Paper2Slides: From Paper to Presentation in One Click

✨ Never Build Slides from Scratch Again ✨

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🎯 What is Paper2Slides?

Turns your research papers, reports, and documents into professional slides & posters in minutes.

✨ Key Features

📄 Universal Document Support<br> Seamlessly process PDF, Word, Excel, PowerPoint, Markdown, and multiple file formats simultaneously.
🎯 Comprehensive Content Extraction<br> RAG-powered mechanism ensures every critical insight, figure, and data point is captured with precision.
🔗 Source-Linked Accuracy<br> Maintains direct traceability between generated content and original sources, eliminating information drift.
🎨 Custom Styling Freedom<br> Choose from professional built-in themes or describe your vision in natural language for custom styling.
⚡ Lightning-Fast Generation<br> Instant preview mode enables rapid experimentation and real-time refinements.
💾 Seamless Session Management<br> Advanced checkpoint system preserves all progress—pause, resume, or switch themes instantly without loss.
✨ Professional-Grade Visuals<br> Deliver polished, presentation-ready slides and posters with publication-quality design standards.

⚡ Easy as One Command

# One command to generate slides from a paper
python -m paper2slides --input paper.pdf --output slides --style doraemon --length medium --fast --parallel 2

🔥 News

[2025.12.09] Added parallel slide generation (--parallel) for faster processing
[2025.12.08] Paper2Slides is now open source!

🎨 Custom Styling Showcase

<div align="center"> <table> <tr> <td align="center" width="290"><img src="assets/doraemon_poster.png?v=2" width="280"/><br/><code>doraemon</code></td> <td align="center" width="290"><img src="assets/academic_poster.png?v=2" width="280"/><br/><code>academic</code></td> <td align="center" width="290"><img src="assets/totoro_poster.png?v=2" width="280"/><br/><code>custom</code></td> </tr> </table> <table> <tr> <td align="center" width="290"><a href="assets/doraemon_slides.pdf"><img src="assets/doraemon_slides_preview.png?v=2" width="280"/></a><br/><code>doraemon</code></td> <td align="center" width="290"><a href="assets/academic_slides.pdf"><img src="assets/academic_slides_preview.png?v=2" width="280"/></a><br/><code>academic</code></td> <td align="center" width="290"><a href="assets/totoro_slides.pdf"><img src="assets/totoro_slides_preview.png?v=2" width="280"/></a><br/><code>custom</code></td> </tr> </table>

<sub>✨ Multiple styles available — simply modify the <code>--style</code> parameter<br/> Examples from <a href="https://arxiv.org/abs/2512.02556">DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models</a></sub>

</div> <details> <summary><b>💡 Custom Style Example: Totoro Theme</b></summary>

--style "Studio Ghibli anime style with warm whimsical aesthetic. Use soft watercolor Morandi tones with light cream background, muted sage green and dusty pink accents. Totoro character can appear as a friendly guide relating to the content, with nature elements like soft clouds or leaves."

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🌐 Paper2Slides Web Interface

🏃 Quick Start

1. Environment Setup

# Clone repository
git clone https://github.com/HKUDS/Paper2Slides.git
cd Paper2Slides

# Create and activate conda environment
conda create -n paper2slides python=3.12 -y
conda activate paper2slides

# Install dependencies
pip install -r requirements.txt

[!NOTE] Create a .env file in paper2slides/ directory with your API keys. Refer to paper2slides/.env.example for the required variables.

