[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-92682":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":16,"stars7d":16,"stars30d":17,"stars90d":16,"forks30d":16,"starsTrendScore":16,"compositeScore":18,"rankGlobal":10,"rankLanguage":10,"license":19,"archived":20,"fork":20,"defaultBranch":21,"hasWiki":20,"hasPages":20,"topics":22,"createdAt":10,"pushedAt":10,"updatedAt":23,"readmeContent":24,"aiSummary":25,"trendingCount":16,"starSnapshotCount":16,"syncStatus":26,"lastSyncTime":27,"discoverSource":28},92682,"lingbot-world-v2","Robbyant\u002Flingbot-world-v2","Robbyant","Infinite Worlds with Versatile Interactions","https:\u002F\u002Ftechnology.robbyant.com\u002Flingbot-world-v2",null,"Python",1076,62,120,1,0,555,63.4,"Other",false,"main",[],"2026-07-22 04:02:06","\u003Cdiv align=\"center\">\n  \u003Cimg src=\"assets\u002Fteaser.png\">\n\n\u003Ch1>Infinite Worlds with Versatile Interactions\u003C\u002Fh1>\n\nRobbyant Team\n\n\u003C\u002Fdiv>\n\n\n\u003Cdiv align=\"center\">\n\n[![Page](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%8C%90%20Project%20Page-Demo-00bfff)](https:\u002F\u002Ftechnology.robbyant.com\u002Flingbot-world-v2)\n[![Tech Report](https:\u002F\u002Fimg.shields.io\u002Fstatic\u002Fv1?label=Paper&message=PDF&color=red&logo=arxiv)](https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.07534)\n[![Model](https:\u002F\u002Fimg.shields.io\u002Fstatic\u002Fv1?label=%F0%9F%A4%97%20Model&message=HuggingFace&color=yellow)](https:\u002F\u002Fhuggingface.co\u002Frobbyant\u002Flingbot-world-v2-14b-causal-fast)\n[![Model](https:\u002F\u002Fimg.shields.io\u002Fstatic\u002Fv1?label=%F0%9F%A4%96%20Model&message=ModelScope&color=purple)](https:\u002F\u002Fmodelscope.cn\u002Fmodels\u002FRobbyant\u002Flingbot-world-v2-14b-causal-fast)\n[![License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-CC%20BY--NC--SA%204.0-green)](LICENSE.txt)\n\n\n\u003C\u002Fdiv>\n\n-----\n\nWe present **LingBot-World 2.0** (also known as **LingBot-World-Infinity**), an advanced iteration of [LingBot-World](https:\u002F\u002Ftechnology.robbyant.com\u002Flingbot-world) featuring four distinct upgrades.\n- **Unbounded Interaction Horizon**: Our model achieves an unbounded interaction horizon while maintaining consistent output quality, benefiting from a carefully crafted causal pretraining paradigm.\n- **Rapid Response Time**: Through distilling a real-time variant from the base model, our system guarantees rapid response time, sufficient to drive 720p video streams at 60 fps.\n- **Highly Diverse Interactive Elements**: Compared to the previous version, this update introduces highly diverse interactive elements, comprising a broader spectrum of actions (*e.g.*, attacking, archery, spell-casting, and shooting) alongside a richer variety of text-driven events.\n- **Agentic Harness**: We pioneer the integration of an agentic harness within the domain of world modeling, wherein a pilot agent is tasked with planning and executing character behaviors, while a director agent is responsible for synthesizing novel environmental elements as the scene progresses.\n\n\n## 🚀 Try it now\nThe real-time version of LingBot-World-Infinity is available on two platforms. We thank [Reactor](https:\u002F\u002Fwww.reactor.inc\u002Flingbot-world-v2) and [LingGuang](https:\u002F\u002Fwww.lingguang.com\u002Fsupport) for their support:\n- **International (Web)**: Experience it on [Reactor](https:\u002F\u002Fwww.reactor.inc\u002Flingbot-world-v2).\n- **Domestic (Mobile)**: Experience it on [LingGuang](https:\u002F\u002Fwww.lingguang.com\u002Fsupport).