feat: migrate to ZeroGPU on Python 3.12 + PyTorch 2.8.

- Switch hardware target to ZeroGPU; add suggested_hardware in README.
- Pin python_version to 3.12.12 (ZeroGPU-supported).
- Manage all dependencies via uv-managed pyproject.toml instead of
subprocess-based runtime wheel installs.
- Rebuild CUDA wheels (diff_gaussian_rasterization, grid_encoder,
voxlib_ext) against cp312 + torch 2.8 + cu128.
- Resolve flash-attn 2.8.3 and torch_scatter 2.1.2 from external
wheel URLs matching the new torch / Python combo.
- Refactor app.py: unconditional 'import spaces', drop the legacy
setup_runtime_env plumbing.
- Bump Gradio SDK to 6.14.0.

.gitignore

@@ -20,7 +20,6 @@ lib64/
 parts/
 sdist/
 var/
-wheels/
 share/python-wheels/
 *.egg-info/
 .installed.cfg
@@ -182,3 +181,6 @@ output/
 flagged/
 *.pth
 *.pkl
+
+# Claude tooling
+.claude/

.python-version

@@ -0,0 +1 @@
+3.12

README.md

@@ -2,12 +2,13 @@
 title: GaussianCity
 emoji: 🌇 
 colorFrom: red
-python_version: 3.10.16
 colorTo: blue
 sdk: gradio
-sdk_version: 6.13.0
+sdk_version: 6.14.0
+python_version: 3.12.12
 app_file: app.py
 pinned: false
+suggested_hardware: zero-a10g
 short_description: Efficient 3D city generation in seconds!
 ---
 
@@ -16,4 +17,3 @@ Official demo for **[Generative Gaussian Splatting for Unbounded 3D City Generat
 - 🔥 GaussianCity is a unbounded 3D city generator based on 3D Gaussian Splatting.
 - 🤗 Try GaussianCity to generate photolistic 3D cities.
 - ⚠️  Due to the limited computational resources at Hugging Face, this demo only generates **A SINGLE IMAGE** based on the New York City layout.
-

app.py

@@ -1,107 +1,19 @@
-# -*- coding: utf-8 -*-
-#
-# @File:   app.py
-# @Author: Haozhe Xie
-# @Date:   2024-03-02 16:30:00
-# @Last Modified by: Haozhe Xie
-# @Last Modified at: 2024-10-13 15:36:50
-# @Email:  root@haozhexie.com
-
-import gradio as gr
 import logging
-import numpy as np
 import os
 import pickle
 import ssl
-import subprocess
 import sys
 import urllib.request
 
-from PIL import Image
-
-# Reinstall PyTorch with CUDA 11.8 (Default version is 12.1)
-# subprocess.call(
-#     [
-#         "pip",
-#         "install",
-#         "torch==2.2.2",
-#         "torchvision==0.17.2",
-#         "--index-url",
-#         "https://download.pytorch.org/whl/cu118",
-#     ]
-# )
+import gradio as gr
+import numpy as np
+import spaces
 import torch
+from PIL import Image
 
-# Create a dummy decorator for Non-ZeroGPU environments
-if os.environ.get("SPACES_ZERO_GPU") is not None:
-    import spaces
-else:
-
-    class spaces:
-        @staticmethod
-        def GPU(func):
-            # This is a dummy wrapper that just calls the function.
-            def wrapper(*args, **kwargs):
-                return func(*args, **kwargs)
-
-            return wrapper
-
-
-# Fix: ssl.SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed
 ssl._create_default_https_context = ssl._create_unverified_context
-# Import GaussianCity modules
-sys.path.append(os.path.join(os.path.dirname(__file__), "gaussiancity"))
-
-
-def _get_output(cmd):
-    try:
-        return subprocess.check_output(cmd).decode("utf-8")
-    except Exception as ex:
-        logging.exception(ex)
 
