curl --request GET \
  --url https://be.datagol.ai/conversations/{conversationId}/messages \
  --header 'x-auth-token: <api-key>'

import requests

url = "https://be.datagol.ai/conversations/{conversationId}/messages"

headers = {"x-auth-token": "<api-key>"}

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

print(response.text)

const options = {method: 'GET', headers: {'x-auth-token': '<api-key>'}};

fetch('https://be.datagol.ai/conversations/{conversationId}/messages', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://be.datagol.ai/conversations/{conversationId}/messages",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "x-auth-token: <api-key>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://be.datagol.ai/conversations/{conversationId}/messages"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("x-auth-token", "<api-key>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://be.datagol.ai/conversations/{conversationId}/messages")
  .header("x-auth-token", "<api-key>")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://be.datagol.ai/conversations/{conversationId}/messages")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Get.new(url)
request["x-auth-token"] = '<api-key>'

response = http.request(request)
puts response.read_body

[
  {
    "id": 7902,
    "conversationId": "c920e1f5-2ac7-4f17-aed7-b260e464c022",
    "userId": 206,
    "userQuery": "Can you do a RFM analysis on this data?",
    "modelResponse": [
      {
        "code": null,
        "data": "Here’s the plan and step-by-step pseudo-code for the RFM analysis, followed by a complete, executable Python script...\n\n```python\nimport pandas as pd\nimport numpy as np...",
        "type": "TEXT",
        "state": null,
        "message": null,
        "metadata": null
      }
    ],
    "uiMetadata": null,
    "messageMetadata": {
      "chainId": "1762280699",
      "agentType": "NewPythonAgent",
      "workbookId": null,
      "executionData": [
        {
          "content": "<table class=\"dataframe dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>user_id</th>\n      <th>email</th>\n      <th>full_name</th>...",
          "response_type": "dataframe"
        },
        {
          "content": {
            "agent": "Expert Selector",
            "model": "o4-mini"
          },
          "response_type": "tool_start"
        },
        {
          "content": {
            "input": "Reasoning Effort: medium",
            "action": "Thinking"
          },
          "response_type": "tool_call"
        },
        {
          "content": "requires_dataset: true\nexpert: \"Data Analyst\"\nconfidence: 9",
          "response_type": "processing"
        }
      ]
    },
    "isPinned": false,
    "timestamp": "2025-11-04T18:24:59.695784Z",
    "feedback": null
  }
]