feat(env): Update dockers, support codex and lighting packaging.

.dockerignore

@@ -13,13 +13,22 @@ build/
 *.egg-info/
 
 .env
+.cache/
+.pytest_cache/
+.ruff_cache/
 .idea/
 .vscode/
 *.log
 tmp/
 .DS_Store
 
+weights/
+wheels_*/
+apps/gradio_cache/
+apps/sessions/
+thirdparty/infinigen/
+
 Dockerfile
 .dockerignore
 
-outputs/
+outputs/

.github/workflows/ci.yml

@@ -0,0 +1,60 @@
+name: CI
+
+on:
+  pull_request:
+  push:
+    branches: [master]
+
+jobs:
+  release-smoke:
+    runs-on: ubuntu-22.04
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+
+      - name: Install validation tools
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install build ruff
+
+      - name: Lint Python
+        run: ruff check embodied_gen apps tests
+
+      - name: Validate shell scripts
+        run: bash -n install.sh install/*.sh
+
+      - name: Build wheel
+        run: python -m build --wheel --outdir dist
+
+      - name: Validate wheel contents
+        run: |
+          python - <<'PY'
+          from pathlib import Path
+          from zipfile import ZipFile
+
+          wheels = list(Path("dist").glob("*.whl"))
+          assert len(wheels) == 1, wheels
+
+          with ZipFile(wheels[0]) as archive:
+              names = archive.namelist()
+
+          required = {
+              "embodied_gen/__init__.py",
+              "embodied_gen/scripts/imageto3d.py",
+              "embodied_gen/scripts/textto3d.py",
+              "embodied_gen/scripts/gen_texture.py",
+              "embodied_gen/utils/gpt_config.yaml",
+          }
+          missing = sorted(required.difference(names))
+          assert not missing, f"Missing wheel files: {missing}"
+          assert any(name.endswith("/LICENSE") for name in names)
+          assert not any(
+              "__pycache__" in name or name.endswith((".pyc", ".pyo"))
+              for name in names
+          )
+          PY

.github/workflows/deploy_docs.yml

@@ -38,7 +38,7 @@ jobs:
         run: echo "PYTHONPATH=$(pwd)" >> $GITHUB_ENV
 
       - name: Build docs (validation)
-        run: mkdocs build
+        run: mkdocs build --strict
 
   deploy:
     needs: build

MANIFEST.in

@@ -1 +1,4 @@
-graft embodied_gen
+graft embodied_gen
+global-exclude __pycache__
+global-exclude *.py[cod]
+global-exclude .DS_Store

README.md

@@ -6,17 +6,18 @@
 [![📄 arXiv](https://img.shields.io/badge/📄-arXiv_v1-b31b1b)](https://arxiv.org/abs/2506.10600)
 [![📄 arXiv](https://img.shields.io/badge/📄-arXiv_v2-b31b1b)](https://arxiv.org/abs/2607.07459)
 [![🎥 Video](https://img.shields.io/badge/🎥-Video-red)](https://youtu.be/MIkJJSVM8L4)
+[![中文介绍](https://img.shields.io/badge/中文介绍-07C160?logo=wechat&logoColor=white)](https://mp.weixin.qq.com/s/RbMPX3vTTSwrW0MjwjeXuA)
+
 [![🤗 Dataset](https://img.shields.io/badge/🤗-Dataset-blue)](https://huggingface.co/datasets/HorizonRobotics/EmbodiedGenData)
-<!-- [![中文介绍](https://img.shields.io/badge/中文介绍-07C160?logo=wechat&logoColor=white)](https://mp.weixin.qq.com/s/HH1cPBhK2xcDbyCK4BBTbw) -->
 [![🤗 Hugging Face](https://img.shields.io/badge/🤗-EmbodiedGen_Asset_Gallery-blue)](https://huggingface.co/spaces/HorizonRobotics/EmbodiedGen-Gallery-Explorer)
 [![🤗 Hugging Face](https://img.shields.io/badge/🤗-Image_to_3D_Demo-blue)](https://huggingface.co/spaces/HorizonRobotics/EmbodiedGen-Image-to-3D)
 [![🤗 Hugging Face](https://img.shields.io/badge/🤗-Text_to_3D_Demo-blue)](https://huggingface.co/spaces/HorizonRobotics/EmbodiedGen-Text-to-3D)
 [![🤗 Hugging Face](https://img.shields.io/badge/🤗-Texture_Gen_Demo-blue)](https://huggingface.co/spaces/HorizonRobotics/EmbodiedGen-Texture-Gen)
 
 > **From intent to executable 3D worlds.**
-> ***EmbodiedGen*** compiles language, images, and edit commands into **simulation-ready 3D worlds** — physically plausible assets, large-scale scenes, and task-driven interactive environments, deployable across every major robotics simulator.
+> ***EmbodiedGen*** compiles language, images, and edit commands into **policy-ready 3D worlds** — physically plausible assets, large-scale scenes, and task-driven interactive environments, deployable across major simulators.
 
