test-Driven Development@yxwan123
    ComUICoderComUICoder: Component-based Reusable UI Code Generation for Complex Websites via Semantic Segmentation and Element-wise Feedback@xjywhu@clearlove43967@C00H

    Datasets

    Dataset NameDescriptionDownloading
    DCGen120 more-complicated real-world static webpages↗️
    Interaction-to-code127 real-world user-interactive webpages and 374 interactions↗️
    MRWeb500 real-world and synthetic multi-page resource aware webpages↗️
    Design-to-code484 static real-world webpages↗️
    DesignBench900 real-world webpages, three frameworks (react, vue and angular), three tasks (design generation, edit and repair)↗️
    ComUIBench150 real-world very complex webpages with component annotations↗️

    ⭐ If you find this project useful, please give it a star.

    🔥 Welcome to Contribute!

    This project is actively maintained, and we welcome your contributions :-)

    Contacts (alphabetically)

    Please feel free to reach out to us if you have any questions on this project.

    Pinned Loading

    1. Interaction2CodeInteraction2CodePublic

      [ASE 2025] Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping

      Python 61 2

    2. DCGenDCGenPublic

      Jupyter Notebook 45 9

    3. DesignBenchDesignBenchPublic

      DesignBench: A Comprehensive Benchmark for MLLM-based Front-end Code Generation

      Python 55 5

    4. EfficientUICoderEfficientUICoderPublic

      [FSE 2026] EfficientUICoder: Efficient MLLM-based UI Code Generation via Input and Output Token Compression

      Jupyter Notebook 28 1

    5. TDDevTDDevPublic

      Forked from yxwan123/TDDev

      Generating Full-Stack Web Applications from Requirements Via Multi-Agent Test-Driven Development

      TypeScript

    6. ComUICoderComUICoderPublic

      [SIGKDD 2026] ComUICoder: Component-based Reusable UI Code Generation for Complex Websites via Semantic Segmentation and Element-wise Feedback

      Python 27