GET
/
api
/
environments
curl --request GET \
  --url https://dashboard.amdatascience.com/api/environments \
  --header 'apiKey: <api-key>'
{
  "environments": [
    {
      "description": "Python environment for working with AI tools and SDKs. Includes tools like AlphAI, OpenAI/Anthropic/Cohere SDKs, Scikit Learn, pandas, and numpy.",
      "environment_id": "ai",
      "name": "AI"
    },
    {
      "description": "Environment equipped with PyTorch, a powerful open-source tensor library for training neural network models written for Python.",
      "environment_id": "torch",
      "name": "PyTorch"
    },
    {
      "description": "Environment set up for JAX, a library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning.",
      "environment_id": "jax",
      "name": "JAX"
    },
    {
      "description": "Python environment for working with Hugging Face tools like transformers and datasets. Contains the Hugging Face Notebooks repostory and is powered by PyTorch.",
      "environment_id": "huggingface",
      "name": "Hugging Face"
    },
    {
      "description": "Python environment for working with RAPIDS.ai tools like cuDF, cuML, cuGraph, etc. all powered by NVIDIA GPUs.",
      "environment_id": "rapidsai",
      "name": "RAPIDS.ai"
    },
    {
      "description": "Environment set up for CuPy, a GPU-accelerated library for numerical computations; NumPy and SciPy for GPUs.",
      "environment_id": "cupy",
      "name": "CuPy"
    },
    {
      "description": "Environment equipped with Numba, a just-in-time compiler for Python that helps developers acclerate scientific computing with GPUs.",
      "environment_id": "numba",
      "name": "Numba"
    },
    {
      "description": "Environment for AI in chemistry and material science @ Meta. Previously known as Open Catalyst Project.",
      "environment_id": "fairchem",
      "name": "FAIR Chemistry"
    },
    {
      "description": "Environment for PyTorch Geometric, a Graph Neural Network Library for PyTorch",
      "environment_id": "pyg",
      "name": "PyTorch Geometric"
    }
  ],
  "status": "success"
}

Authorizations

apiKey
string
header
required

Response

200 - application/json
Get Environments
environments
object[]
Example:
[
  {
    "description": "Python environment for working with AI tools and SDKs. Includes tools like AlphAI, OpenAI/Anthropic/Cohere SDKs, Scikit Learn, pandas, and numpy.",
    "environment_id": "ai",
    "name": "AI"
  },
  {
    "description": "Environment equipped with PyTorch, a powerful open-source tensor library for training neural network models written for Python.",
    "environment_id": "torch",
    "name": "PyTorch"
  },
  {
    "description": "Environment set up for JAX, a library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and large-scale machine learning.",
    "environment_id": "jax",
    "name": "JAX"
  },
  {
    "description": "Python environment for working with Hugging Face tools like transformers and datasets. Contains the Hugging Face Notebooks repostory and is powered by PyTorch.",
    "environment_id": "huggingface",
    "name": "Hugging Face"
  },
  {
    "description": "Python environment for working with RAPIDS.ai tools like cuDF, cuML, cuGraph, etc. all powered by NVIDIA GPUs.",
    "environment_id": "rapidsai",
    "name": "RAPIDS.ai"
  },
  {
    "description": "Environment set up for CuPy, a GPU-accelerated library for numerical computations; NumPy and SciPy for GPUs.",
    "environment_id": "cupy",
    "name": "CuPy"
  },
  {
    "description": "Environment equipped with Numba, a just-in-time compiler for Python that helps developers acclerate scientific computing with GPUs.",
    "environment_id": "numba",
    "name": "Numba"
  },
  {
    "description": "Environment for AI in chemistry and material science @ Meta. Previously known as Open Catalyst Project.",
    "environment_id": "fairchem",
    "name": "FAIR Chemistry"
  },
  {
    "description": "Environment for PyTorch Geometric, a Graph Neural Network Library for PyTorch",
    "environment_id": "pyg",
    "name": "PyTorch Geometric"
  }
]
status
string
Example:

"success"