curl --request PUT \
  --url http://localhost:8080/api/v2/config/memory/semantic \
  --header 'Content-Type: application/json' \
  --data '
{
  "enabled": true,
  "database": "<string>",
  "storage_backend": "<string>",
  "feature_store": "<string>",
  "vector_collection": "<string>",
  "vector_dimensions": 1,
  "llm_model": "<string>",
  "embedding_model": "<string>",
  "ingestion_trigger_messages": 1,
  "ingestion_trigger_age_seconds": 1
}
'

import requests

url = "http://localhost:8080/api/v2/config/memory/semantic"

payload = {
    "enabled": True,
    "database": "<string>",
    "storage_backend": "<string>",
    "feature_store": "<string>",
    "vector_collection": "<string>",
    "vector_dimensions": 1,
    "llm_model": "<string>",
    "embedding_model": "<string>",
    "ingestion_trigger_messages": 1,
    "ingestion_trigger_age_seconds": 1
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'PUT',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    enabled: true,
    database: '<string>',
    storage_backend: '<string>',
    feature_store: '<string>',
    vector_collection: '<string>',
    vector_dimensions: 1,
    llm_model: '<string>',
    embedding_model: '<string>',
    ingestion_trigger_messages: 1,
    ingestion_trigger_age_seconds: 1
  })
};

fetch('http://localhost:8080/api/v2/config/memory/semantic', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_PORT => "8080",
  CURLOPT_URL => "http://localhost:8080/api/v2/config/memory/semantic",
  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([
    'enabled' => true,
    'database' => '<string>',
    'storage_backend' => '<string>',
    'feature_store' => '<string>',
    'vector_collection' => '<string>',
    'vector_dimensions' => 1,
    'llm_model' => '<string>',
    'embedding_model' => '<string>',
    'ingestion_trigger_messages' => 1,
    'ingestion_trigger_age_seconds' => 1
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($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 := "http://localhost:8080/api/v2/config/memory/semantic"

	payload := strings.NewReader("{\n  \"enabled\": true,\n  \"database\": \"<string>\",\n  \"storage_backend\": \"<string>\",\n  \"feature_store\": \"<string>\",\n  \"vector_collection\": \"<string>\",\n  \"vector_dimensions\": 1,\n  \"llm_model\": \"<string>\",\n  \"embedding_model\": \"<string>\",\n  \"ingestion_trigger_messages\": 1,\n  \"ingestion_trigger_age_seconds\": 1\n}")

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

	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("http://localhost:8080/api/v2/config/memory/semantic")
  .header("Content-Type", "application/json")
  .body("{\n  \"enabled\": true,\n  \"database\": \"<string>\",\n  \"storage_backend\": \"<string>\",\n  \"feature_store\": \"<string>\",\n  \"vector_collection\": \"<string>\",\n  \"vector_dimensions\": 1,\n  \"llm_model\": \"<string>\",\n  \"embedding_model\": \"<string>\",\n  \"ingestion_trigger_messages\": 1,\n  \"ingestion_trigger_age_seconds\": 1\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("http://localhost:8080/api/v2/config/memory/semantic")

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

request = Net::HTTP::Put.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"enabled\": true,\n  \"database\": \"<string>\",\n  \"storage_backend\": \"<string>\",\n  \"feature_store\": \"<string>\",\n  \"vector_collection\": \"<string>\",\n  \"vector_dimensions\": 1,\n  \"llm_model\": \"<string>\",\n  \"embedding_model\": \"<string>\",\n  \"ingestion_trigger_messages\": 1,\n  \"ingestion_trigger_age_seconds\": 1\n}"

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

{
  "success": true,
  "message": "<string>"
}

{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}