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ViviDoc generates self-contained interactive HTML documents from a single topic input. It designs a purpose-built visual style, structures the document using the SRTC Interaction Spec (State · Render · Transition · Constraint), and writes a single .html file with KaTeX math and Canvas visualizations — no build step, no server. Your AI coding agent (Claude Code, Codex, etc.) is the harness — no external API key required.

Accepted at ACL 2026 System Demonstrations — arXiv:2603.01912

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🚀 Quick Start

curl -sSL https://raw.githubusercontent.com/MisterBrookT/vividoc/main/install.sh | bash

Installs /vividoc, /vividoc-learn, and /vividoc-slides into ~/.claude/commands/. Your harness is the model — no separate API key needed.

/vividoc Fourier Transform

/vividoc-learn https://ncase.me/trust/

/vividoc-slides https://example.edu/lecture.pdf

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📚 Showcase

→ vividoc.vercel.app

Document	Domain	Interaction
Fourier Transform	Physics & Math	Temporal Control
Lorenz Attractor	Physics & Math	Parameter Exploration
Action Potential	Biology	Temporal Control
DNA Replication	Biology	Temporal Control
Gradient Descent	Machine Learning	Direct Manipulation
Bias–Variance Tradeoff	Machine Learning	Parameter Exploration
Shannon Entropy	Information Theory	Parameter Exploration
Huffman Coding	Information Theory	Freeform Construction

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🗺️ Roadmap

ViviDoc Learn (concept)

An email-based personalized learning product built on top of ViviDoc's generative visualization engine:

• Assess — a short interactive quiz at signup determines the learner's current level on a chosen topic
• Generate — ViviDoc produces a personalized interactive document (or short quiz) for each learning unit
• Deliver — content is emailed on a daily/weekly cadence, in the learner's preferred language
• Test — each delivery includes a small embedded quiz; results feed the next generation cycle
• Progress — staged curriculum that adapts to demonstrated understanding over time

This would be a separate hosted product ("ViviDoc Learn") from the current open-source harness skill, requiring server-side generation, email infrastructure, and subscription accounts. The current harness-skill approach remains the core open-source offering.

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🔬 Development

uv sync --dev
uv run pytest
cd frontend && npm install && npm run dev

Baselines (AutoGen, CAMEL, MetaGPT, naive): uv run python benchmark/run.py --baseline autogen

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📄 Citation

@article{tang2026vividoc,
  title   = {{ViviDoc}: Generating Interactive Documents through Human-Agent Collaboration},
  author  = {Tang, Yinghao and Xie, Yupeng and Feng, Yingchaojie and
             Lan, Tingfeng and Lao, Jiale and Cheng, Yue and Chen, Wei},
  journal = {arXiv preprint arXiv:2603.27991},
  year    = {2026},
  url     = {https://arxiv.org/abs/2603.27991}
}

@inproceedings{tang2026demonstrating,
  title     = {Demonstrating {ViviDoc}: Generating Interactive Documents through Human-Agent Collaboration},
  author    = {Tang, Yinghao and Xie, Yupeng and Feng, Yingchaojie and Lan, Tingfeng and Chen, Wei},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics: System Demonstrations},
  year      = {2026},
  url       = {https://arxiv.org/abs/2603.01912}
}

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