🧑‍💻 Profile/简介

The main contributor of this repo is a Master's student graduating in 2026, currently on the job market.

本仓库主要贡献者是2026届硕士毕业生，正在求职中，欢迎联系。

We're excited to announce a significant update planned for release by the end of 2025! This update will introduce powerful new features:

• Deep Research Integration - Enhanced research capabilities built directly into the workflow
• Free-Form Visual Design - Create and customize visuals with unprecedented flexibility
• Autonomous Asset Creation - Automatically generate assets based on your requirements
• Text-to-Image Generation - Transform text descriptions into high-quality images

Want a sneak peek? Check out our demo and detailed outputs below!

• Prompt: Please present the given document to me.

• Prompt: 请介绍小米 SU7 的外观和价格

• Prompt: 请制作一份高中课堂展示课件，主题为“解码立法过程：理解其对国际关系的影响”

📄 Paper   |   🤗 OpenSource   |   📝 Documentation   |   DeepWiki   |   🙏 Citation

We present PPTAgent, an innovative system that automatically generates presentations from documents. Drawing inspiration from human presentation creation methods, our system employs a two-step process to ensure excellence in overall quality. Additionally, we introduce PPTEval, a comprehensive evaluation framework that assesses presentations across multiple dimensions.

• [2025/09]: 🛠️ We support MCP server now, see MCP Server for details
• [2025/09]: 🚀 Released v2 with major improvements - see release notes for details
• [2025/08]: 🎉 Paper accepted to EMNLP 2025!
• [2025/05]: ✨ Released v1 with core functionality and 🌟 breakthrough: reached 1,000 stars on GitHub! - see release notes for details
• [2025/01]: 🔓 Open-sourced the codebase, with experimental code archived at experiment release

We have released our model and data at HuggingFace.

• Dynamic Content Generation: Creates slides with seamlessly integrated text and images
• Smart Reference Learning: Leverages existing presentations without requiring manual annotation
• Comprehensive Quality Assessment: Evaluates presentations through multiple quality metrics

• Iphone 16 Pro

• Build Effective Agents

PPTAgent follows a two-phase approach:

1. Analysis Phase: Extracts and learns from patterns in reference presentations
2. Generation Phase: Develops structured outlines and produces visually cohesive slides

Our system's workflow is illustrated below:

PPTEval evaluates presentations across three dimensions:

• Content: Check the accuracy and relevance of the slides.
• Design: Assesses the visual appeal and consistency.
• Coherence: Ensures the logical flow of ideas.

The workflow of PPTEval is shown below:

If you find this project helpful, please use the following to cite it:

@article{zheng2025pptagent,
  title={PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides},
  author={Zheng, Hao and Guan, Xinyan and Kong, Hao and Zheng, Jia and Zhou, Weixiang and Lin, Hongyu and Lu, Yaojie and He, Ben and Han, Xianpei and Sun, Le},
  journal={arXiv preprint arXiv:2501.03936},
  year={2025}
}