-<img src="docs/landing/assets/img/overview.jpg" alt="EmbodiedGen V2 Overview" width="700"/>
+<img src="docs/landing/assets/img/overview.jpg" alt="EmbodiedGen V2 Overview" width="800"/>
 
 ---
 
@@ -27,7 +28,7 @@
 - 📦 **One world, every simulator** — a standardized layout loads with consistent geometry, collision, and physics across **SAPIEN, Isaac Sim, Isaac Gym, MuJoCo, Genesis, and PyBullet**.
 - 🧩 **Pluggable 3D backends** — switch between **SAM3D**, **TRELLIS**, and the **Hunyuan3D Pro** cloud API with a single flag.
 - 🧥 **Beyond rigid bodies** — text-conditioned garments deploy as deformable meshes in Genesis.
-- 🦾 **Part-level affordance** — functional part segmentation, per-part semantics, and simulation-validated 6-DoF grasp poses for any generated asset.
+- 🕹️ **Part-level affordance** — functional part segmentation, per-part semantics, and simulation-validated 6-DoF grasp poses for any generated asset.
 - 🤖 **Closed-loop robot learning** — policies trained purely in EmbodiedGen-generated worlds transfer to real robots (task success **9.7 → 79.8%** in sim, **21.7 → 75.0%** on real robots, from [sim2real RL paper](https://arxiv.org/abs/2603.18532)).
 
 ## 📋 Table of Contents
@@ -42,6 +43,7 @@
 - [🤖 Train — Robot Learning](#robot-learning)
 - [⚙️ Articulated Object Generation](#articulated-object-generation)
 - [🧩 3D Scene Completion](#3d-scene-completion)
+- [🔄 Sim-to-Real Reinforcement Learning](#sim-to-real-reinforcement-learning)
 
 ---
 
@@ -50,26 +52,34 @@
 ```sh
 git clone https://github.com/HorizonRobotics/EmbodiedGen.git
 cd EmbodiedGen
-git checkout v2.0.1
+git checkout v2.1.0
 conda create -n embodiedgen python=3.10.13 -y
 conda activate embodiedgen
 # Manually install one CUDA toolkit when needed. cu126 remains the default.
 # bash install.sh cu126 # RTX 40-series.
 # bash install.sh cu128 # RTX 50-series / Blackwell.
-bash install.sh basic # around 10 mins
 conda deactivate && conda activate embodiedgen
+bash install.sh basic # around 10 mins
 ```
 
-Set up the GPT agent (required by most pipelines): update the API key in `embodied_gen/utils/gpt_config.yaml`. Then generate your first sim-ready asset:
+Set up one GPT agent backend (required by most pipelines):
+
+- **Azure OpenAI / OpenRouter:** select the backend and update its API key in
+  `embodied_gen/utils/gpt_config.yaml`.
+- **Codex CLI:** run `codex login`, then set `agent_type: codex` in
+  `embodied_gen/utils/gpt_config.yaml`; no project API key is required.
+
+See the [GPT Agent Setup guide](docs/documentation/gpt_agent.md) for complete
+configuration, environment variables, and deployment recommendations.
+
+Then generate your first sim-ready asset:
 
 ```sh
 img3d-cli --image_path apps/assets/example_image/sample_00.jpg \
     --n_retry 2 --output_root outputs/imageto3d
 # → outputs/imageto3d/sample_00/result: URDF + mesh(.obj/.glb) + 3DGS(.ply) + video
 ```
 
-A pre-built Docker image is also available on [Docker Hub](https://hub.docker.com/repository/docker/wangxinjie/embodiedgen).
-
 ➡️ Full guide: [Installation & Setup](https://horizonrobotics.github.io/EmbodiedGen/docs/install.html) · [Docker](docker/README.md)
 
 ---
@@ -133,7 +143,7 @@ room-cli -m embodied_gen.scripts.room_gen.gen_room \
 # or specify the profile explicitly: --room-type Kitchen --seed 42 --complexity simple
 
