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Get AI Model List

2 min read

The Smartrerbot AI API enables the retrieval of knowledge base data for a specified chatbot by sending a GET request to the /chat/Chatbot/ModelList endpoint.

Endpoint #

Request URL: https://chat.smarterbot.ai/chat/Chatbot/ModelList

Method: GET

Request Headers #

The API request must include the following headers:

  • Authorization: <Your-Secret-Key> – string, required – The secret key for authenticating the API request
  • Content-Type: application/json – string, required – The content type of the request payload (must be application/json)

Example Request #

JavaScript (Fetch API) #

const res = await fetch('https://chat.smarterbot.ai/chat/Chatbot/ModelList', {
method: 'GET',
headers: {
"Authorization": "<Your-Secret-Key>",
"Content-Type": "application/json"
},
body: JSON.stringify({})
});

const data = await res.json();
console.log(data);

Python (Requests Library) #

import requests
import json

url = 'https://chat.smarterbot.ai/chat/Chatbot/ModelList'
headers = {
"Authorization": "<Your-Secret-Key>",
"Content-Type": "application/json"
}
data = {}

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

cURL #

curl 'https://chat.smarterbot.ai/chat/Chatbot/ModelList' \
-X GET \
-H 'Authorization: <Your-Secret-Key>' \
-H 'Content-Type: application/json' \
-d '{}'

HTTP Request #

GET /chat/Chatbot/ModelList HTTP/1.1
Host: chat.smarterbot.ai
Authorization: <Your-Secret-Key>
Content-Type: application/json

{}

Response #

The API response will be a JSON object with the following structure:

{
// array - List of knowledge items
"Data": [
{
"Key": "2",
"Value": "gpt-4o",
"Status": true
},
{
"Key": "3",
"Value": "gpt-4o-mini",
"Status": true
},
{
"Key": "22",
"Value": "claude-3.5-sonnet",
"Status": false
},
{
"Key": "23",
"Value": "claude-3.5-haiku",
"Status": false
}
],
// string - API version
"Version": "1.0.0",
// boolean - Operation success status
"Success": true,
// integer - HTTP status code
"Code": 200,
// string - Error message if any
"Message": ""
}

Error Handling #

If the request fails, you should: 1. Check the HTTP status code for network-level errors 2. Examine the `Code` and `Message` fields in the response for business-level errors 3. The `Message` field will contain detailed error information

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