Nexus Office

• 🔥 News
• ✨ Core Features
• 📸 Showcase
• 🧩 Drawio
• 🚀 Quick Start
• 📂 Project Structure
• 🗺️ Roadmap
• 🤝 Contributing

[!IMPORTANT] 🆕 2026-06-13 · Paper to Any Studio / Nexus Upgrade
The online version is being upgraded to the new Paper to Any Studio experience, with a unified Studio workspace, Spaces for personal/project/team files, Labs apps, online Office previews, Credits visibility, and cleaner long-running workflows.
🌐 New public entry: https://paper2any-studio.cpolar.cn/
💻 Mac desktop releases: Paper2Any-Desktop-Releases · public DMG artifacts only; source code remains private/commercial.
⚠️ The public entry is a hosted Studio / Nexus experience and is not identical to the open-source code in this repository. The commercial Studio implementation is not fully open-sourced here.
📢 Full update notice: Paper to Any Studio New Version Update Notice

[!TIP] 🆕 2026-05-30 · Editable PPT Workflow Consolidation
The latest frontend editable PPT workflow is now integrated into Paper2Any, combining outline-assisted generation, canvas editing, gallery review, and paper / AI image insertion into editable decks.
HTML-based editable PPTX export and ONLYOFFICE online editing remain available as optional layers on top of the main editable export workflow.

[!TIP] 🆕 2026-04-24 · Image Model Playground Upgrade
Added a new Image Model Playground page for managed image generation across Nano Banana 2 / Nano Banana Pro / Image 2 / Image 2 All.
The workflow now supports language control, model-specific generation options, batch generation (1 / 2 / 4 / 8 / 16), compressed thumbnail previews, and one-click batch download.

[!TIP] 🆕 2026-04-15 · 2026 Paper Updates
Two Paper2Any-related papers are now listed in the 2026 cycle:
Paper2SysArch: Structure-Constrained System Architecture Generation from Scientific Papers · CVPR 2026 Findings
SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing · ACL 2026 Main

BibTeX

@article{guo2025paper2sysarch,
  title   = {Paper2SysArch: Structure-Constrained System Architecture Generation from Scientific Papers},
  author  = {Guo, Ziyi and Liu, Zhou and Zhang, Wentao},
  journal = {arXiv preprint arXiv:2511.18036},
  year    = {2025},
  note    = {CVPR 2026 Findings}
}

@article{zhang2026sciflowbench,
  title   = {SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing},
  author  = {Zhang, Tong and Lin, Honglin and Liu, Zhou and Chen, Chong and Zhang, Wentao},
  journal = {arXiv preprint arXiv:2602.09809},
  year    = {2026},
  note    = {ACL 2026 Main}
}

[!TIP] 🆕 2026-03-28 · Editable PPT Showcase Refresh
Added two new editable PPT showcase screenshots for the frontend-deck workflow:
a generated multi-slide gallery view and the canvas editing workspace with deck theme lock.

From paper PDFs / images / text to editable scientific figures, slide decks, video scripts, academic posters, and other multimodal content in one click.

Paper2Any currently includes the following sub-capabilities:

• 📊 Paper2Figure - Editable Scientific Figures: Model architecture diagrams, technical roadmaps (PPT + SVG), and experimental plots with editable PPTX output.
• 🧩 Paper2Diagram / Image2Drawio - Editable Diagrams: Generate draw.io diagrams from paper/text or images, with drawio/png/svg export and chat-based edits.
• 🎬 Paper2PPT - Editable Slide Decks: Paper/text/topic to PPT, long-doc support, and built-in table/figure extraction.
• 📝 Paper2Rebuttal: Draft structured rebuttals and revision responses with claims-to-evidence grounding.
• 🖼️ PDF2PPT - Layout-Preserving Conversion: Accurate layout retention for PDF → editable PPTX.
• 🖼️ Image2PPT - Image to Slides: Convert images or screenshots into structured slides.
• 🔥 Image Model Playground: Directly call backend-managed image models with prompt templates, language control, batch generation, compressed previews, and zip download.
• 🎨 PPTPolish - Smart Beautification: AI-based layout optimization and style transfer.
• 🎬 Paper2Video: Generate video scripts and narration assets.
• 🖼️ Paper2Poster - Academic Poster: Turn paper PDFs into poster-ready layouts with configurable sections, logos, and export assets.
• 🔎 Paper2Citation - Citation Explorer: Track citing authors, institutions, and notable downstream works from author names or DOI/paper URLs.
• 📝 Paper2Technical: Produce technical reports and method summaries.
• 📚 Knowledge Base (KB): Ingest/embedding, semantic search, and KB-driven PPT/podcast/mindmap generation.

