Create Model

curl --request POST \
  --url https://api.sophra.org/api/nous/learn/models \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "search-ranking-model-v1",
  "type": "ranking",
  "hyperparameters": {
    "learning_rate": 0.001,
    "batch_size": 32,
    "epochs": 100,
    "optimizer": "adam",
    "hidden_layers": [
      128,
      64,
      32
    ],
    "dropout_rate": 0.2
  },
  "trainingParams": {
    "validation_split": 0.2,
    "early_stopping": {
      "patience": 5,
      "min_delta": 0.001
    },
    "class_weights": {
      "0": 1,
      "1": 2
    }
  }
}
'

import requests

url = "https://api.sophra.org/api/nous/learn/models"

payload = {
    "name": "search-ranking-model-v1",
    "type": "ranking",
    "hyperparameters": {
        "learning_rate": 0.001,
        "batch_size": 32,
        "epochs": 100,
        "optimizer": "adam",
        "hidden_layers": [128, 64, 32],
        "dropout_rate": 0.2
    },
    "trainingParams": {
        "validation_split": 0.2,
        "early_stopping": {
            "patience": 5,
            "min_delta": 0.001
        },
        "class_weights": {
            "0": 1,
            "1": 2
        }
    }
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'search-ranking-model-v1',
    type: 'ranking',
    hyperparameters: {
      learning_rate: 0.001,
      batch_size: 32,
      epochs: 100,
      optimizer: 'adam',
      hidden_layers: [128, 64, 32],
      dropout_rate: 0.2
    },
    trainingParams: {
      validation_split: 0.2,
      early_stopping: {patience: 5, min_delta: 0.001},
      class_weights: {'0': 1, '1': 2}
    }
  })
};

fetch('https://api.sophra.org/api/nous/learn/models', 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.sophra.org/api/nous/learn/models",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => 'search-ranking-model-v1',
    'type' => 'ranking',
    'hyperparameters' => [
        'learning_rate' => 0.001,
        'batch_size' => 32,
        'epochs' => 100,
        'optimizer' => 'adam',
        'hidden_layers' => [
                128,
                64,
                32
        ],
        'dropout_rate' => 0.2
    ],
    'trainingParams' => [
        'validation_split' => 0.2,
        'early_stopping' => [
                'patience' => 5,
                'min_delta' => 0.001
        ],
        'class_weights' => [
                '0' => 1,
                '1' => 2
        ]
    ]
  ]),
  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 := "https://api.sophra.org/api/nous/learn/models"

	payload := strings.NewReader("{\n  \"name\": \"search-ranking-model-v1\",\n  \"type\": \"ranking\",\n  \"hyperparameters\": {\n    \"learning_rate\": 0.001,\n    \"batch_size\": 32,\n    \"epochs\": 100,\n    \"optimizer\": \"adam\",\n    \"hidden_layers\": [\n      128,\n      64,\n      32\n    ],\n    \"dropout_rate\": 0.2\n  },\n  \"trainingParams\": {\n    \"validation_split\": 0.2,\n    \"early_stopping\": {\n      \"patience\": 5,\n      \"min_delta\": 0.001\n    },\n    \"class_weights\": {\n      \"0\": 1,\n      \"1\": 2\n    }\n  }\n}")

	req, _ := http.NewRequest("POST", 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.post("https://api.sophra.org/api/nous/learn/models")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"search-ranking-model-v1\",\n  \"type\": \"ranking\",\n  \"hyperparameters\": {\n    \"learning_rate\": 0.001,\n    \"batch_size\": 32,\n    \"epochs\": 100,\n    \"optimizer\": \"adam\",\n    \"hidden_layers\": [\n      128,\n      64,\n      32\n    ],\n    \"dropout_rate\": 0.2\n  },\n  \"trainingParams\": {\n    \"validation_split\": 0.2,\n    \"early_stopping\": {\n      \"patience\": 5,\n      \"min_delta\": 0.001\n    },\n    \"class_weights\": {\n      \"0\": 1,\n      \"1\": 2\n    }\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.sophra.org/api/nous/learn/models")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"search-ranking-model-v1\",\n  \"type\": \"ranking\",\n  \"hyperparameters\": {\n    \"learning_rate\": 0.001,\n    \"batch_size\": 32,\n    \"epochs\": 100,\n    \"optimizer\": \"adam\",\n    \"hidden_layers\": [\n      128,\n      64,\n      32\n    ],\n    \"dropout_rate\": 0.2\n  },\n  \"trainingParams\": {\n    \"validation_split\": 0.2,\n    \"early_stopping\": {\n      \"patience\": 5,\n      \"min_delta\": 0.001\n    },\n    \"class_weights\": {\n      \"0\": 1,\n      \"1\": 2\n    }\n  }\n}"

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

{
  "success": true,
  "data": {
    "modelId": "<string>",
    "status": "created",
    "config": {}
  }
}

