PPT Master — AI generates native PowerPoint from any document

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💼 I'm open to new opportunities. Investment background (CPA · CPV · Consulting Engineer), also building AI tools and open source. Happy to talk about any opportunity: [email protected] · hehugo.com.

🆕 I built a construction project economic evaluation site: cs.hehugo.com (in Chinese) — the wind, solar and storage templates are now open to everyone; just register and use them (a comparable module in one commercial package sells for ¥100,000).

❤️ Sponsors

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

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

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.

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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:

• Transparent, predictable cost — free and open source; the only cost is your AI model usage, with no PPT subscription on top
• Data stays local — apart from AI model calls and the search, image, and speech services you choose to enable, the entire pipeline runs on your machine
• No platform lock-in — any agent-capable AI IDE can drive it; Claude, GPT, Gemini, Kimi, and other models all work

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.

This is the beginning of the README. Read the rest at the original. Read the full README ↗