ppt-master README

The project's README from github.com/hugohe3/ppt-master. As one markdown file: README.md.

PPT Master — AI generates native PowerPoint from any document

Version License: MIT GitHub stars AtomGit stars The Agentic Leaderboard

hugohe3%2Fppt-master | Trendshift GitHub Trending Repository of the Day

English | 中文

❤️ Sponsors

This project is kept free and open source with the support of Kimi, PackyCode, APIKEY.FUN, RunAPI, YouYun ZhiSuan and other sponsors.

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Kimi

Thanks to Kimi for sponsoring this project! Kimi K3 is the world's first open 3T-class model, featuring native vision and a 1-million-token context window. With PPT Master, K3 can understand source materials such as PDFs, DOCX files, and web pages, identify key points, structure the narrative, and generate a natively editable PPTX that you can continue refining in PowerPoint.

Try Kimi Code, or access the API through the Kimi Open Platform (中文站 | Global).


PackyCode Thanks to PackyCode for sponsoring this project! PackyCode is a reliable and efficient API relay service provider, offering relay services for Claude Code, Codex, Gemini, and more. PackyCode provides special discounts for our project users: register using this link and enter the promo code ppt-master during recharge to get 10% off.
APIKEY.FUN Thanks to APIKEY.FUN for sponsoring this project! APIKEY.FUN is a professional enterprise-grade AI relay service committed to stable, efficient, and low-cost AI access for businesses and developers. The platform supports mainstream models including Claude, OpenAI, and Gemini, with prices as low as 7% of official rates. Register through our dedicated link for an exclusive perk: up to 5% off on top-ups, permanently.
RunAPI Thanks to RunAPI for sponsoring this project! RunAPI is an efficient and stable API platform — a single API Key gives you access to 150+ leading models, including OpenAI, Claude, Gemini, DeepSeek, and Grok, at prices as low as 10% of official rates, with exceptional stability and seamless compatibility with tools like Claude Code. RunAPI offers an exclusive perk for PPT Master users: register and contact an administrator via our dedicated link to claim ¥7 in free credit.
YouYun ZhiSuan Thanks to YouYun ZhiSuan for sponsoring this project! YouYun ZhiSuan is UCloud's AI cloud platform, providing one-stop API services for mainstream domestic and international models, all accessible with a single key. The platform features cost-effective CodingPlan packages for domestic models (including GLM5.2, Deepseek-v4, and more), along with official channels for stable access to overseas models, meeting diverse development needs. It's compatible with mainstream AI coding tools like Claude Code and Codex, as well as general API calls. The platform supports enterprise-level high concurrency, 24/7 technical support, and self-service invoicing. Register through this link to receive up to ¥10 in free credits. This project has been built into an Agent — PPT Master — ready to use without local deployment.

Editable is already table stakes — what sets PPT Master apart is native depth. It hands you a real PowerPoint: slide masters, native shapes, data-backed charts and tables — not flat text boxes, and not a filled-in template. It also does more than lay slides out nicely — it reasons the argument into shape first, then designs; and that native depth keeps converging with PowerPoint itself, adding more of its native capabilities release after release. In form, it's a workflow that runs inside any agent-capable AI tool: hand the AI your topic or material, and it generates on your machine — your data stays local, no platform or model lock-in. How it works and where the limits are → Product Positioning.

Quick Start · Live Demo · Examples · FAQ · Roadmap

Pixel art — Chinese breakfast atlas
Pixel Art — Chinese breakfast atlas: AI sprite sheets, HUD panels, Morph and 8-bit sound cues
Technical blueprint — Attention Is All You Need
Technical Blueprint — Transformer paper walkthrough: diagrams, native formulas, notes and animations
Brand template — China Telecom 2025 results
Brand Template — China Telecom 2025 results on the company's own deck template, with a native-chart export

Every example is a single pass with no manual polish; downloading a .pptx and opening it in PowerPoint is the fastest way to see what it can really do.
Flip through all examples online → · Source repository · Why PPT Master?


Product Positioning

Editable is now table stakes — the real question is how much of PowerPoint you actually get. PPT Master delivers PowerPoint's native object model itself, and in depth: native shapes and connectors with working adjustment handles, data-backed charts and tables on demand, and the full text / picture / fill / effect model — click any element and keep editing it as a native PowerPoint object; and through the template / structured route, it can hand you a deck with real slide masters and layouts (p:sldMaster / p:sldLayout inheritance).

And that depth is a direction of travel, not a fixed checklist. PPT Master's north star is to keep converging with PowerPoint itself: an ongoing effort to build and integrate more of PowerPoint's native capabilities, release after release, closing the gap between what an AI can generate for you and what you could build by hand in PowerPoint. The PowerPoint ↔ SVG Mapping Guide is the honest, feature-by-feature record of how far that reaches today — and SmartArt is a deliberate omission, not a gap.