POST

nous

learn

models

Create Model

curl --request POST \
  --url https://api.sophra.org/api/nous/learn/models \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "search-ranking-model-v1",
  "type": "ranking",
  "hyperparameters": {
    "learning_rate": 0.001,
    "batch_size": 32,
    "epochs": 100,
    "optimizer": "adam",
    "hidden_layers": [
      128,
      64,
      32
    ],
    "dropout_rate": 0.2
  },
  "trainingParams": {
    "validation_split": 0.2,
    "early_stopping": {
      "patience": 5,
      "min_delta": 0.001
    },
    "class_weights": {
      "0": 1,
      "1": 2
    }
  }
}
'

import requests

url = "https://api.sophra.org/api/nous/learn/models"

payload = {
    "name": "search-ranking-model-v1",
    "type": "ranking",
    "hyperparameters": {
        "learning_rate": 0.001,
        "batch_size": 32,
        "epochs": 100,
        "optimizer": "adam",
        "hidden_layers": [128, 64, 32],
        "dropout_rate": 0.2
    },
    "trainingParams": {
        "validation_split": 0.2,
        "early_stopping": {
            "patience": 5,
            "min_delta": 0.001
        },
        "class_weights": {
            "0": 1,
            "1": 2
        }
    }
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'search-ranking-model-v1',
    type: 'ranking',
    hyperparameters: {
      learning_rate: 0.001,
      batch_size: 32,
      epochs: 100,
      optimizer: 'adam',
      hidden_layers: [128, 64, 32],
      dropout_rate: 0.2
    },
    trainingParams: {
      validation_split: 0.2,
      early_stopping: {patience: 5, min_delta: 0.001},
      class_weights: {'0': 1, '1': 2}
    }
  })
};

fetch('https://api.sophra.org/api/nous/learn/models', 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.sophra.org/api/nous/learn/models",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => 'search-ranking-model-v1',
    'type' => 'ranking',
    'hyperparameters' => [
        'learning_rate' => 0.001,
        'batch_size' => 32,
        'epochs' => 100,
        'optimizer' => 'adam',
        'hidden_layers' => [
                128,
                64,
                32
        ],
        'dropout_rate' => 0.2
    ],
    'trainingParams' => [
        'validation_split' => 0.2,
        'early_stopping' => [
                'patience' => 5,
                'min_delta' => 0.001
        ],
        'class_weights' => [
                '0' => 1,
                '1' => 2
        ]
    ]
  ]),
  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 := "https://api.sophra.org/api/nous/learn/models"

	payload := strings.NewReader("{\n  \"name\": \"search-ranking-model-v1\",\n  \"type\": \"ranking\",\n  \"hyperparameters\": {\n    \"learning_rate\": 0.001,\n    \"batch_size\": 32,\n    \"epochs\": 100,\n    \"optimizer\": \"adam\",\n    \"hidden_layers\": [\n      128,\n      64,\n      32\n    ],\n    \"dropout_rate\": 0.2\n  },\n  \"trainingParams\": {\n    \"validation_split\": 0.2,\n    \"early_stopping\": {\n      \"patience\": 5,\n      \"min_delta\": 0.001\n    },\n    \"class_weights\": {\n      \"0\": 1,\n      \"1\": 2\n    }\n  }\n}")

	req, _ := http.NewRequest("POST", 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.post("https://api.sophra.org/api/nous/learn/models")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"search-ranking-model-v1\",\n  \"type\": \"ranking\",\n  \"hyperparameters\": {\n    \"learning_rate\": 0.001,\n    \"batch_size\": 32,\n    \"epochs\": 100,\n    \"optimizer\": \"adam\",\n    \"hidden_layers\": [\n      128,\n      64,\n      32\n    ],\n    \"dropout_rate\": 0.2\n  },\n  \"trainingParams\": {\n    \"validation_split\": 0.2,\n    \"early_stopping\": {\n      \"patience\": 5,\n      \"min_delta\": 0.001\n    },\n    \"class_weights\": {\n      \"0\": 1,\n      \"1\": 2\n    }\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.sophra.org/api/nous/learn/models")

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

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"search-ranking-model-v1\",\n  \"type\": \"ranking\",\n  \"hyperparameters\": {\n    \"learning_rate\": 0.001,\n    \"batch_size\": 32,\n    \"epochs\": 100,\n    \"optimizer\": \"adam\",\n    \"hidden_layers\": [\n      128,\n      64,\n      32\n    ],\n    \"dropout_rate\": 0.2\n  },\n  \"trainingParams\": {\n    \"validation_split\": 0.2,\n    \"early_stopping\": {\n      \"patience\": 5,\n      \"min_delta\": 0.001\n    },\n    \"class_weights\": {\n      \"0\": 1,\n      \"1\": 2\n    }\n  }\n}"

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

{
  "success": true,
  "data": {
    "modelId": "<string>",
    "status": "created",
    "config": {}
  }
}

Body

application/json

name

string

required

Model name

type

enum<string>

required

Type of model

Available options:

ranking,

classification,

regression

hyperparameters

object

required

Show child attributes

trainingParams

object

Show child attributes

Response

201 - application/json

Model created successfully

success

boolean

data

object

Show child attributes

Cortex > Metrics

Administration

Cortex > System Health

Cortex > Session Management

Cortex > Index Management

Cortex > Document Operations

Cortex > Search Operations

Cortex > A/B Testing

Cortex > Analytics

Cortex > Feedback

Nous > Health

Nous > A/B Testing

Nous > Adaptation

Nous > Learning > Models

Nous > Learning > Search Patterns

Nous > Learning > Feedback

Nous > Learning > Metrics and Events

Nous > Signals

API Reference

Create Model

Body

Response