-    return None
-
-
-def install_cuda_toolkit():
-    # CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run"
-    CUDA_TOOLKIT_URL = "https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run"
-    CUDA_TOOLKIT_FILE = "/tmp/%s" % os.path.basename(CUDA_TOOLKIT_URL)
-    subprocess.call(["wget", "-q", CUDA_TOOLKIT_URL, "-O", CUDA_TOOLKIT_FILE])
-    subprocess.call(["chmod", "+x", CUDA_TOOLKIT_FILE])
-    subprocess.call([CUDA_TOOLKIT_FILE, "--silent", "--toolkit"])
-
-    os.environ["CUDA_HOME"] = "/usr/local/cuda"
-    os.environ["PATH"] = "%s/bin:%s" % (os.environ["CUDA_HOME"], os.environ["PATH"])
-    os.environ["LD_LIBRARY_PATH"] = "%s/lib:%s" % (
-        os.environ["CUDA_HOME"],
-        "" if "LD_LIBRARY_PATH" not in os.environ else os.environ["LD_LIBRARY_PATH"],
-    )
-    # Fix: arch_list[-1] += '+PTX'; IndexError: list index out of range
-    os.environ["TORCH_CUDA_ARCH_LIST"] = "8.0;8.6"
-
-
-def setup_runtime_env():
-    logging.info("Python Version: %s" % _get_output(["python", "--version"]))
-    logging.info("CUDA Version: %s" % _get_output(["nvcc", "--version"]))
-    logging.info("GCC Version: %s" % _get_output(["gcc", "--version"]))
-    logging.info("CUDA is available: %s" % torch.cuda.is_available())
-    logging.info("CUDA Device Capability: %s" % (torch.cuda.get_device_capability(),))
-
-    # Install Pre-compiled CUDA extensions
-    # Ref: https://huggingface.co/spaces/zero-gpu-explorers/README/discussions/110
-    ext_dir = os.path.join(os.path.dirname(__file__), "wheels")
-    for e in os.listdir(ext_dir):
-        logging.info("Installing Extensions from %s" % e)
-        subprocess.call(
-            ["pip", "install", os.path.join(ext_dir, e)], stderr=subprocess.STDOUT
-        )
-    # Compile CUDA extensions
-    # ext_dir = os.path.join(os.path.dirname(__file__), "gaussiancity", "extensions")
-    # for e in os.listdir(ext_dir):
-    #     if os.path.isdir(os.path.join(ext_dir, e)):
-    #         subprocess.call(["pip", "install", "."], cwd=os.path.join(ext_dir, e))
-
-    logging.info("Installed Python Packages: %s" % _get_output(["pip", "list"]))
+sys.path.append(os.path.join(os.path.dirname(__file__), "gaussiancity"))
 
 
 def get_models(file_name):
@@ -109,20 +21,17 @@ def get_models(file_name):
 
     if not os.path.exists(file_name):
         urllib.request.urlretrieve(
-            "https://huggingface.co/hzxie/gaussian-city/resolve/main/%s" % file_name,
+            f"https://huggingface.co/hzxie/gaussian-city/resolve/main/{file_name}",
             file_name,
         )
 
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    ckpt = torch.load(file_name, map_location=torch.device(device), weights_only=False)
+    ckpt = torch.load(file_name, map_location="cpu", weights_only=False)
     model = gaussiancity.generator.Generator(
         ckpt["cfg"].NETWORK.GAUSSIAN,
         n_classes=ckpt["cfg"].DATASETS.GOOGLE_EARTH.N_CLASSES,
         proj_size=ckpt["cfg"].DATASETS.GOOGLE_EARTH.PROJ_SIZE,
     )
-    if torch.cuda.is_available():
-        model = torch.nn.DataParallel(model).cuda().eval()
-
+    model = torch.nn.DataParallel(model).cuda().eval()
     model.load_state_dict(ckpt["gaussian_g"], strict=False)
     return model
 
@@ -130,7 +39,6 @@ def get_models(file_name):
 def get_city_layout():
     import gaussiancity.inference
 