\n\n> **Note:** Reactor and LingGuang provide a convenient way to try LingBot-World-Infinity in real time. In our official setup, the model runs at full capability. To experience our official demo, join us at [WAIC 2026](https:\u002F\u002Fwaica2026.worldaic.com.cn\u002F).\n\n## 🎬 Demo Gallery\n\n\u003Cdiv align=\"center\">\n  \u003Cvideo src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fab2a81a8-56f7-4328-a5cc-80477151c61c\" width=\"100%\" poster=\"\"> \u003C\u002Fvideo>\n  \u003Cvideo src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F2a1a4864-7809-4bff-ab08-32bd30099581\" width=\"100%\" poster=\"\"> \u003C\u002Fvideo>\n  \u003Cvideo src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Ff1059674-a7e7-45b1-8738-627d811d7bee\" width=\"100%\" poster=\"\"> \u003C\u002Fvideo>\n  \u003Cvideo src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F538097aa-6c02-48e1-9802-563416f6191a\" width=\"100%\" poster=\"\"> \u003C\u002Fvideo>\n  \u003Cvideo src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002Fe7e0749a-9ca9-4502-a846-661c41b48096\" width=\"100%\" poster=\"\"> \u003C\u002Fvideo>\n  \u003Cvideo src=\"https:\u002F\u002Fgithub.com\u002Fuser-attachments\u002Fassets\u002F09970b6c-990d-4e40-bd8b-82755400fa9d\" width=\"100%\" poster=\"\"> \u003C\u002Fvideo>\n\u003C\u002Fdiv>\n\n\n\u003Cp align=\"center\">\u003Ci>✨ For more high-fidelity and compelling demos, please visit our \u003Ca href=\"https:\u002F\u002Ftechnology.robbyant.com\u002Flingbot-world-v2\">Project Page\u003C\u002Fa>.\u003C\u002Fi>\u003C\u002Fp>\n\n## 🔥 News\n- Jul. 9, 2026: 🎉 We release the technical report, inference code, and models for LingBot-World-Infinity.\n\n## 📋 TODO\n- [x] Release the causal-fast inference code and model of the 14B model\n- [ ] Release the causal-pretrained model of the 14B model\n- [ ] Release the bidirectional model of the 14B model\n- [ ] Release the causal-fast and causal-pretrained models of the 1.3B model\n\n## ⚙️ Quick Start\nThis codebase is built upon [Wan2.2](https:\u002F\u002Fgithub.com\u002FWan-Video\u002FWan2.2). Please refer to their documentation for installation instructions.\n### Installation\nClone the repo:\n```sh\ngit clone https:\u002F\u002Fgithub.com\u002Frobbyant\u002Flingbot-world-v2.git\ncd lingbot-world-v2\n```\nInstall dependencies:\n```sh\n# Ensure torch >= 2.4.0\npip install -r requirements.txt\n```\nInstall [`flash_attn`](https:\u002F\u002Fgithub.com\u002FDao-AILab\u002Fflash-attention):\n```sh\npip install flash-attn --no-build-isolation\n```\n### Model Download\n\n| Model | Model Type | Model Size | Download Links |\n| :---  | :--- | :--- | :--- |\n| **lingbot-world-v2-14b-causal-fast** | causal-fast | 14B | 🤗 [HuggingFace](https:\u002F\u002Fhuggingface.co\u002Frobbyant\u002Flingbot-world-v2-14b-causal-fast) 🤖 [ModelScope](https:\u002F\u002Fwww.modelscope.cn\u002Fmodels\u002FRobbyant\u002Flingbot-world-v2-14b-causal-fast) |\n| **lingbot-world-v2-14b-causal-pretrain** | causal-pretrain | 14B | TODO |\n\nDownload models using huggingface-cli:\n```sh\npip install \"huggingface_hub[cli]\"\nhuggingface-cli download robbyant\u002Flingbot-world-v2-14b-causal-fast --local-dir .\u002Flingbot-world-v2-14b-causal-fast\n```\nDownload models using modelscope-cli:\n ```sh\npip install modelscope\nmodelscope download robbyant\u002Flingbot-world-v2-14b-causal-fast --local_dir .\u002Flingbot-world-v2-14b-causal-fast\n```\n\n### Inference\n\nWe provide `generate.py` for causal inference with KV caching, which processes video frames chunk-by-chunk instead of all at once.\n\u003C!