 # 3DGS background scene from text (requires `bash install.sh scene3d`)
-scene3d-cli --prompts "Art studio with easel and canvas" --output_dir outputs/bg_scenes/ --seed 0
+CUDA_VISIBLE_DEVICES=0 scene3d-cli --prompts "Art studio with easel and canvas" --output_dir outputs/bg_scenes/ --seed 0
 ```
 
 ➡️ Full guides: [Room Generation](https://horizonrobotics.github.io/EmbodiedGen/docs/tutorials/room_gen.html) · [3D Scene Generation](https://horizonrobotics.github.io/EmbodiedGen/docs/tutorials/scene_gen.html)
@@ -252,6 +262,14 @@ See our paper **3D-Fixer** published in CVPR 2026:
 
 ---
 
+<h2 id="sim-to-real-reinforcement-learning">🔄 Sim-to-Real Reinforcement Learning</h2>
+
+See our paper **Scaling Sim-to-Real Reinforcement Learning for Robot VLAs with Generative 3D Worlds** [[link]](https://arxiv.org/abs/2603.18532).
+
+<img src="docs/documentation/assets/sim2real_work.jpg" alt="Sim-to-real reinforcement learning with EmbodiedGen-generated worlds" width="600">
+
+---
+
 ## For Developer
 
 ```sh
@@ -263,17 +281,6 @@ python -m pytest # Pass all unit-test are required.
 
 If you use EmbodiedGen in your research or projects, please cite:
 
-```bibtex
-@misc{wang2026embodiedgenv2agenticsimulationready,
-      title={EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI},
-      author={Xinjie Wang and Liu Liu and Taojun Ding and Andrew Choi and Chaodong Huang and Mengao Zhao and Ziang Li and Jackson Jiang and Chunlei Yu and Shengxiang Liu and Wei Xu and Zhizhong Su},
-      year={2026},
-      eprint={2607.07459},
-      archivePrefix={arXiv},
-      primaryClass={cs.RO},
-      url={https://arxiv.org/abs/2607.07459},
-}
-```
 ```bibtex
 @misc{wang2025embodiedgengenerative3dworld,
   title         = {EmbodiedGen: Towards a Generative 3D World Engine for Embodied Intelligence},
@@ -286,6 +293,18 @@ If you use EmbodiedGen in your research or projects, please cite:
 }
 ```
 
+```bibtex
+@misc{wang2026embodiedgenv2agenticsimulationready,
+      title={EmbodiedGen V2: An Agentic, Simulation-Ready 3D World Engine for Embodied AI},
+      author={Xinjie Wang and Liu Liu and Taojun Ding and Andrew Choi and Chaodong Huang and Mengao Zhao and Ziang Li and Jackson Jiang and Chunlei Yu and Shengxiang Liu and Wei Xu and Zhizhong Su},
+      year={2026},
+      eprint={2607.07459},
+      archivePrefix={arXiv},
+      primaryClass={cs.RO},
+      url={https://arxiv.org/abs/2607.07459},
+}
+```
+
 ---
 
 ## 🙌 Acknowledgement
@@ -297,4 +316,4 @@ EmbodiedGen builds upon the following amazing projects and models:
 
 ## ⚖️ License
 
-This project is licensed under the [Apache License 2.0](docs/LICENSE). See the `LICENSE` file for details.
+This project is licensed under the [Apache License 2.0](LICENSE). See the `LICENSE` file for details.

apps/app_style.py

@@ -15,7 +15,7 @@
 # permissions and limitations under the License.
 
 from gradio.themes import Soft
-from gradio.themes.utils.colors import gray, neutral, slate, stone, teal, zinc
+from gradio.themes.utils.colors import gray, stone
 
 lighting_css = """
 <style>

apps/visualize_asset.py

@@ -89,7 +89,6 @@ def fake_gpu_init():
             "dataset/**/*.mp4",
         ],
         local_dir=HF_LOCAL_DIR,
-        local_dir_use_symlinks=False,
     )
     DATA_ROOT = os.path.join(HF_LOCAL_DIR, "dataset")
 else:
@@ -115,7 +114,6 @@ def ensure_hf_files(rel_patterns: list[str]) -> None:
         repo_type="dataset",
         allow_patterns=[f"dataset/{p}" for p in rel_patterns],
         local_dir=HF_LOCAL_DIR,
-        local_dir_use_symlinks=False,
     )
 
 

