Targeted Sentiment Analysis - Beta

Analyze sentiment for specific topics.

POST /api/ai/v1/targeted-sentiment

Targeted Sentiment Analysis - Beta

cURL

curl --request POST \
  --url https://{subdomain}.domo.com/api/ai/v1/targeted-sentiment \
  --header 'Content-Type: application/json' \
  --header 'X-DOMO-Developer-Token: <api-key>' \
  --data '
{
  "input": [
    {
      "type": "TEXT",
      "text": "The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get."
    }
  ],
  "topics": [
    {
      "topic": "product_quality",
      "description": "Quality and features of the product"
    },
    {
      "topic": "shipping",
      "description": "Shipping speed and delivery experience"
    },
    {
      "topic": "customer_service",
      "description": "Customer support experience"
    },
    {
      "topic": "pricing",
      "description": "Price and value for money"
    }
  ]
}
'

import requests

url = "https://{subdomain}.domo.com/api/ai/v1/targeted-sentiment"

payload = {
    "input": [
        {
            "type": "TEXT",
            "text": "The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get."
        }
    ],
    "topics": [
        {
            "topic": "product_quality",
            "description": "Quality and features of the product"
        },
        {
            "topic": "shipping",
            "description": "Shipping speed and delivery experience"
        },
        {
            "topic": "customer_service",
            "description": "Customer support experience"
        },
        {
            "topic": "pricing",
            "description": "Price and value for money"
        }
    ]
}
headers = {
    "X-DOMO-Developer-Token": "<api-key>",
    "Content-Type": "application/json"
}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'X-DOMO-Developer-Token': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    input: [
      {
        type: 'TEXT',
        text: 'The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get.'
      }
    ],
    topics: [
      {topic: 'product_quality', description: 'Quality and features of the product'},
      {topic: 'shipping', description: 'Shipping speed and delivery experience'},
      {topic: 'customer_service', description: 'Customer support experience'},
      {topic: 'pricing', description: 'Price and value for money'}
    ]
  })
};

fetch('https://{subdomain}.domo.com/api/ai/v1/targeted-sentiment', 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://{subdomain}.domo.com/api/ai/v1/targeted-sentiment",
  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([
    'input' => [
        [
                'type' => 'TEXT',
                'text' => 'The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get.'
        ]
    ],
    'topics' => [
        [
                'topic' => 'product_quality',
                'description' => 'Quality and features of the product'
        ],
        [
                'topic' => 'shipping',
                'description' => 'Shipping speed and delivery experience'
        ],
        [
                'topic' => 'customer_service',
                'description' => 'Customer support experience'
        ],
        [
                'topic' => 'pricing',
                'description' => 'Price and value for money'
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "X-DOMO-Developer-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"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://{subdomain}.domo.com/api/ai/v1/targeted-sentiment"

	payload := strings.NewReader("{\n  \"input\": [\n    {\n      \"type\": \"TEXT\",\n      \"text\": \"The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get.\"\n    }\n  ],\n  \"topics\": [\n    {\n      \"topic\": \"product_quality\",\n      \"description\": \"Quality and features of the product\"\n    },\n    {\n      \"topic\": \"shipping\",\n      \"description\": \"Shipping speed and delivery experience\"\n    },\n    {\n      \"topic\": \"customer_service\",\n      \"description\": \"Customer support experience\"\n    },\n    {\n      \"topic\": \"pricing\",\n      \"description\": \"Price and value for money\"\n    }\n  ]\n}")

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

	req.Header.Add("X-DOMO-Developer-Token", "<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.post("https://{subdomain}.domo.com/api/ai/v1/targeted-sentiment")
  .header("X-DOMO-Developer-Token", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"input\": [\n    {\n      \"type\": \"TEXT\",\n      \"text\": \"The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get.\"\n    }\n  ],\n  \"topics\": [\n    {\n      \"topic\": \"product_quality\",\n      \"description\": \"Quality and features of the product\"\n    },\n    {\n      \"topic\": \"shipping\",\n      \"description\": \"Shipping speed and delivery experience\"\n    },\n    {\n      \"topic\": \"customer_service\",\n      \"description\": \"Customer support experience\"\n    },\n    {\n      \"topic\": \"pricing\",\n      \"description\": \"Price and value for money\"\n    }\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://{subdomain}.domo.com/api/ai/v1/targeted-sentiment")

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

request = Net::HTTP::Post.new(url)
request["X-DOMO-Developer-Token"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"input\": [\n    {\n      \"type\": \"TEXT\",\n      \"text\": \"The product quality is excellent and works perfectly. However, the shipping took longer than expected and customer service was slow to respond. Pricing is fair for what you get.\"\n    }\n  ],\n  \"topics\": [\n    {\n      \"topic\": \"product_quality\",\n      \"description\": \"Quality and features of the product\"\n    },\n    {\n      \"topic\": \"shipping\",\n      \"description\": \"Shipping speed and delivery experience\"\n    },\n    {\n      \"topic\": \"customer_service\",\n      \"description\": \"Customer support experience\"\n    },\n    {\n      \"topic\": \"pricing\",\n      \"description\": \"Price and value for money\"\n    }\n  ]\n}"

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

200

{
  "type": "TARGETED",
  "topicSentiments": {
    "shipping": "negative",
    "product_quality": "positive",
    "customer_service": "negative",
    "pricing": "positive"
  },
  "model": "domo.domo_ai.domogpt-medium-v2.1:anthropic",
  "isCustomerModel": false,
  "sessionId": "34c1b391-1302-4149-89ad-dd5c9a009e89",
  "requestId": "d81674e9-984d-4ca3-b943-acf1fdbc95b4",
  "modelProviderUsage": null
}

"<string>"

Authorizations

X-DOMO-Developer-Token · string · header · required

Body

application/json

Request for sentiment analysis using the Messages API.

Supports two modes:

• Simple sentiment: When topics is null/empty, analyzes overall sentiment
• Targeted sentiment: When topics provided, analyzes sentiment for each topic

Validation happens primarily in AIValidator, not in this constructor.

input · object[] · required

The input message content to analyze (text, images, documents, etc.)

Text-based message content.

Option 1

Option 2

Option 3

Show child attributes

topics · object[]

Optional list of topics for targeted sentiment analysis. When provided, sentiment is analyzed for each topic individually. When omitted or empty, overall sentiment of the content is analyzed. Topic names must start with a letter and contain only letters, numbers, and underscores (e.g., 'customer_service', 'productQuality').

Show child attributes

instructions · string

Optional instructions for sentiment analysis behavior

model · string

The ID of the model to use (optional, uses default if not specified)

modelConfiguration · object

Additional model parameters (temperature, max_tokens, etc.)

Show child attributes

sessionId · string<uuid>

AI session ID for associating with existing session

reasoningConfig · object

Configuration for reasoning behavior

Show child attributes

targetedSentiment · boolean

Returns true if this is a targeted sentiment request (has topics).

simpleSentiment · boolean

Returns true if this is a simple sentiment request (no topics).

Response

200

application/json

Successful targeted sentiment analysis response.

Response for targeted sentiment analysis containing sentiment per topic.

topicSentiments · object

Map of topic to sentiment (includes NOT_APPLICABLE for unmentioned topics)

Show child attributes

model · string

The ID of the model used

isCustomerModel · boolean

Whether the model is a customer model

sessionId · string<uuid>

The AI session ID

requestId · string<uuid>

The request ID

modelProviderUsage · object

Token usage information

Show child attributes