-- The `--infer_mode` flag selects the inference mode:\n\n| infer_mode | Model | Sampling |\n| :--- | :--- | :--- |\n| `causal_fast` (default) | Distilled few-step model (`LingBot-World-Fast`) | 4 steps per chunk, no CFG |\n| `causal_pretrain` | Pretrained causal model | 40 steps per chunk with CFG | -->\n\n- `causal_fast` — 480P, multi-GPU:\n  ``` sh\n  torchrun --nproc_per_node=8 generate.py --task i2v-A14B --size 480*832 --ckpt_dir lingbot-world-v2-14b-causal-fast --image examples\u002F03\u002Fimage.jpg --action_path examples\u002F03 --dit_fsdp --t5_fsdp --ulysses_size 8 --frame_num 361 --local_attn_size 18 --sink_size 6 --prompt \"A serene lakeside scene with a lone tree standing in calm water, surrounded by distant snow-capped mountains under a bright blue sky with drifting white clouds — gentle ripples reflect the tree and sky, creating a tranquil, meditative atmosphere.\"\n  ```\n\n\u003C!-- - `causal_pretrain` — 480P, multi-GPU:\n  ``` sh\n  torchrun --nproc_per_node=8 generate.py --task i2v-A14B --infer_mode causal_pretrain --size 480*832 --ckpt_dir lingbot-world-v2-14b-causal-pretrain --image examples\u002F03\u002Fimage.jpg --action_path examples\u002F03 --dit_fsdp --t5_fsdp --ulysses_size 8 --frame_num 81 --prompt \"A serene lakeside scene with a lone tree standing in calm water, surrounded by distant snow-capped mountains under a bright blue sky with drifting white clouds — gentle ripples reflect the tree and sky, creating a tranquil, meditative atmosphere.\"\n  ``` -->\n\nYou can also use the provided `run_fast.sh` script:\n``` sh\nbash run_fast.sh \u003Cweights_dir> \u003Cframe_num>\n# e.g. bash run_fast.sh lingbot-world-v2-14b-causal-fast 361\n```\n\n### Deployment\nWe do NOT plan to release our deployment code. If you would like to deploy our model yourself, please refer to the LingBot-World deployment in [SGLang](https:\u002F\u002Fdocs.sglang.io\u002Fcookbook\u002Fdiffusion\u002FLingBot-World\u002FLingBot-World-2.0) or [flashdreams](https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fflashdreams).\n\n## 📚 Related Projects\n- [LingBot-World](https:\u002F\u002Fgithub.com\u002Frobbyant\u002Flingbot-world)\n\n## 📜 License\nThis project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0). The project is available for non-commercial use only: you may share and adapt it with proper attribution, but derivative works must be distributed under the same license. Please refer to the [LICENSE file](LICENSE.txt) for the full text, including details on rights and restrictions.\n\n## ✨ Acknowledgement\nWe would like to express our gratitude to the Wan Team for open-sourcing their code and models. Their contributions have been instrumental to the development of this project.\n\n## 📖 Citation\nIf you find this work useful for your research, please cite our paper:\n\n```\n@article{lingbot-world-v2,\n      title={Infinite Worlds with Versatile Interactions}, \n      author={Zelin Gao and Qiuyu Wang and Jiapeng Zhu and Jingye Chen and Zichen Liu and Qingyan Bai and Jiahao Wang and Yufeng Yuan and Hanlin Wang and Yichong Lu and Ka Leong Cheng and Haojie Zhang and Jian Gao and Tianrui Feng and Yuzheng Liu and Yao Yao and Yinghao Xu and Xing Zhu and Yujun Shen and Hao Ouyang},\n      journal={arXiv preprint arXiv:2607.07534},\n      year={2026}\n}\n```\n","LingBot-World v2 是一个面向交互式虚拟世界建模的开源大模型框架，支持无限时长、多模态协同的动态场景生成与实时响应。其核心技术包括因果预训练实现的无界交互时序建模、轻量化蒸馏模型保障60fps高清视频流实时推理、多样化动作与文本事件融合的交互元素库，以及首创的双智能体协同架构（飞行员代理负责角色行为规划，导演代理动态生成环境）。适用于AI驱动的游戏原型开发、虚拟仿真训练、教育互动叙事及具身智能研究等需要长期连贯交互的场景。",2,"2026-07-10 02:30:08","CREATED_QUERY"]