✨ Upload a paper figure or screenshot as the starting point

✨ Keep the source structure visible before conversion

✨ Convert the image into an editable DrawIO canvas

✨ Generate a model or system diagram directly inside the DrawIO workbench

✨ Refine the generated architecture with chat editing and export-ready layout

_{✨ Rebuttal drafting and revision support}

<sub>✨ Model Architecture Diagram Generation

✨ Model Architecture Diagram Generation</sub>

✨ Technical roadmap workbench: choose route type, input source, model config, and visual template

✨ Generated technical roadmap figure with structured dual-column layout

_{✨ Experimental Plot Generation (Multiple Styles)}

✨ End-to-end PPT generation demo

✨ Paper / text / topic to polished slide deck

✨ Edit slide text directly on canvas while keeping the deck theme locked

✨ Review the generated multi-page gallery before export

✨ AI-assisted outline refinement with targeted rewrite prompts

✨ Structured outline editing down to section and bullet detail

_{✨ Long document support for 40+ slides · Intelligent table extraction and insertion · Version history and iterative deck management}

_{✨ PPT / PDF to narrated video with script confirmation, Aliyun TTS voices, and downloadable output}

PNG poster result

PPT poster result

_{✨ Paper PDF to academic poster with configurable layout, editable poster output, and one-click export}

_{✨ Search authors or papers to inspect citation candidates, institutions, and downstream citation context}

<sub>✨ AI-based Layout Optimization

✨ AI-based Layout Optimization & Style Transfer</sub>

<sub>✨ Intelligent Cutout & Layout Preservation

✨ Image2PPT</sub>

Paper2Any now supports two configuration styles:

• Simple mode: use *.env.simple.example. Recommended for most self-hosted users.
• Advanced mode: use *.env.example. Use this only when you need workflow-specific model/provider overrides.

Quick choice:

cp fastapi_app/.env.simple.example fastapi_app/.env
cp frontend-workflow/.env.simple.example frontend-workflow/.env

If you need fine-grained workflow overrides instead:

cp fastapi_app/.env.example fastapi_app/.env
cp frontend-workflow/.env.example frontend-workflow/.env

# 1. Clone
git clone https://github.com/OpenDCAI/Paper2Any.git
cd Paper2Any

# 2. Configure environment variables
cp fastapi_app/.env.simple.example fastapi_app/.env
cp frontend-workflow/.env.simple.example frontend-workflow/.env
cp deploy/docker.env.example deploy/docker.env

# Internal API auth key. Must match frontend VITE_API_KEY.
BACKEND_API_KEY=your-backend-api-key

# Recommended: let backend own all workflow model choices
APP_BILLING_MODE=free
PAPER2ANY_CONFIG_MODE=simple

# Required: unified text entry
SIMPLE_TEXT_API_URL=https://your-text-gateway/v1
SIMPLE_TEXT_API_KEY=your_text_key

# Optional but recommended: unified image entry
SIMPLE_IMAGE_API_URL=https://your-image-gateway
SIMPLE_IMAGE_API_KEY=your_image_key

# Optional: DrawIO OCR / VLM service
SIMPLE_OCR_API_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
SIMPLE_OCR_API_KEY=your_dashscope_key

# Optional: MinerU official remote API
MINERU_API_BASE_URL=https://mineru.net/api/v4
MINERU_API_KEY=your_mineru_api_key

# Optional: SAM3 segmentation service for PDF2PPT / Image2PPT / Image2Drawio
# SAM3_SERVER_URLS=http://GPU_MACHINE_IP:8001
# SAM3_SERVER_URLS=http://GPU1:8021,http://GPU2:8022

# Optional: Supabase (skip for no auth — core features still work)
# SUPABASE_URL=https://your-project-id.supabase.co
# SUPABASE_ANON_KEY=your_supabase_anon_key

# Must match BACKEND_API_KEY in fastapi_app/.env
VITE_API_KEY=your-backend-api-key

# Usually keep VITE_API_BASE_URL empty in Docker, because nginx proxies /api and /outputs
VITE_API_BASE_URL=

# Frontend display defaults only
VITE_DEFAULT_LLM_API_URL=https://your-text-gateway/v1
VITE_DEFAULT_LLM_MODEL=gpt-4o

# Optional: Supabase (keep consistent with backend)
# VITE_SUPABASE_URL=https://your-project-id.supabase.co
# VITE_SUPABASE_ANON_KEY=your_supabase_anon_key