2. Command Line Usage

# Basic usage - generate slides from a paper
python -m paper2slides --input paper.pdf --output slides --length medium

# Generate poster with custom style
python -m paper2slides --input paper.pdf --output poster --style "minimalist with blue theme" --density medium

# Fast mode
python -m paper2slides --input paper.pdf --output slides --fast

# Enable parallel generation (2 workers by default)
python -m paper2slides --input paper.pdf --output slides --parallel 2

# List all processed outputs
python -m paper2slides --list

CLI Options:

Option	Description	Default
`--input, -i`	Input file(s) or directory	Required
`--output`	Output type: `slides` or `poster`	`poster`
`--content`	Content type: `paper` or `general`	`paper`
`--style`	Style: `academic`, `doraemon`, or custom	`doraemon`
`--length`	Slides length: `short`, `medium`, `long`	`short`
`--density`	Poster density: `sparse`, `medium`, `dense`	`medium`
`--fast`	Fast mode: skip RAG indexing	`false`
`--parallel`	Enable parallel slide generation: `--parallel` uses 2 workers, `--parallel N` uses N workers	`1` (sequential without this option)
`--from-stage`	Force restart from stage: `rag`, `summary`, `plan`, `generate`	Auto-detect
`--debug`	Enable debug logging	`false`

💾 Checkpoint & Resume:

Paper2Slides intelligently saves your progress at every key stage, allowing you to:

Scenario	Command
Resume after interruption	Just run the same command again — it auto-detects and continues
Change style only	Add `--from-stage plan` to skip re-parsing
Regenerate images	Add `--from-stage generate` to keep the same plan
Full restart	Add `--from-stage rag` to start from scratch

[!TIP] Checkpoints are auto-saved. Just run the same command to resume. Use --from-stage only to force restart from a specific stage.

3. Web Interface

Launch both backend and frontend services:

./scripts/start.sh

Or start services independently:

# Terminal 1: Start backend API
./scripts/start_backend.sh

# Terminal 2: Start frontend
./scripts/start_frontend.sh

Access the web interface at http://localhost:5173 (default)

🏗️ Paper2Slides Framework

Paper2Slides transforms documents through a 4-stage pipeline designed for reliability and efficiency:

Stage	Description	Checkpoint	Output
🔍 RAG	Parse documents and construct intelligent retrieval index using RAG	`checkpoint_rag.json`	Searchable knowledge base
📊 Analysis	Extract document structure, identify key figures, tables, and content hierarchy	`checkpoint_summary.json`	Structured content map
📋 Planning	Generate optimized content layout and slide/poster organization strategy	`checkpoint_plan.json`	Presentation blueprint
🎨 Creation	Render final high-quality slides and poster visuals	Output directory	Polished presentation materials

💾 Smart Recovery System

Each stage automatically saves progress checkpoints, enabling seamless resumption from any point if the process is interrupted—no need to start over.

Fast Mode vs Normal Mode

Mode	Processing Pipeline	Use Cases
Normal	Complete RAG indexing with deep document analysis	Complex research papers, lengthy documents, multi-section content
Fast	Skip RAG indexing, direct LLM query	Short documents, instant previews, quick revisions

Use --fast when:

Document (text + figures) is short enough to fit in LLM context
Quick preview/iteration needed
Don't want to wait for RAG indexing

Use normal mode (default) when:

Document is long or has many figures
Multiple files to process together
Need retrieval for better context selection

⚙️ Configuration

Output Directory Structure

outputs/
├── <project_name>/
│   ├── <content_type>/                   # paper or general
│   │   ├── <mode>/                       # fast or normal
│   │   │   ├── checkpoint_rag.json       # RAG query results & parsed file paths
│   │   │   ├── checkpoint_summary.json   # Extracted content, figures, tables
│   │   │   ├── summary.md                # Human-readable summary
│   │   │   └── <config_name>/            # e.g., slides_doraemon_medium
│   │   │       ├── state.json            # Current pipeline state
│   │   │       ├── checkpoint_plan.json  # Content plan for slides/poster
│   │   │       └── <timestamp>/          # Generated outputs
│   │   │           ├── slide_01.png
│   │   │           ├── slide_02.png
│   │   │           ├── ...
│   │   │           └── slides.pdf        # Final PDF output
│   │   └── rag_output/                   # RAG index storage
│   └── ...
└── ...

