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POST
/
v1
/
models
Create a new analysis model
curl --request POST \
  --url https://api.example.com/v1/models \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "Customer Service Evaluation v2",
  "description": "Comprehensive evaluation model for customer service calls",
  "prompt": "Evaluate the call based on professional standards...",
  "template_variables": [
    {
      "key": "greeting_quality",
      "type": "INTEGER",
      "required": true
    },
    {
      "key": "resolution_achieved",
      "type": "BOOLEAN",
      "required": true
    }
  ],
  "transcription_prompt": "Customer service call for telecom company.",
  "summarize_call": true,
  "summarize_prompt": "Summarize the key points of this call.",
  "neurascore_template": false,
  "enabled": true
}
'
import requests

url = "https://api.example.com/v1/models"

payload = {
    "name": "Customer Service Evaluation v2",
    "description": "Comprehensive evaluation model for customer service calls",
    "prompt": "Evaluate the call based on professional standards...",
    "template_variables": [
        {
            "key": "greeting_quality",
            "type": "INTEGER",
            "required": True
        },
        {
            "key": "resolution_achieved",
            "type": "BOOLEAN",
            "required": True
        }
    ],
    "transcription_prompt": "Customer service call for telecom company.",
    "summarize_call": True,
    "summarize_prompt": "Summarize the key points of this call.",
    "neurascore_template": False,
    "enabled": True
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

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

print(response.text)
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: 'Customer Service Evaluation v2',
    description: 'Comprehensive evaluation model for customer service calls',
    prompt: 'Evaluate the call based on professional standards...',
    template_variables: [
      {key: 'greeting_quality', type: 'INTEGER', required: true},
      {key: 'resolution_achieved', type: 'BOOLEAN', required: true}
    ],
    transcription_prompt: 'Customer service call for telecom company.',
    summarize_call: true,
    summarize_prompt: 'Summarize the key points of this call.',
    neurascore_template: false,
    enabled: true
  })
};

fetch('https://api.example.com/v1/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.example.com/v1/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' => 'Customer Service Evaluation v2',
    'description' => 'Comprehensive evaluation model for customer service calls',
    'prompt' => 'Evaluate the call based on professional standards...',
    'template_variables' => [
        [
                'key' => 'greeting_quality',
                'type' => 'INTEGER',
                'required' => true
        ],
        [
                'key' => 'resolution_achieved',
                'type' => 'BOOLEAN',
                'required' => true
        ]
    ],
    'transcription_prompt' => 'Customer service call for telecom company.',
    'summarize_call' => true,
    'summarize_prompt' => 'Summarize the key points of this call.',
    'neurascore_template' => false,
    'enabled' => true
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "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.example.com/v1/models"

	payload := strings.NewReader("{\n  \"name\": \"Customer Service Evaluation v2\",\n  \"description\": \"Comprehensive evaluation model for customer service calls\",\n  \"prompt\": \"Evaluate the call based on professional standards...\",\n  \"template_variables\": [\n    {\n      \"key\": \"greeting_quality\",\n      \"type\": \"INTEGER\",\n      \"required\": true\n    },\n    {\n      \"key\": \"resolution_achieved\",\n      \"type\": \"BOOLEAN\",\n      \"required\": true\n    }\n  ],\n  \"transcription_prompt\": \"Customer service call for telecom company.\",\n  \"summarize_call\": true,\n  \"summarize_prompt\": \"Summarize the key points of this call.\",\n  \"neurascore_template\": false,\n  \"enabled\": true\n}")

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

	req.Header.Add("Authorization", "Bearer <token>")
	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.example.com/v1/models")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"Customer Service Evaluation v2\",\n  \"description\": \"Comprehensive evaluation model for customer service calls\",\n  \"prompt\": \"Evaluate the call based on professional standards...\",\n  \"template_variables\": [\n    {\n      \"key\": \"greeting_quality\",\n      \"type\": \"INTEGER\",\n      \"required\": true\n    },\n    {\n      \"key\": \"resolution_achieved\",\n      \"type\": \"BOOLEAN\",\n      \"required\": true\n    }\n  ],\n  \"transcription_prompt\": \"Customer service call for telecom company.\",\n  \"summarize_call\": true,\n  \"summarize_prompt\": \"Summarize the key points of this call.\",\n  \"neurascore_template\": false,\n  \"enabled\": true\n}")
  .asString();
require 'uri'
require 'net/http'