BACKEND_PORT=8000
FRONTEND_PORT=3000
DOCKER_APP_WORKERS=1

# Optional: enable local SAM3 container by running DOCKER_WITH_SAM3=1 bash deploy/docker-up.sh
SAM3_PORT=8021
SAM3_SERVER_URLS=

# 3. Build + run
bash deploy/docker-up.sh

# Optional: load a pre-downloaded image tar if your deployment ships one
docker load -i /path/to/onlyoffice-documentserver-latest.tar

docker run -d --name paper2any-onlyoffice \
  -p 8082:80 \
  --add-host=host.docker.internal:host-gateway \
  -e JWT_ENABLED=false \
  -e ALLOW_PRIVATE_IP_ADDRESS=true \
  onlyoffice/documentserver:latest

ONLYOFFICE_DOCUMENT_SERVER_URL=/onlyoffice
ONLYOFFICE_THINKFLOW_PUBLIC_URL=http://host.docker.internal:8000
ONLYOFFICE_DOCUMENT_DOWNLOAD_BASE_URL=http://host.docker.internal:8000
ONLYOFFICE_SERVER_DOWNLOAD_URL_BASE=http://127.0.0.1:8082
ONLYOFFICE_JWT_SECRET=

We recommend using Conda to create an isolated environment (Python 3.11).

# 0. Create and activate a conda environment
conda create -n paper2any python=3.11 -y
conda activate paper2any

# 1. Clone repository
git clone https://github.com/OpenDCAI/Paper2Any.git
cd Paper2Any

# 2. Install base dependencies
pip install -r requirements-base.txt

# 3. Install in editable (dev) mode
pip install -e .

Paper2Any involves LaTeX rendering, vector graphics processing as well as PPT/PDF conversion, which require extra dependencies.

The dependency boundary is now:

• requirements-base.txt: shared cross-platform Python runtime
• requirements-paper.txt: paper / PDF / figure extras
• requirements-cu12.txt: NVIDIA CUDA 12 Linux GPU extras
• requirements-system-ubuntu.txt: Ubuntu/Debian system packages, not Python packages

# 1. Paper / PDF / figure Python extras
pip install -r requirements-paper.txt

# 2. NVIDIA GPU runtime extras (Linux + CUDA 12 only)
pip install -r requirements-cu12.txt

# 3. LaTeX engine (tectonic) - recommended via conda
conda install -c conda-forge tectonic -y

# 4. Resolve doclayout_yolo dependency conflicts (Important)
pip install doclayout_yolo --no-deps

# 5. System dependencies (Ubuntu example; full list is mirrored in requirements-system-ubuntu.txt)
sudo apt-get update
sudo apt-get install -y ffmpeg inkscape libreoffice poppler-utils wkhtmltopdf

[!IMPORTANT] ffmpeg, libreoffice/soffice, inkscape, poppler-utils, wkhtmltopdf, and tectonic are external system tools. They are not installed by pip, and deploy/start*.sh does not auto-install them.

export DF_API_KEY=your_api_key_here
export DF_API_URL=xxx  # Optional: if you need a third-party API gateway
export MINERU_DEVICES="0,1,2,3" # Optional: MinerU task GPU resource pool

[!TIP] 📚 For detailed configuration guide, see Configuration Guide for step-by-step instructions on configuring models, environment variables, and starting services.

# Copy backend environment file
cp fastapi_app/.env.example fastapi_app/.env

# Copy frontend environment file
cp frontend-workflow/.env.example frontend-workflow/.env

SUPABASE_URL=https://your-project-id.supabase.co
SUPABASE_ANON_KEY=your_supabase_anon_key

# Default LLM API URL
DEFAULT_LLM_API_URL=http://123.129.219.111:3000/v1/

# Workflow-level defaults
PAPER2PPT_DEFAULT_MODEL=gpt-5.1
PAPER2PPT_DEFAULT_IMAGE_MODEL=gemini-3-pro-image-preview
PDF2PPT_DEFAULT_MODEL=gpt-4o
# ... see .env.example for full list

# DrawIO OCR / VLM
PAPER2DRAWIO_OCR_API_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
PAPER2DRAWIO_OCR_API_KEY=your_dashscope_key

# MinerU official remote API; if MINERU_API_KEY is empty, backend falls back to local MINERU_PORT
MINERU_API_BASE_URL=https://mineru.net/api/v4
MINERU_API_KEY=your_mineru_api_key
MINERU_API_MODEL_VERSION=vlm