Checkpoint Files:

File	Description	Reusable When
`checkpoint_rag.json`	Parsed document content	Same input files
`checkpoint_summary.json`	Figures, tables, structure	Same input files
`checkpoint_plan.json`	Content layout plan	Same style & length/density

Style Configuration

Style	Description
`academic`	Clean, professional academic presentation style
`doraemon`	Colorful, friendly style with illustrations
`custom`	Any text description for LLM-generated style

Image Generation Providers

Set IMAGE_GEN_PROVIDER in paper2slides/.env to choose the backend:
- openrouter (default): uses IMAGE_GEN_API_KEY, IMAGE_GEN_BASE_URL, and IMAGE_GEN_MODEL (default google/gemini-3-pro-image-preview)
- google: uses the official Gemini API at GOOGLE_GENAI_BASE_URL (default https://generativelanguage.googleapis.com/v1beta), IMAGE_GEN_API_KEY, IMAGE_GEN_MODEL (default models/gemini-3-pro-image-preview, must be image-capable), and IMAGE_GEN_RESPONSE_MIME_TYPE (default text/plain; use text types if your model does not support image responses)
Reference figures are sent as inline data when supported (Google) or as image_url attachments (OpenRouter).

Image Generation Notes

[!TIP] By default Paper2Slides uses gemini-3-pro-image-preview (OpenRouter) for image generation; you can switch to an image-capable Google Gemini model (e.g., models/gemini-1.5-flash) via IMAGE_GEN_PROVIDER=google. Key findings:

Mood Keywords: Words like "warm", "elegant", "vibrant" strongly influence the overall color palette

Layout vs Style: Fine-grained layout instructions ground well; fine-grained element styling does not

Prompt Length: Simple prompts generally outperform detailed ones

Multi-slide Generation: Native multi-image output is story-like; for consistent slides, we use iterative single-image generation

📁 Code Structure

Module	Description
`paper2slides/core/`	Pipeline orchestration, 4-stage execution
`paper2slides/raganything/`	Document parsing & RAG indexing
`paper2slides/summary/`	Content extraction: figures, tables, paper structure
`paper2slides/generator/`	Content planning & image generation
`api/`	FastAPI backend for web interface
`frontend/`	React frontend (Vite + TailwindCSS)

<details> <summary><b>Click to expand full project structure</b></summary>

Paper2Slides/
├── paper2slides/                 # Core library
│   ├── main.py                   # CLI entry point
│   ├── core/
│   │   ├── pipeline.py           # Main pipeline orchestration
│   │   ├── state.py              # Checkpoint state management
│   │   └── stages/
│   │       ├── rag_stage.py      # Stage 1: Parse & index
│   │       ├── summary_stage.py  # Stage 2: Extract content
│   │       ├── plan_stage.py     # Stage 3: Plan layout
│   │       └── generate_stage.py # Stage 4: Generate images
│   │
│   ├── raganything/
│   │   ├── raganything.py        # RAG processor
│   │   └── parser.py             # Document parser
│   │
│   ├── summary/
│   │   ├── paper.py              # Paper structure extraction
│   │   └── extractors/           # Figure/table extractors
│   │
│   ├── generator/
│   │   ├── content_planner.py    # Slide/poster planning
│   │   └── image_generator.py    # Image generation
│   │
│   ├── prompts/                  # LLM prompt templates
│   └── utils/                    # Utilities
│
├── api/server.py                 # FastAPI backend
├── frontend/src/                 # React frontend
└── scripts/                      # Shell scripts (start/stop)

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🙏 Related Open-Sourced Projects

LightRAG: Graph-Empowered RAG
RAG-Anything: Multi-Modal RAG
VideoRAG: RAG with Extremely-Long Videos

🌟Found Paper2Slides helpful? Star us on GitHub!

🚀 Turn any document into professional presentations in minutes!

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