-    layout = None
     if os.path.exists("assets/NYC.pkl"):
         with open("assets/NYC.pkl", "rb") as fp:
             layout = pickle.load(fp)
@@ -139,9 +47,7 @@ def get_city_layout():
         # Fix: nonzero is not supported for tensors with more than INT_MAX elements
         td_hf[td_hf > 500] = 500
         bu_hf = np.zeros_like(td_hf)
-        seg_map = np.array(Image.open("assets/NYC-SegMap.png").convert("P")).astype(
-            np.int32
-        )
+        seg_map = np.array(Image.open("assets/NYC-SegMap.png").convert("P")).astype(np.int32)
         ins_map = gaussiancity.inference.get_instance_seg_map(seg_map.copy())
         pts_map = gaussiancity.inference.get_point_map(seg_map)
         layout = {
@@ -154,7 +60,6 @@ def get_city_layout():
         with open("assets/NYC.pkl", "wb") as fp:
             pickle.dump(layout, fp)
 
-    centers = None
     if os.path.exists("assets/CENTERS.pkl"):
         with open("assets/CENTERS.pkl", "rb") as fp:
             centers = pickle.load(fp)
@@ -167,17 +72,24 @@ def get_city_layout():
     return layout
 
 
+logging.basicConfig(format="[%(levelname)s] %(asctime)s %(message)s", level=logging.INFO)
+
+logging.info("Loading pretrained models...")
+fgm = get_models("GaussianCity-Fgnd.pth")
+bgm = get_models("GaussianCity-Bgnd.pth")
+
+logging.info("Loading New York city layout to RAM...")
+city_layout = get_city_layout()
+
+
 @spaces.GPU
 def get_generated_city(radius, altitude, azimuth, map_center):
-    logging.info("CUDA is available: %s" % torch.cuda.is_available())
-    logging.info("PyTorch is built with CUDA: %s" % torch.version.cuda)
-    # The import must be done after CUDA extension compilation
     import gaussiancity.inference
 
     return gaussiancity.inference.generate_city(
-        get_generated_city.fgm.to("cuda"),
-        get_generated_city.bgm.to("cuda"),
-        get_generated_city.city_layout,
+        fgm.to("cuda"),
+        bgm.to("cuda"),
+        city_layout,
         map_center,
         map_center,
         radius,
@@ -186,7 +98,7 @@ def get_generated_city(radius, altitude, azimuth, map_center):
     )
 
 
-def main(debug):
+def main():
     title = "Generative Gaussian Splatting for Unbounded 3D City Generation"
     with open("README.md", "r") as f:
         markdown = f.read()
@@ -208,33 +120,9 @@ def main(debug):
         article=arti,
         flagging_mode="never",
     )
-    app.queue(api_open=False)
-    app.launch(debug=debug)
+    app.queue()
+    app.launch()
 
 
 if __name__ == "__main__":
-    logging.basicConfig(
-        format="[%(levelname)s] %(asctime)s %(message)s", level=logging.INFO
-    )
-    logging.info("Environment Variables: %s" % os.environ)
-    # if _get_output(["nvcc", "--version"]) is None:
-    #     logging.info("Installing CUDA toolkit...")
-    #     install_cuda_toolkit()
-    # else:
-    #     logging.info("Detected CUDA: %s" % _get_output(["nvcc", "--version"]))
-
-    logging.info("Compiling CUDA extensions...")
-    setup_runtime_env()
-
-    logging.info("Downloading pretrained models...")
-    fgm = get_models("GaussianCity-Fgnd.pth")
-    bgm = get_models("GaussianCity-Bgnd.pth")
-    get_generated_city.fgm = fgm
-    get_generated_city.bgm = bgm
-
-    logging.info("Loading New York city layout to RAM...")
-    city_layout = get_city_layout()
-    get_generated_city.city_layout = city_layout
-
-    logging.info("Starting the main application...")
-    main(os.getenv("DEBUG") == "1")
+    main()