# SAM3 segmentation service for PDF2PPT / Image2PPT / Image2Drawio
# One endpoint:
SAM3_SERVER_URLS=http://127.0.0.1:8001
# Or multiple endpoints for load balancing:
# SAM3_SERVER_URLS=http://127.0.0.1:8021,http://127.0.0.1:8022

# Default API URL shown in the UI
VITE_DEFAULT_LLM_API_URL=https://api.apiyi.com/v1

# Available API URLs in the dropdown (comma-separated)
VITE_LLM_API_URLS=https://api.apiyi.com/v1,http://b.apiyi.com:16888/v1,http://123.129.219.111:3000/v1

VITE_SUPABASE_URL=https://your-project.supabase.co
VITE_SUPABASE_ANON_KEY=your-anon-key

[!NOTE] Quick Start: You can skip the .env configuration entirely and use CLI scripts directly with --api-key parameter. See CLI Scripts section below.

bash script/start_local_sam3_dev.sh

[!NOTE] We currently recommend trying Paper2Any on Linux / WSL. If you need to deploy on native Windows, please follow the steps below.

# 0. Create and activate a conda environment
conda create -n paper2any python=3.12 -y
conda activate paper2any

# 1. Clone repository
git clone https://github.com/OpenDCAI/Paper2Any.git
cd Paper2Any

# 2. Install base dependencies
pip install -r requirements-win-base.txt

# 3. Install in editable (dev) mode
pip install -e .

Paper2Any involves LaTeX rendering and vector graphics processing, which require extra dependencies:

# Python dependencies
pip install -r requirements-paper.txt

# NVIDIA GPU runtime extras (Linux only; skip on Windows)
# pip install -r requirements-cu12.txt

# tectonic: LaTeX engine (recommended via conda)
conda install -c conda-forge tectonic -y

🎨 Install Inkscape (SVG/Vector Graphics Processing | Recommended/Required)

1. Download and install (Windows 64-bit MSI): Inkscape Download
2. Add the Inkscape executable directory to the system environment variable Path (example): C:\Program Files\Inkscape\bin\

[!TIP] After configuring the Path, it is recommended to reopen the terminal (or restart VS Code / PowerShell) to ensure the environment variables take effect.

Release page: vllm-windows releases
Recommended version: 0.11.0

pip install vllm-0.11.0+cu124-cp312-cp312-win_amd64.whl

[!IMPORTANT] Please make sure the .whl matches your current environment:

• Python: cp312 (Python 3.12)
• Platform: win_amd64
• CUDA: cu124 (must match your local CUDA / driver)

Paper2Any - Paper Workflow Web Frontend (Recommended)

# Recommended one-click entrypoint on NVIDIA machines
bash deploy/start_nv.sh

Default local addresses:

• Frontend dev server: http://localhost:3000
• Backend health: http://127.0.0.1:8000/health

Useful local deploy commands:

• Start full stack (recommended): bash deploy/start_nv.sh
• Start backend only after loading a deploy profile: set -a && source deploy/profiles/nv.env && set +a && bash deploy/start.sh
• Stop backend: ./deploy/stop.sh
• Restart backend: ./deploy/restart.sh

Notes:

• deploy/start.sh reads deploy/app_config.sh, but it does not load deploy/profiles/*.env by itself.
• deploy/start_nv.sh is the safe one-click entrypoint because it loads deploy/profiles/nv.env, prepares local models, starts model servers, then starts backend and frontend.
• If you change APP_PORT, update the frontend proxy target in frontend-workflow/vite.config.ts as well.

Configure Frontend Proxy

Modify server.proxy in frontend-workflow/vite.config.ts:

export default defineConfig({
  plugins: [react()],
  server: {
    port: 3000,
    open: true,
    allowedHosts: true,
    proxy: {
      '/api': {
        target: 'http://127.0.0.1:8000',  // FastAPI backend address
        changeOrigin: true,
      },
      '/outputs': {
        target: 'http://127.0.0.1:8000',
        changeOrigin: true,
      },
    },
  },
})

Visit http://localhost:3000.

Windows: Load MinerU Pre-trained Model

# Start in PowerShell
vllm serve opendatalab/MinerU2.5-2509-1.2B `
  --host 127.0.0.1 `
  --port 8010 `
  --logits-processors mineru_vl_utils:MinerULogitsProcessor `
  --gpu-memory-utilization 0.6 `
  --trust-remote-code `
  --enforce-eager

# Recommended one-click entrypoint on NVIDIA machines
bash deploy/start_nv.sh

Visit http://localhost:3000. Backend health is available at http://127.0.0.1:8000/health by default.

