curl --request GET \
  --url https://api.torchcast.ai/v1/models

import requests

url = "https://api.torchcast.ai/v1/models"

response = requests.get(url)

print(response.text)

const options = {method: 'GET'};

fetch('https://api.torchcast.ai/v1/models', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "data": [
    {
      "id": "torchcast-decider-latest",
      "kind": "alias",
      "target_model": "torchcast-decider-4b-v1-1-api-1",
      "status": "active",
      "replacement_model": null,
      "price_per_million_input_tokens_usd": null,
      "max_questions": 16,
      "max_options": 255,
      "max_levels": 10,
      "max_body_bytes": 29360128
    },
    {
      "id": "torchcast-decider-4b-v1-1-api-1",
      "kind": "pinned",
      "target_model": null,
      "status": "active",
      "replacement_model": null,
      "price_per_million_input_tokens_usd": null,
      "max_questions": 16,
      "max_options": 255,
      "max_levels": 10,
      "max_body_bytes": 29360128
    }
  ]
}

{
  "error": {
    "message": "Rate limit exceeded. Retry after the indicated delay.",
    "type": "rate_limit_error",
    "code": "rate_limited"
  }
}

{
  "error": {
    "message": "Internal error.",
    "type": "api_error",
    "code": "internal_error"
  }
}

{
  "error": {
    "message": "The requested model is temporarily unavailable.",
    "type": "api_error",
    "code": "model_unavailable"
  }
}