pyproject.toml

@@ -0,0 +1,43 @@
+[project]
+name = "gaussian-city"
+version = "0.1.0"
+description = "GaussianCity 3D city generation Space"
+readme = "README.md"
+requires-python = "==3.12.*"
+dependencies = [
+    "addict>=2.4.0",
+    "diff-gaussian-rasterization",
+    "easydict>=1.13",
+    "flash-attn==2.8.3",
+    "gradio[mcp,oauth]==6.14.0",
+    "grid-encoder",
+    "huggingface-hub>=0.36.0",
+    "numpy<2",
+    "opencv-python-headless>=4.10.0.84",
+    "pillow>=11.0.0",
+    "scipy>=1.14.1",
+    "spaces>=0.50.2",
+    "spconv-cu126>=2.3.8",
+    "torch==2.8.0",
+    "torch-scatter==2.1.2",
+    "torchvision==0.23.0",
+    "tqdm>=4.66.5",
+    "voxlib-ext",
+]
+
+[tool.uv]
+no-build-isolation-package = ["flash-attn", "torch-scatter"]
+
+[tool.uv.sources]
+torch = [{ index = "pytorch-cu128" }]
+torchvision = [{ index = "pytorch-cu128" }]
+torch-scatter = { url = "https://data.pyg.org/whl/torch-2.8.0+cu128/torch_scatter-2.1.2+pt28cu128-cp312-cp312-linux_x86_64.whl" }
+flash-attn = { url = "https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp312-cp312-linux_x86_64.whl" }
+diff-gaussian-rasterization = { path = "wheels/diff_gaussian_rasterization-1.0.0-cp312-cp312-linux_x86_64.whl" }
+grid-encoder = { path = "wheels/grid_encoder-1.0.0-cp312-cp312-linux_x86_64.whl" }
+voxlib-ext = { path = "wheels/voxlib_ext-3.0.0-cp312-cp312-linux_x86_64.whl" }
+
+[[tool.uv.index]]
+name = "pytorch-cu128"
+url = "https://download.pytorch.org/whl/cu128"
+explicit = true

