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Generate World

OrganizationPopular
AgibotTech
generate-world

Drive `geniesim_world` to produce a photorealistic, explorable 3D world from a single equirectangular panorama — uses the `geniesim_world create` CLI (Click subcommand), pairs SHARP + DA360 to fuse panorama RGB with metric depth, and optionally upscales with Real-ESRGAN. Trigger: When the user asks to "generate a world", "生成 3D 世界", "pano to 3D", "PanoRecon", "make a scene from a photo", "create a world from a panorama", or references `geniesim_world` / a `.png` panorama input.

Overview

PublisherAgibotTech
Repositorygenie_sim
Skill namegenerate-world
Stars
1.4K
Forks
119
Bundled files
Instructions only
LicenseMPL-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AgibotTech on GitHub. Read the source before you install it.

Installation

Install the Generate World AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgibotTech/genie_sim.git /tmp/genie_sim
mkdir -p .claude/skills
cp -r /tmp/genie_sim/source/geniesim_world/skills/generate-world .claude/skills/generate-world
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Generate World in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Generate World on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Generate World is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

When to Use

  • User has an equirectangular panorama (2:1 aspect, e.g. 4096×2048) and wants a 3D world (Gaussian splat / depth map / fused cubes) out of it.
  • User wants to seed a Genie Sim scene with a generated environment rather than a hand-authored USD.
  • Researcher reproducing the PanoRecon paper (arXiv 2604.07105).

Do not use for:

  • USD scene authoring without a panorama input → that's the generate-scene skill in geniesim_generator.
  • Asset / object library search → search-assets in geniesim_generator.
  • Importing an existing USD scene into the RT Engine → just point the scene yaml's scene_usda at the existing USD (see add-robot / launch-scene). This skill is not the path for that — geniesim_world produces .ply / .gsp Gaussians today, and loading them into a scene_*.yaml is 🚧 W.I.P.

Critical Patterns

  1. Out-of-band install. geniesim_world is not pulled in by geniesim bootstrap — it lives behind heavy CUDA deps (PyTorch + ml-sharp + DA360 + optional Real-ESRGAN). Install in its own conda env, separate from the rest of the stack.
  2. Three external dependencies, not on pip. Need external/ml-sharp/, external/DA360/ (with checkpoint), and optionally external/realesrgan-ncnn-vulkan-…/. The external/ tree sits next to geniesim_world/ under source/.
  3. DA360 checkpoint is mandatory. Either drop it at external/DA360/DA360_large.pth, pass --da360-checkpoint, or set GENIESIM_DA360_CHECKPOINT. Without it, depth prediction fails immediately.
  4. Tested on RTX 5090 / CUDA 12.8. Other GPUs work but need a matching requirements-cu<XX>.txt. Don't paste the cu128 line verbatim onto a cu118 box.
  5. Real-ESRGAN is optional. It improves visual fidelity but introduces synthetic texture — disable for tasks where ground-truth pixel statistics matter.

Workflow

Step 1 — Verify the layout

source/
├── geniesim_world/                              # this project
└── external/
    ├── ml-sharp/                                # git clone https://github.com/apple/ml-sharp.git
    ├── DA360/                                   # git clone https://github.com/DepthAnything/DA360.git
    │   └── DA360_large.pth                      # checkpoint (download separately)
    └── realesrgan-ncnn-vulkan-20220424-ubuntu/  # optional, super-sample binary
        └── realesrgan-ncnn-vulkan

If any external is missing, run the clone / download from the geniesim_world/README.md § "Prepare Dependencies".

Step 2 — Create a clean env and install

bash
conda create -n geniesim_world python=3.11 -y
conda activate geniesim_world
pip install --upgrade "pip==24.0" "setuptools==69.5.1" "wheel==0.43.0"

cd source/geniesim_world
pip install --extra-index-url https://download.pytorch.org/whl/cu128 -r requirements-cu128.txt
pip install --extra-index-url https://download.pytorch.org/whl/cu128 -e .

Verify:

bash
geniesim_world --help                            # Click group
geniesim_world create --help                     # subcommand surface

Step 3 — Generate a world from a panorama

bash
geniesim_world create \
  --panorama path/to/scene_pano.png \
  --work-dir runs/$(date +%Y%m%d_%H%M%S) \
  --device cuda:0

Optional knobs:

FlagEffect
--da360-checkpoint <path>Override checkpoint path
--da360-root <dir>Override DA360 repo root
--checkpoint-path <path>SHARP checkpoint override
--depth-max <float>Clip predicted depth at N metres
--no-depth-gt-initStock SHARP (ignore depth_gt override)
--super-sampleRun Real-ESRGAN before fusing (needs the optional binary)

Step 4 — Inspect the work-dir

Typical artifacts under runs/<stamp>/:

runs/<stamp>/
├── pano_input.png             # the panorama (copied for provenance)
├── depth/                     # per-cube depth maps (EXR or PNG)
├── cubes/                     # cubemap faces fused from pano + depth
└── world.gsp / world.ply / …  # exported world (format depends on flags)

Step 5 — (🚧 W.I.P.) Feed into a Genie Sim scene

Loading the generated world into the RT Engine via a scene_*.yaml is not yet supported. The current contract is that geniesim_world produces .ply / .gsp Gaussians (plus per-face EXR depth + cubemap RGB); downstream consumption is via the package's own debug tooling (geniesim_world debug) and external viewers, not the RT Engine launcher. The RT-Engine load path is planned — track the Roadmap & Updates section in the root README.

Commands (copy-paste summary for the user)

bash
# Once-off setup
conda create -n geniesim_world python=3.11 -y && conda activate geniesim_world
cd source/geniesim_world
pip install --extra-index-url https://download.pytorch.org/whl/cu128 \
  -r requirements-cu128.txt
pip install --extra-index-url https://download.pytorch.org/whl/cu128 -e .

# Generate
geniesim_world create \
  --panorama path/to/scene_pano.png \
  --work-dir runs/demo \
  --device cuda:0

Notes

  • The CLI is a Click group: geniesim_world exposes subcommands, with create being the primary one. Run geniesim_world --help for the full list.
  • "Generate from text" and "Generate from sparse images" are flagged COMING SOON in geniesim_world/README.md — don't promise them in the workflow.
  • The env is intentionally isolated from the rest of the stack so pip install here can't break a working geniesim_ros shell.
  • For sim-to-real research, the generated world's depth statistics are more reliable without --super-sample (Real-ESRGAN introduces hallucinated texture).

Resources

Frequently asked questions

What does the Generate World AI skill do?

Drive `geniesim_world` to produce a photorealistic, explorable 3D world from a single equirectangular panorama — uses the `geniesim_world create` CLI (Click subcommand), pairs SHARP + DA360 to fuse panorama RGB with metric depth, and optionally upscales with Real-ESRGAN. Trigger: When the user asks to "generate a world", "生成 3D 世界", "pano to 3D", "PanoRecon", "make a scene from a photo", "create a world from a panorama", or references `geniesim_world` / a `.png` panorama input.

Why use Generate World on TypingMind?

Because you install it once and use it with any model. Generate World is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Generate World in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgibotTech/genie_sim/tree/main/source/geniesim_world/skills/generate-world. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Generate World?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Generate World?

As many as you like. As long as a model supports skills, you can use Generate World with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Generate World AI skill free?

Yes. It is published on GitHub by AgibotTech under the MPL-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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