curl --request GET \
  --url https://api.yourapp.com/api/ai/models \
  --header 'Authorization: Bearer <token>'

const response = await fetch('https://api.yourapp.com/api/ai/models', {
  method: 'GET',
  headers: {
    'Authorization': 'Bearer <token>'
  }
});

const data = await response.json();

import requests

url = "https://api.yourapp.com/api/ai/models"
headers = {
    "Authorization": "Bearer <token>"
}

response = requests.get(url, headers=headers)
data = response.json()

{
  "success": true,
  "models": {
    "llms": [
      {
        "id": "gpt-4o",
        "name": "GPT-4 Optimized",
        "provider": "OpenAI",
        "contextWindow": 128000
      },
      {
        "id": "claude-3-5-sonnet-20241022",
        "name": "Claude 3.5 Sonnet",
        "provider": "Anthropic",
        "contextWindow": 200000
      },
      {
        "id": "gemini-2.0-flash-exp",
        "name": "Gemini 2.0 Flash",
        "provider": "Google",
        "contextWindow": 1000000
      }
    ],
    "embeddings": [
      {
        "id": "text-embedding-3-large",
        "name": "Text Embedding 3 Large",
        "provider": "OpenAI",
        "dimensions": 3072
      },
      {
        "id": "text-embedding-3-small",
        "name": "Text Embedding 3 Small",
        "provider": "OpenAI",
        "dimensions": 1536
      }
    ],
    "image": [
      {
        "id": "dall-e-3",
        "name": "DALL-E 3",
        "provider": "OpenAI"
      },
      {
        "id": "google/gemini-2.5-flash-image",
        "name": "Gemini 2.5 Flash Image",
        "provider": "Google"
      }
    ]
  },
  "vectorstores": [
    {
      "id": "pinecone",
      "name": "Pinecone"
    },
    {
      "id": "chroma",
      "name": "Chroma"
    }
  ]
}

{
  "success": false,
  "message": "Unauthorized"
}