requirements.txt

@@ -1,13 +1,359 @@
---extra-index-url https://download.pytorch.org/whl/cu121
-easydict
-gradio
-numpy<2.0.0
-opencv-python
-pillow
-scipy
-torch==2.2.2
-torchvision==0.17.2
-
-addict
-spconv-cu121
-
+# This file was autogenerated by uv via the following command:
+#    uv export --no-hashes --no-dev --no-emit-package typer-slim --no-emit-package spaces --no-emit-project -o requirements.txt
+./wheels/diff_gaussian_rasterization-1.0.0-cp312-cp312-linux_x86_64.whl
+    # via gaussian-city
+./wheels/grid_encoder-1.0.0-cp312-cp312-linux_x86_64.whl
+    # via gaussian-city
+./wheels/voxlib_ext-3.0.0-cp312-cp312-linux_x86_64.whl
+    # via gaussian-city
+addict==2.4.0
+    # via gaussian-city
+annotated-doc==0.0.4
+    # via
+    #   fastapi
+    #   typer
+annotated-types==0.7.0
+    # via pydantic
+anyio==4.13.0
+    # via
+    #   gradio
+    #   httpx
+    #   mcp
+    #   sse-starlette
+    #   starlette
+attrs==26.1.0
+    # via
+    #   jsonschema
+    #   referencing
+authlib==1.7.2
+    # via gradio
+brotli==1.2.0
+    # via gradio
+ccimport==0.4.4
+    # via
+    #   pccm
+    #   spconv-cu126
+certifi==2026.5.20
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+cffi==2.0.0 ; platform_python_implementation != 'PyPy'
+    # via cryptography
+charset-normalizer==3.4.7
+    # via requests
+click==8.4.1
+    # via
+    #   typer
+    #   uvicorn
+colorama==0.4.6 ; sys_platform == 'win32'
+    # via
+    #   click
+    #   tqdm
+cryptography==48.0.0
+    # via
+    #   authlib
+    #   joserfc
+    #   pyjwt
+cumm-cu126==0.7.11
+    # via spconv-cu126
+easydict==1.13
+    # via gaussian-city
+einops==0.8.2
+    # via flash-attn
+fastapi==0.136.3
+    # via gradio
+filelock==3.29.0
+    # via
+    #   huggingface-hub
+    #   torch
+fire==0.7.1
+    # via
+    #   cumm-cu126
+    #   pccm
+    #   spconv-cu126
+flash-attn @ https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp312-cp312-linux_x86_64.whl
+    # via gaussian-city
+fsspec==2026.4.0
+    # via
+    #   gradio-client
+    #   huggingface-hub
+    #   torch
+gradio==6.14.0
+    # via
+    #   gaussian-city
+    #   spaces
+gradio-client==2.5.0
+    # via
+    #   gradio
+    #   hf-gradio
+groovy==0.1.2
+    # via gradio
+h11==0.16.0
+    # via
+    #   httpcore
+    #   uvicorn
+hf-gradio==0.4.1
+    # via gradio
+hf-xet==1.5.0 ; platform_machine == 'AMD64' or platform_machine == 'aarch64' or platform_machine == 'amd64' or platform_machine == 'arm64' or platform_machine == 'x86_64'
+    # via huggingface-hub
+httpcore==1.0.9
+    # via httpx
+httpx==0.28.1
+    # via
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   mcp
+    #   safehttpx
+    #   spaces
+httpx-sse==0.4.3
+    # via mcp
+huggingface-hub==1.16.1
+    # via
+    #   gaussian-city
+    #   gradio
+    #   gradio-client
+idna==3.16
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+itsdangerous==2.2.0
+    # via gradio
+jinja2==3.1.6
+    # via
+    #   gradio
+    #   torch
+joserfc==1.6.7
+    # via authlib
+jsonschema==4.26.0
+    # via mcp
+jsonschema-specifications==2025.9.1
+    # via jsonschema
+lark==1.3.1
+    # via pccm
+markdown-it-py==4.2.0
+    # via rich
+markupsafe==3.0.3
+    # via
+    #   gradio
+    #   jinja2
+mcp==1.27.1
+    # via gradio
+mdurl==0.1.2
+    # via markdown-it-py
+mpmath==1.3.0
+    # via sympy
+networkx==3.6.1
+    # via torch
+ninja==1.13.0
+    # via ccimport
+numpy==1.26.4
+    # via
+    #   cumm-cu126
+    #   gaussian-city
+    #   gradio
+    #   opencv-python-headless
+    #   pandas
+    #   scipy
+    #   spconv-cu126
+    #   torchvision
+nvidia-cublas-cu12==12.8.4.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via
+    #   nvidia-cudnn-cu12
+    #   nvidia-cusolver-cu12
+    #   torch
+nvidia-cuda-cupti-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cuda-nvrtc-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cuda-runtime-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cudnn-cu12==9.10.2.21 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cufft-cu12==11.3.3.83 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cufile-cu12==1.13.1.3 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-curand-cu12==10.3.9.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cusolver-cu12==11.7.3.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-cusparse-cu12==12.5.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via
+    #   nvidia-cusolver-cu12
+    #   torch