In form, it's a workflow (a "skill") that runs inside any agent-capable AI tool: tell it in chat — "make a deck from this PDF" — and it runs the workflow on your machine and exports a natively editable .pptx. No coding on your side; you do exactly three things — install Python, install an AI tool, drop in your material.

Generating a new deck from source documents is the main pipeline, but not the only route. PPT Master can also distill reusable brand / style / layout / deck templates from your references, fill an existing .pptx with new content while preserving its design, and add native transitions, animations, and narration to a finished deck — each route with an explicit contract for what gets preserved. How to use each capability → Getting Started.

On top of that native depth, this form comes with three promises:

Why you'd choose it, and where it isn't the right fit → Why PPT Master; the long-term capability boundaries behind these promises → Project Positioning.

[!IMPORTANT]

This is a tool, not a wishing well

harness + model = agent — PPT Master only owns the workflow; the model sets the ceiling. Recommended: Kimi K3 (or Claude) with a large context window (~1M tokens) + AI image generation (gpt-image-2 or Google gemini-3.1-flash-image); other models can run the pipeline, with a quality gap.

And don't expect a finished, perfect deck in one shot. The tool's value is taking most of the tedious work off your plate; the polishing that's left is yours — a natively editable deck exists precisely so you can keep working on it, not a flat image you can't touch. The cheaper the model, the more there is to do; if results disappoint, upgrade the model first, then check your usage against Getting Started and the example projects.


Built by Hugo He

I'm a finance professional (CPA · CPV · Consulting Engineer (Investment)) who regularly reviews and edits presentation decks. I wanted AI-generated slides to remain editable in PowerPoint, not flattened into images — so I built this.

Knowing how to use Python and AI agents will matter more and more, and this project is also meant to show how far you can go with just those two things. There's a learning curve if you're starting cold, but it's the curve worth climbing — making a deck is just the excuse; what I'm really pushing is Python and agents.


You Might Also Like

ResearchStudio-Reel

A Microsoft open-source project I recently joined — from paper to talk video, poster, and blog, automating the last mile of research dissemination.

📦 Repo: microsoft/ResearchStudio · 📄 Paper: arXiv:2607.04438

ResearchStudio-Reel demo ResearchStudio-Reel generated poster
BibTeX — if you use ResearchStudio-Reel in your research
@article{xiao2026researchstudioreel,
  title   = {ResearchStudio-Reel: Automate the Last Mile of Research from Paper to Poster, Video, and Blog},
  author  = {Lingao Xiao and Yalun Dai and Yangyu Huang and Qihao Zhao and Wenshan Wu and Hugo He and Ruishuo Chen and Jin Jiang and Qianli Ma and Jiahuan Zhang and Xin Zhang and Ying Xin and Yang Ou and Yan Xia and Scarlett Li and Longbo Huang and Zhipeng Zhang and Yang He and Yap Kim Hui and Yan Lu},
  journal = {arXiv preprint arXiv:2607.04438},
  year    = {2026},
  url     = {https://arxiv.org/abs/2607.04438}
}

Quick Start

1. Prerequisites

All you need to install is Python 3.10+. Everything else comes with one line — pip install -r requirements.txt — after you download the project in Step 3.

Windows — see the dedicated step-by-step guide ⚠️

Windows requires a few extra steps (PATH setup, execution policy, etc.). We wrote a step-by-step guide specifically for Windows users:

📖 Windows Installation Guide — from zero to a working presentation in 10 minutes.

Quick version: download Python from python.org → check "Add to PATH" during install → done; dependencies are installed in Step 3.

macOS / Linux — install and go
# macOS
brew install python

# Ubuntu / Debian
sudo apt install python3 python3-pip
Edge-case fallback — 99% of users don't need this

Pandoc — only needed for legacy document formats: .doc, .odt, .rtf, .tex, .rst, .org, or .typ. .docx, .html, .epub, .ipynb are handled natively by Python — no pandoc required.

# macOS
brew install pandoc

# Ubuntu / Debian
sudo apt install pandoc

2. Pick an Agent

PPT Master runs in any tool with agent capability — read/write files, execute commands, and sustain multi-turn conversation.

Never used one of these? Don't worry — in this project they play exactly one role: an AI chat window that can read and write files. Pick any tool from the table, install it, and you'll only ever use its chat panel. No coding involved.

Author's pick: Claude Code — the environment this project is developed and tested on most thoroughly, as the CLI or the VS Code / JetBrains extension.

