paper-2-web

What this skill does

# Paper2All: Academic Paper Transformation Pipeline

## Overview

This skill enables the transformation of academic papers into multiple promotional and presentation formats using the Paper2All autonomous pipeline. The system converts research papers (LaTeX or PDF) into three primary outputs:

1. **Paper2Web**: Interactive, explorable academic homepages with layout-aware design
2. **Paper2Video**: Professional presentation videos with narration, slides, and optional talking-head
3. **Paper2Poster**: Print-ready conference posters with professional layouts

The pipeline uses LLM-powered content extraction, design generation, and iterative refinement to create high-quality outputs suitable for conferences, journals, preprint repositories, and academic promotion.

## When to Use This Skill

Use this skill when:

- **Creating conference materials**: Posters, presentation videos, and companion websites for academic conferences
- **Promoting research**: Converting published papers or preprints into accessible, engaging web formats
- **Preparing presentations**: Generating video abstracts or full presentation videos from paper content
- **Disseminating findings**: Creating promotional materials for social media, lab websites, or institutional showcases
- **Enhancing preprints**: Adding interactive homepages to bioRxiv, arXiv, or other preprint submissions
- **Batch processing**: Generating promotional materials for multiple papers simultaneously

**Trigger phrases**:
- "Convert this paper to a website"
- "Generate a conference poster from my LaTeX paper"
- "Create a video presentation from this research"
- "Make an interactive homepage for my paper"
- "Transform my paper into promotional materials"
- "Generate a poster and video for my conference talk"

## Visual Enhancement with Scientific Schematics

**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**

If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic

**For new documents:** Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.

**How to generate schematics:**
```bash
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
```

The AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory

**When to add schematics:**
- Paper transformation pipeline diagrams
- Website layout architecture diagrams
- Video production workflow illustrations
- Poster design process flowcharts
- Content extraction diagrams
- System architecture visualizations
- Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

---

## Core Capabilities

### 1. Paper2Web: Interactive Website Generation

Converts papers into layout-aware, interactive academic homepages that go beyond simple HTML conversion.

**Key Features**:
- Responsive, multi-section layouts adapted to paper content
- Interactive figures, tables, and citations
- Mobile-friendly design with navigation
- Automatic logo discovery (with Google Search API)
- Aesthetic refinement and quality assessment

**Best For**: Post-publication promotion, preprint enhancement, lab websites, permanent research showcases

→ **See `references/paper2web.md` for detailed documentation**

---

### 2. Paper2Video: Presentation Video Generation

Generates professional presentation videos with slides, narration, cursor movements, and optional talking-head video.

**Key Features**:
- Automated slide generation from paper structure
- Natural-sounding speech synthesis
- Synchronized cursor movements and highlights
- Optional talking-head video using Hallo2 (requires GPU)
- Multi-language support

**Best For**: Video abstracts, conference presentations, online talks, course materials, YouTube promotion

→ **See `references/paper2video.md` for detailed documentation**

---

### 3. Paper2Poster: Conference Poster Generation

Creates print-ready academic posters with professional layouts and visual design.

**Key Features**:
- Custom poster dimensions (any size)
- Professional design templates
- Institution branding support
- QR code generation for links
- High-resolution output (300+ DPI)

**Best For**: Conference poster sessions, symposiums, academic exhibitions, virtual conferences

→ **See `references/paper2poster.md` for detailed documentation**

---

## Quick Start

### Prerequisites

1. **Install Paper2All**:
   ```bash
   git clone https://github.com/YuhangChen1/Paper2All.git
   cd Paper2All
   conda create -n paper2all python=3.11
   conda activate paper2all
   pip install -r requirements.txt
   ```

2. **Configure API Keys** (create `.env` file):
   ```
   OPENAI_API_KEY=your_openai_api_key_here
   # Optional: GOOGLE_API_KEY and GOOGLE_CSE_ID for logo search
   ```

3. **Install System Dependencies**:
   - LibreOffice (document conversion)
   - Poppler utilities (PDF processing)
   - NVIDIA GPU with 48GB (optional, for talking-head videos)

→ **See `references/installation.md` for complete installation guide**

---

### Basic Usage

**Generate All Components** (website + poster + video):
```bash
python pipeline_all.py \
  --input-dir "path/to/paper" \
  --output-dir "path/to/output" \
  --model-choice 1
```

**Generate Website Only**:
```bash
python pipeline_all.py \
  --input-dir "path/to/paper" \
  --output-dir "path/to/output" \
  --model-choice 1 \
  --generate-website
```

**Generate Poster with Custom Size**:
```bash
python pipeline_all.py \
  --input-dir "path/to/paper" \
  --output-dir "path/to/output" \
  --model-choice 1 \
  --generate-poster \
  --poster-width-inches 60 \
  --poster-height-inches 40
```

**Generate Video** (lightweight pipeline):
```bash
python pipeline_light.py \
  --model_name_t gpt-4.1 \
  --model_name_v gpt-4.1 \
  --result_dir "path/to/output" \
  --paper_latex_root "path/to/paper"
```

→ **See `references/usage_examples.md` for comprehensive workflow examples**

---

## Workflow Decision Tree

Use this decision tree to determine which components to generate:

```
User needs promotional materials for paper?
│
├─ Need permanent online presence?
│  └─→ Generate Paper2Web (interactive website)
│
├─ Need physical conference materials?
│  ├─→ Poster session? → Generate Paper2Poster
│  └─→ Oral presentation? → Generate Paper2Video
│
├─ Need video content?
│  ├─→ Journal video abstract? → Generate Paper2Video (5-10 min)
│  ├─→ Conference talk? → Generate Paper2Video (15-20 min)
│  └─→ Social media? → Generate Paper2Video (1-3 min)
│
└─ Need complete package?
   └─→ Generate all three components
```

## Input Requirements

### Supported Input Formats

**1. LaTeX Source** (Recommended):
```
paper_directory/
├── main.tex              # Main paper file
├── sections/             # Optional: split sections
├── figures/              # All figure files
├── tables/               # Table files
└── bibliography.bib      # References
```

**2. PDF**:
- High-quality PDF with embedded fonts
- Selectable text (not scanned images)
- High-resolution figures (300+ DPI preferred)

### Input Organization

**Single Paper**:
```bash
input/
└── paper_name/
    ├── main.tex (or paper.pdf)
    ├── figures/
    └── bibliography.bib
```

**Multiple Papers** (batch processing):
```bash
input/
├── paper1/
│   └── main.tex
├── paper2/
│   └── main.tex
└── paper3/
    └── main.tex
```

## Common Parameters

### Model Selection
- `--model-choice 1`: GPT-4 (best balance of