Paper2Any provides standalone CLI scripts that accept command-line parameters for direct workflow execution without requiring the web frontend/backend.

Configure API access via environment variables (optional):

export DF_API_URL=https://api.openai.com/v1  # LLM API URL
export DF_API_KEY=sk-xxx                      # API key
export DF_MODEL=gpt-4o                        # Default model

1. Paper2Figure CLI - Generate scientific figures (3 types)

# Generate model architecture diagram from PDF
python script/run_paper2figure_cli.py \
  --input paper.pdf \
  --graph-type model_arch \
  --api-key sk-xxx

# Generate technical roadmap from text
python script/run_paper2figure_cli.py \
  --input "Transformer architecture with attention mechanism" \
  --input-type TEXT \
  --graph-type tech_route

# Generate experimental data visualization
python script/run_paper2figure_cli.py \
  --input paper.pdf \
  --graph-type exp_data

Graph types: model_arch (model architecture), tech_route (technical roadmap), exp_data (experimental plots)

2. Paper2PPT CLI - Convert papers to PPT presentations

# Basic usage
python script/run_paper2ppt_cli.py \
  --input paper.pdf \
  --api-key sk-xxx \
  --page-count 15

# With custom style
python script/run_paper2ppt_cli.py \
  --input paper.pdf \
  --style "Academic style; English; Modern design" \
  --language en

3. PDF2PPT CLI - One-click PDF to editable PPT

# Basic conversion (no AI enhancement)
python script/run_pdf2ppt_cli.py --input slides.pdf

# With AI enhancement
python script/run_pdf2ppt_cli.py \
  --input slides.pdf \
  --use-ai-edit \
  --api-key sk-xxx

4. Image2PPT CLI - Convert images to editable PPT

# Basic conversion
python script/run_image2ppt_cli.py --input screenshot.png

# With AI enhancement
python script/run_image2ppt_cli.py \
  --input diagram.jpg \
  --use-ai-edit \
  --api-key sk-xxx

5. PPT2Polish CLI - Beautify existing PPT files

# Basic beautification
python script/run_ppt2polish_cli.py \
  --input old_presentation.pptx \
  --style "Academic style, clean and elegant" \
  --api-key sk-xxx

# With reference image for style consistency
python script/run_ppt2polish_cli.py \
  --input old_presentation.pptx \
  --style "Modern minimalist style" \
  --ref-img reference_style.png \
  --api-key sk-xxx

[!NOTE] System Requirements for PPT2Polish:

• LibreOffice: sudo apt-get install libreoffice (Ubuntu/Debian)
• pdf2image: pip install pdf2image
• poppler-utils: sudo apt-get install poppler-utils

All CLI scripts support these common options:

• --api-url URL - LLM API URL (default: from DF_API_URL env var)
• --api-key KEY - API key (default: from DF_API_KEY env var)
• --model NAME - Text model name (default: varies by script)
• --output-dir DIR - Custom output directory (default: outputs/cli/{script_name}/{timestamp})
• --help - Show detailed help message

For complete parameter documentation, run any script with --help:

python script/run_paper2figure_cli.py --help

Paper2Any/
├── dataflow_agent/          # Core codebase
│   ├── agentroles/         # Agent definitions
│   │   └── paper2any_agents/ # Paper2Any-specific agents
│   ├── workflow/           # Workflow definitions
│   ├── promptstemplates/   # Prompt templates
│   └── toolkits/           # Toolkits (drawing, PPT generation, etc.)
├── fastapi_app/            # Backend API service
├── frontend-workflow/      # Frontend web interface
├── static/                 # Static assets
├── script/                 # Script tools
└── tests/                  # Test cases

Feature	Status	Sub-features
📊 Paper2Figure Editable Scientific Figures
🧩 Paper2Diagram Drawio Diagrams
🎬 Paper2PPT Editable Slide Decks
🖼️ PDF2PPT Layout-Preserving Conversion
🖼️ Image2PPT Image to Slides
🎨 PPTPolish Smart Beautification
📚 Knowledge Base KB Workflows
🎬 Paper2Video Video Script Generation

This is the historical contribution section for the legacy codebase. New product features and architecture changes are no longer synchronized to this repository, and new feature pull requests are not currently planned for review. Existing issues and discussions remain available as a community archive.

This project is licensed under Apache License 2.0.