curl --request PUT \
  --url https://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey} \
  --header 'Content-Type: application/json' \
  --header 'X-Clinia-API-Key: <api-key>' \
  --data '
{
  "profile": {
    "properties": {},
    "description": "<string>",
    "contained": {}
  }
}
'

import requests

url = "https://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey}"

payload = { "profile": {
        "properties": {},
        "description": "<string>",
        "contained": {}
    } }
headers = {
    "X-Clinia-API-Key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.put(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'PUT',
  headers: {'X-Clinia-API-Key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({profile: {properties: {}, description: '<string>', contained: {}}})
};

fetch('https://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey}', 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://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey}",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "PUT",
  CURLOPT_POSTFIELDS => json_encode([
    'profile' => [
        'properties' => [
                
        ],
        'description' => '<string>',
        'contained' => [
                
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-Clinia-API-Key: <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"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey}"

	payload := strings.NewReader("{\n  \"profile\": {\n    \"properties\": {},\n    \"description\": \"<string>\",\n    \"contained\": {}\n  }\n}")

	req, _ := http.NewRequest("PUT", url, payload)

	req.Header.Add("X-Clinia-API-Key", "<api-key>")
	req.Header.Add("Content-Type", "application/json")

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

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

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.put("https://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey}")
  .header("X-Clinia-API-Key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"profile\": {\n    \"properties\": {},\n    \"description\": \"<string>\",\n    \"contained\": {}\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.{workspaceId}.clinia.cloud/sources/{sourceKey}/v1/collections/{collectionKey}")

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

request = Net::HTTP::Put.new(url)
request["X-Clinia-API-Key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"profile\": {\n    \"properties\": {},\n    \"description\": \"<string>\",\n    \"contained\": {}\n  }\n}"

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

{
  "key": "<string>",
  "profile": {
    "properties": {},
    "key": "<string>",
    "description": "<string>",
    "contained": {}
  },
  "pipeline": {
    "steps": [
      {
        "vectorizer": {
          "inputProperty": "content.passages",
          "propertyKey": "vector",
          "modelId": "text-embedding-004",
          "dimensions": 768,
          "propertyDescription": "The vectorized content"
        },
        "trigger": {
          "operator": {
            "and": "<array>",
            "id": "<string>"
          }
        }
      }
    ],
    "id": "<string>"
  }
}

{
  "key": "<string>",
  "profile": {
    "properties": {},
    "key": "<string>",
    "description": "<string>",
    "contained": {}
  },
  "pipeline": {
    "steps": [
      {
        "vectorizer": {
          "inputProperty": "content.passages",
          "propertyKey": "vector",
          "modelId": "text-embedding-004",
          "dimensions": 768,
          "propertyDescription": "The vectorized content"
        },
        "trigger": {
          "operator": {
            "and": "<array>",
            "id": "<string>"
          }
        }
      }
    ],
    "id": "<string>"
  }
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}

{
  "message": "<string>",
  "details": "<array>",
  "additionalContext": {}
}