url = URI("https://api.example.com/v1/models")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"Customer Service Evaluation v2\",\n  \"description\": \"Comprehensive evaluation model for customer service calls\",\n  \"prompt\": \"Evaluate the call based on professional standards...\",\n  \"template_variables\": [\n    {\n      \"key\": \"greeting_quality\",\n      \"type\": \"INTEGER\",\n      \"required\": true\n    },\n    {\n      \"key\": \"resolution_achieved\",\n      \"type\": \"BOOLEAN\",\n      \"required\": true\n    }\n  ],\n  \"transcription_prompt\": \"Customer service call for telecom company.\",\n  \"summarize_call\": true,\n  \"summarize_prompt\": \"Summarize the key points of this call.\",\n  \"neurascore_template\": false,\n  \"enabled\": true\n}"

response = http.request(request)
puts response.read_body
{
  "id": 1,
  "client_id": "client_abc123",
  "name": "Customer Service Evaluation v2",
  "description": "Comprehensive evaluation model for customer service calls",
  "prompt": "<string>",
  "summarize_call": true,
  "neurascore_template": false,
  "enabled": true,
  "created_at": "2023-11-07T05:31:56Z",
  "created_by": "<string>",
  "template_metadata": [],
  "transcription_prompt": "Customer service call for telecom company.",
  "summarize_prompt": "Summarize the key points of this call.",
  "updated_at": "2023-11-07T05:31:56Z",
  "updated_by": "<string>"
}
{
  "code": "001-001-0001",
  "message": "The requested resource was not found"
}
{
  "code": "001-001-0001",
  "message": "The requested resource was not found"
}
{
  "code": "001-001-0001",
  "message": "The requested resource was not found"
}

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

Request body for creating or updating an analysis model

​
name
string
required

Unique name for this analysis model

Required string length: 1 - 255
Example:

"Customer Service Evaluation v2"

​
description
string
required

Detailed description of what this model evaluates

Example:

"Comprehensive evaluation model for customer service calls including greeting, problem resolution, and closing."

​
prompt
string
required

Analysis configuration defining evaluation criteria and scoring rules

​
template_variables
TemplateVariable · object[]

List of variables to extract during analysis

​
transcription_prompt
string
default:""

Custom prompt to guide audio transcription. Include domain-specific vocabulary, proper nouns, or context to improve accuracy.

Example:

"This is a customer service call for a telecommunications company."

​
summarize_call
boolean
default:false

Enable automatic call summary generation after analysis

Example:

true

​
summarize_prompt
string
default:""

Custom prompt for summary generation. Only used if summarize_call is true.

Example:

"Summarize the key points of this customer service call."

​
neurascore_template
boolean
default:false

Whether this model uses the NeuraScore scoring system

Example:

false

​
enabled
boolean
default:true

Whether this model is active. Disabled models are hidden from listings.

Example:

true

Response

Successful Response

Analysis model details and configuration

​
id
integer
required

Unique identifier for this model

Example:

1

​
client_id
string
required

Owner client identifier

Example:

"client_abc123"

​
name
string
required

Model name

Example:

"Customer Service Evaluation v2"

​
description
string
required

Detailed description of the model

Example:

"Comprehensive evaluation model for customer service calls"

​
prompt
string
required

Analysis configuration and evaluation criteria

​
summarize_call
boolean
required

Whether automatic summary generation is enabled

Example:

true

​
neurascore_template
boolean
required

Whether this model uses the NeuraScore scoring system

Example:

false

​
enabled
boolean
required

Whether this model is active and available for use

Example:

true

​
created_at
string<date-time>
required

Timestamp when model was created (UTC)

​
created_by
string
required

Creator identifier

​
template_metadata
ClientTemplateMetadata · object[]

Configured metadata fields for additional data extraction

​
transcription_prompt
string
default:""

Custom prompt for audio transcription

Example:

"Customer service call for telecom company."

​
summarize_prompt
string
default:""

Custom prompt for summary generation

Example:

"Summarize the key points of this call."

​
updated_at
string<date-time>

Timestamp of last update (UTC)

​
updated_by
string

Last updater identifier