+nvidia-cusparselt-cu12==0.7.1 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-nccl-cu12==2.27.3 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+nvidia-nvjitlink-cu12==12.8.93 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via
+    #   nvidia-cufft-cu12
+    #   nvidia-cusolver-cu12
+    #   nvidia-cusparse-cu12
+    #   torch
+nvidia-nvtx-cu12==12.8.90 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+opencv-python-headless==4.11.0.86
+    # via gaussian-city
+orjson==3.11.9
+    # via gradio
+packaging==26.2
+    # via
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   spaces
+pandas==3.0.3
+    # via gradio
+pccm==0.4.16
+    # via
+    #   cumm-cu126
+    #   spconv-cu126
+pillow==12.2.0
+    # via
+    #   gaussian-city
+    #   gradio
+    #   torchvision
+portalocker==3.2.0
+    # via pccm
+pybind11==3.0.4
+    # via
+    #   ccimport
+    #   cumm-cu126
+    #   pccm
+    #   spconv-cu126
+pycparser==3.0 ; implementation_name != 'PyPy' and platform_python_implementation != 'PyPy'
+    # via cffi
+pydantic==2.12.5
+    # via
+    #   fastapi
+    #   gradio
+    #   mcp
+    #   pydantic-settings
+    #   spaces
+pydantic-core==2.41.5
+    # via pydantic
+pydantic-settings==2.14.1
+    # via mcp
+pydub==0.25.1
+    # via gradio
+pygments==2.20.0
+    # via rich
+pyjwt==2.13.0
+    # via mcp
+python-dateutil==2.9.0.post0
+    # via pandas
+python-dotenv==1.2.2
+    # via pydantic-settings
+python-multipart==0.0.29
+    # via
+    #   gradio
+    #   mcp
+pytz==2026.2
+    # via gradio
+pywin32==311 ; sys_platform == 'win32'
+    # via
+    #   mcp
+    #   portalocker
+pyyaml==6.0.3
+    # via
+    #   gradio
+    #   huggingface-hub
+referencing==0.37.0
+    # via
+    #   jsonschema
+    #   jsonschema-specifications
+requests==2.34.2
+    # via
+    #   ccimport
+    #   spaces
+rich==15.0.0
+    # via typer
+rpds-py==0.30.0
+    # via
+    #   jsonschema
+    #   referencing
+safehttpx==0.1.7
+    # via gradio
+scipy==1.17.1
+    # via gaussian-city
+semantic-version==2.10.0
+    # via gradio
+setuptools==82.0.1
+    # via
+    #   torch
+    #   triton
+shellingham==1.5.4
+    # via typer
+six==1.17.0
+    # via python-dateutil
+spconv-cu126==2.3.8
+    # via gaussian-city
+sse-starlette==3.4.4
+    # via mcp
+starlette==1.1.0
+    # via
+    #   fastapi
+    #   gradio
+    #   mcp
+    #   sse-starlette
+sympy==1.14.0
+    # via
+    #   cumm-cu126
+    #   torch
+termcolor==3.3.0
+    # via fire
+tomlkit==0.14.0
+    # via gradio
+torch==2.8.0+cu128
+    # via
+    #   flash-attn
+    #   gaussian-city
+    #   torchvision
+torch-scatter @ https://data.pyg.org/whl/torch-2.8.0+cu128/torch_scatter-2.1.2+pt28cu128-cp312-cp312-linux_x86_64.whl
+    # via gaussian-city
+torchvision==0.23.0+cu128
+    # via gaussian-city
+tqdm==4.67.3
+    # via
+    #   gaussian-city
+    #   huggingface-hub
+triton==3.4.0 ; platform_machine == 'x86_64' and sys_platform == 'linux'
+    # via torch
+typer==0.25.1
+    # via
+    #   gradio
+    #   hf-gradio
+    #   huggingface-hub
+typing-extensions==4.15.0
+    # via
+    #   anyio
+    #   fastapi
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   mcp
+    #   pydantic
+    #   pydantic-core
+    #   referencing
+    #   spaces
+    #   starlette
+    #   torch
+    #   typing-inspection
+typing-inspection==0.4.2
+    # via
+    #   fastapi
+    #   mcp
+    #   pydantic
+    #   pydantic-settings
+tzdata==2026.2 ; sys_platform == 'emscripten' or sys_platform == 'win32'
+    # via pandas
+urllib3==2.7.0
+    # via requests
+uvicorn==0.48.0
+    # via
+    #   gradio
+    #   mcp

wheels/{diff_gaussian_rasterization-1.0.0-cp310-cp310-linux_x86_64.whl → diff_gaussian_rasterization-1.0.0-cp312-cp312-linux_x86_64.whl}

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-size 618661
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+size 3950877

wheels/flash_attn-2.7.4.post1-cp310-cp310-linux_x86_64.whl

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wheels/{voxlib_ext-3.0.0-cp310-cp310-linux_x86_64.whl → grid_encoder-1.0.0-cp312-cp312-linux_x86_64.whl}

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wheels/torch_scatter-2.1.2+pt22cu121-cp310-cp310-linux_x86_64.whl

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-size 10864848

wheels/{grid_encoder-1.0.0-cp310-cp310-linux_x86_64.whl → voxlib_ext-3.0.0-cp312-cp312-linux_x86_64.whl}

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