docker/5090/Dockerfile

@@ -0,0 +1,40 @@
+FROM pytorch/pytorch:2.8.0-cuda12.8-cudnn9-devel
+
+LABEL maintainer="Horizon Robotics" \
+      description="EmbodiedGen for RTX 5090 (sm_120, CUDA 12.8)"
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    LANG=C.UTF-8 \
+    LC_ALL=C.UTF-8
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        git build-essential ninja-build pkg-config \
+        libgl1-mesa-glx libglib2.0-0 libsm6 libxext6 libxrender1 \
+        libegl1 libgles2 libgbm1 \
+    && rm -rf /var/lib/apt/lists/*
+
+ENV CUDA_HOME=/usr/local/cuda \
+    CUDA_PATH=/usr/local/cuda \
+    PATH=/usr/local/cuda/bin:$PATH \
+    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
+    EMBODIEDGEN_TORCH_INDEX_URL=https://download.pytorch.org/whl/cu128 \
+    PIP_NO_CACHE_DIR=1 \
+    TORCH_CUDA_ARCH_LIST="12.0" \
+    FORCE_CUDA=1 \
+    MAX_JOBS=8
+
+ENV HF_HOME=/hf_cache \
+    TORCH_HOME=/hf_cache/torch_hub \
+    OPENCV_IO_ENABLE_OPENEXR=1
+
+WORKDIR /EmbodiedGen
+COPY . /EmbodiedGen/
+
+RUN conda create -n embodiedgen python=3.10.13 -y && \
+    conda run -n embodiedgen bash install/install_basic.sh && \
+    conda run -n embodiedgen python -m pip install numpy==1.26.4
+
+RUN /opt/conda/bin/conda init bash && \
+    echo "conda activate embodiedgen" >> /root/.bashrc
+
+CMD ["bash", "--login"]

docker/5090/README.md

@@ -0,0 +1,61 @@
+# RTX 5090 Docker Image
+
+This image builds the EmbodiedGen `basic` stage for RTX 5090 / Blackwell
+(`sm_120`) with PyTorch 2.8 and CUDA 12.8. Model weights are downloaded at
+runtime and are not included in the image.
+
+## Prerequisites
+
+- Linux with an RTX 5090 and a CUDA 12.8-compatible NVIDIA driver.
+- Docker with NVIDIA Container Toolkit.
+- Access to PyPI and GitHub while building, and Hugging Face at runtime.
+
+## Build
+
+`.git` is excluded from the build context, so initialize the basic-stage
+submodules on the host first:
+
+```bash
+git clone <repository-url> EmbodiedGen
+cd EmbodiedGen
+git submodule update --init --recursive --progress \
+    thirdparty/TRELLIS thirdparty/sam3d
+docker build -t embodiedgen:cu128-sm120 -f docker/5090/Dockerfile .
+```
+
+Lower `MAX_JOBS` in the Dockerfile if CUDA extension builds exhaust memory.
+
+## Verify
+
+```bash
+docker run --rm embodiedgen:cu128-sm120 \
+    conda run -n embodiedgen python -c "import embodied_gen, gsplat, kaolin, pytorch3d; print('imports OK')"
+docker run --rm embodiedgen:cu128-sm120 \
+    conda run -n embodiedgen img3d-cli --help
+docker run --rm --gpus all embodiedgen:cu128-sm120 \
+    conda run -n embodiedgen python -c "import torch; x=torch.randn(1024,1024,device='cuda:0'); print('matmul', (x@x).sum().item())"
+```
+
+The last command must print a numeric result. A `no kernel image` error usually
+means a cu126 PyTorch wheel replaced the cu128 wheel.
+
+## Run
+
+```bash
+docker run --gpus all --shm-size=64g -it --rm \
+    -v embodiedgen_hf_cache:/hf_cache \
+    -v "$PWD":/workspace \
+    embodiedgen:cu128-sm120 bash
+```
+
+Inside the container:
+
+```bash
+conda activate embodiedgen
+img3d-cli --image_path <image> --output_root /workspace/outputs
+```
+
+## Notes
+
+- `EMBODIEDGEN_TORCH_INDEX_URL` keeps newer installers on the cu128 index.
+- For RTX 4090, A100, or H100, use `docker/Dockerfile` instead.

docker/Dockerfile

@@ -1,6 +1,6 @@
-FROM pytorch/pytorch:2.4.0-cuda11.8-cudnn9-devel
+FROM pytorch/pytorch:2.8.0-cuda12.6-cudnn9-devel
 LABEL maintainer="Horizon Robotics <xinjie.wang@horizon.auto>" \
-    version="0.1.2" \
+    version="2.1.0" \
     description="Docker image for EmbodiedGen"
 
 RUN apt-get update && apt-get install -y --no-install-recommends \
@@ -16,9 +16,9 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
     && rm -rf /var/lib/apt/lists/*
 
 # TORCH_CUDA_ARCH_LIST="8.0;8.9;9.0" -> A100/4090/H100
-ENV CUDA_HOME=/usr/local/cuda-11.8 \
-    PATH=/usr/local/cuda-11.8/bin:$PATH \
-    LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH \
+ENV CUDA_HOME=/usr/local/cuda \
+    PATH=/usr/local/cuda/bin:$PATH \
+    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
     DEBIAN_FRONTEND=noninteractive \
     TORCH_CUDA_ARCH_LIST="8.0;8.9;9.0" \
     TCNN_CUDA_ARCHITECTURES=80,89,90