Type Examples Notes
IDE-native agent • VS Code architecture (VS Code itself, plus forks & derivatives): Cursor, Trae, Codebuddy IDE, Windsurf, etc.
• Other architectures: Zed, etc.
Editor with a built-in agent
IDE plugin / extension Claude Code (VS Code / JetBrains extension), GitHub Copilot, Cline, etc. Installed inside hosts like VS Code or JetBrains
CLI agent Claude Code CLI, Codex CLI, Gemini CLI, etc. Runs in the terminal; suits scripting, remote, or server use

Model recommendation: for the best results, use Kimi K3 (or Claude) to drive the pipeline, paired with AI image generation — gpt-image-2 (OpenAI) or gemini-3.1-flash-image (Google). Kimi Code, the project sponsor, is a great pick for pay-as-you-go access.

🔑 Want to use Claude / GPT / Gemini but don't have access yet? Project sponsors PackyCode, APIKEY.FUN and RunAPI offer pay-as-you-go access to Claude, GPT, Gemini and more — no subscription required, with exclusive discounts for our users (details at the top of this page).

🔀 Juggling several providers? Once you hold keys from more than one of them, cc-switch — a cross-platform desktop app — lets you one-click switch API providers for Claude Code, Codex, Gemini CLI and more, no manual config editing.

3. Set Up

Option A — Git clone (recommended; requires Git installed): the preferred path, since a clone can pull the latest version at any time.

git clone https://github.com/hugohe3/ppt-master.git
cd ppt-master

Then install dependencies:

pip install -r requirements.txt

Option B — Download ZIP (no Git required; best for a quick trial): click Code → Download ZIP on the GitHub page, then unzip, and install dependencies with pip install -r requirements.txt. A ZIP has no Git history, so it can't git pull — see Updating Later. If that download is too large or fails, grab the skill-only package ppt-master-skill-*.zip (~56 MB, fully functional but without the bundled example decks) from the Releases page instead.

Updating Later

Git clone installs:

python3 skills/ppt-master/scripts/update_repo.py

The script pulls the latest version and syncs Python dependencies when requirements.txt changes.

Download ZIP installs:

ZIP folders do not include Git history,

ppt-master (hugohe3/ppt-master)

Searching Database…

这是什么?PPT Master 是一种 AI 工作流,可以把文档或一个主题变成真正可原生编辑的 PowerPoint 演示文稿,包括原生形状、切换效果、动画、基于数据的图表和表格、根据演讲者备注生成的语音解说,并支持你自己的 .pptx 模板。
这是独立的应用,还是在我的编程助手里运行?它不是独立的应用,而是一种可以在任何支持智能体的 AI 工具中运行的工作流(即 skill)。你只需要和 AI 助手聊天,比如说“用这个 PDF 做一份演示文稿”,它就会在你的电脑上生成并导出 .pptx 文件。
我要怎么把它跑起来?安装 Python 3.10+,选择一款支持智能体的 AI 工具(比如 Claude Code、Codex CLI 或 Cursor),然后 git clone 该仓库(或下载 ZIP 压缩包),再运行 pip install -r requirements.txt。
它支持哪些 AI 工具和模型?任何支持智能体的工具都可以用,比如 Claude Code、Codex CLI、Gemini CLI、Cursor、Windsurf、Zed 等。为获得最佳效果,作者推荐使用 Kimi K3,或上下文窗口较大(约 1M token)的 Claude,并搭配图像生成模型,如 gpt-image-2 或 gemini-3.1-flash-image。
一次生成就能得到完整、精致的演示文稿吗?不能。作者明确表示,不要指望一次就得到完美的演示文稿。它能免去大部分繁琐的工作,但结果仍需要你自己润色;越便宜的模型,留给你修改的工作就越多。
我生成演示文稿时,文档数据会去哪里?除了与你所选 AI 模型之间的必要通信外,整个流程都在你自己的电脑上本地运行,你的源文件和生成的演示文稿都保留在本地。
它免费吗?MIT 许可证对费用意味着什么?PPT Master 本身采用 MIT 许可证,可免费使用;唯一的持续性开销是你所选 AI 模型的 API 调用费用,而不是 PPT 的订阅费。
生成的 PowerPoint 和普通 AI 幻灯片生成器有什么不同?它提供的是 PowerPoint 真正的原生对象模型:带有可正常使用调整手柄的形状和连接线、基于数据的图表和表格,以及(通过模板)真正的幻灯片母版和版式。每个元素都可以在 PowerPoint 中点选和编辑,而不是扁平的图片或文本框。
能套用我自己的品牌 PowerPoint 模板吗?可以。它可以从你的参考文件中提炼出可复用的品牌、风格、版式或演示文稿模板,也可以在保留原有设计的前提下,向现有的 .pptx 文件中填入新内容。
作者为什么不用网页版 AI 幻灯片生成器,而要自己做这个?Hugo He 是一位经常审阅演示文稿的金融从业者,他希望 AI 生成的幻灯片能保持可在 PowerPoint 中编辑,而不是被压平成图片,因此他开发了这款工具,可输出原生、可再编辑的 .pptx 文件。
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