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Classify

Automatically classify text using a custom Text Classifier ML model trained on your data.

Perfect for applying consistent labels to text (articles, video/audio transcripts, tickets, emails, reviews, comments, etc.) based on historical patterns in your data plus the semantic meaning of your text.

Example Use Cases
  • Assign labels to video/audio transcripts
  • Assign categories to product descriptions
  • Classify user reviews/comments by sentiment
  • Categorize customer feedback by topic or product
  • Flag urgent vs non-urgent customer inquiries
  • Detect spam in emails or user posts
  • Route support tickets to the right team (technical, billing, sales)
  • Assign topic to documents or articles
Categorize vs. Classify vs. Predict

See this page for details on selecting the right endpoint for your classification task.

Endpoint

POST /v20241104/classify

API Request

  • Required Parameters

    input object

    JSON object specifying a document_id or a text string to classify.

    Info

    • Example (document ID): 

      "input": {
  "type": "document_id",
  "value": "4nD1gZIB7caKVIeL2MgL"
}

    • Example (text string): 

      "input": {
  "type": "text",
  "value": "Server is down, customers cannot access the service"
}

    • For document ID:

      MinLength: 1   MaxLength: 128

    • For text string:

      MinLength: 1   MaxLength: 5000

    • Text strings have a max length (characters) specified above. To classify longer texts, first add them as a document and then classify them using their document_id.

    model_id string required

    ID of your custom ML model to use for classification.

    Info
    • You can find the model ID in your Gainly Dashboard under Settings > Custom Models.

    MinLength: 1   MaxLength: 128

    Optional Parameters

    max_labels integer

    Maximum number of labels (classifications) to assign.

    Default is 3.

    Min: 1   Max: 10

    version string required

    Version of your custom ML model to use for classification. Default is default.

    Info
    • You can find the version number in your Gainly Dashboard under Settings > Custom Models.

    • You can also mark a version as default in your Gainly Dashboard.

    • Examples: 

      "version": "2"

      "version": "default"

    MinLength: 1   MaxLength: 10

  • POST /v20241104/classify

    curl -X POST "https://api.gainly.ai/v20241104/classify" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: YOUR_API_KEY_HERE" \  # (1)!
  -d '{
    "input": {
      "type": "text",
      "value": "I love my original Listerine. This came properly packaged so it didn\'t leak. What more can I say. Kills germs by the millions. Great for use with my waterpick and I feel so clean."
    },
    "model_id": "support_priority_v1"
  }'
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    # Prompt for AI coding assistants/IDEs (e.g., ChatGPT, Claude, GitHub Copilot, Cursor, Windsurf)

Using the Gainly API:
1. Write code to call the classify operation (see OpenAPI spec: https://api.gainly.ai/v20241104/openapi.json)
2. Implement authentication using the header "X-API-Key" as described in the docs: https://docs.gainly.ai/latest/api-reference/authentication/
3. Implement rate limit handling as described in the docs: https://docs.gainly.ai/latest/api-reference/rate-limits/
4. Implement error handling
5. Handle the response according to the ClassifyResults schema in the OpenAPI spec

    using System.Net.Http;
using System.Text.Json;
using System.Text;

var client = new HttpClient();

var url = "https://api.gainly.ai/v20241104/classify";

var payload = new {
    input = new {
        type = "text",
        value = "Server is down, customers cannot access the service"
    },
    model_id = "support_priority_v1"
};

var content = new StringContent(
    JsonSerializer.Serialize(payload),
    Encoding.UTF8,
    "application/json"
);

client.DefaultRequestHeaders.Add("X-API-Key", "YOUR_API_KEY_HERE"); // (1)!

var response = await client.PostAsync(url, content);
var result = await response.Content.ReadAsStringAsync();
Console.WriteLine(result);
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "net/http"
)

func main() {
    url := "https://api.gainly.ai/v20241104/classify"

    payload := map[string]interface{}{
        "input": map[string]interface{}{
            "type": "text",
            "value": "Server is down, customers cannot access the service",
        },
        "model_id": "support_priority_v1",
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Content-Type", "application/json")
    req.Header.Set("X-API-Key", "YOUR_API_KEY_HERE") // (1)!

    resp, _ := http.DefaultClient.Do(req)
    defer resp.Body.Close()

    var result map[string]interface{}
    json.NewDecoder(resp.Body).Decode(&result)
    fmt.Println(result)
}
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

var client = HttpClient.newHttpClient();

var url = "https://api.gainly.ai/v20241104/classify";

var payload = """
    {
        "input": {
            "type": "text",
            "value": "Server is down, customers cannot access the service"
        },
        "model_id": "support_priority_v1"
    }
    """;

var request = HttpRequest.newBuilder()
    .uri(URI.create(url))
    .header("Content-Type", "application/json")
    .header("X-API-Key", "YOUR_API_KEY_HERE") // (1)!
    .POST(HttpRequest.BodyPublishers.ofString(payload))
    .build();

var response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    const axios = require('axios');  // or: import axios from 'axios';

const url = 'https://api.gainly.ai/v20241104/classify';

const payload = {
    input: {
        type: "text",
        value: "Server is down, customers cannot access the service"
    },
    model_id: "support_priority_v1"
};

const headers = {
    'Content-Type': 'application/json',
    'X-API-Key': 'YOUR_API_KEY_HERE' // (1)!
};

axios.post(url, payload, { headers })
    .then(response => console.log(response.data))
    .catch(error => console.error('Error:', error.message));
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    <?php

$client = new \GuzzleHttp\Client();

$url = 'https://api.gainly.ai/v20241104/classify';

$payload = [
    'input' => [
        'type' => 'text',
        'value' => 'I love my original Listerine. This came properly packaged so it didn\'t leak. What more can I say. Kills germs by the millions. Great for use with my waterpick and I feel so clean.',
    ],
    'model_id' => 'support_priority_v1',
];

$response = $client->request('POST', $url, [
    'json' => $payload,
    'headers' => [
        'Content-Type' => 'application/json',
        'X-API-Key' => 'YOUR_API_KEY_HERE' # (1)!
    ],
]);

echo $response->getBody();
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    import requests

url = "https://api.gainly.ai/v20241104/classify"

payload = {
    "input": {
        "type": "text",
        "value": "Server is down, customers cannot access the service"
    },
    "model_id": "support_priority_v1"
}

headers = {
    "Content-Type": "application/json",
    "X-API-Key": "YOUR_API_KEY_HERE" # (1)!
}

response = requests.post(url, json=payload, headers=headers)
data = response.json()
print(data)
    1. Replace YOUR_API_KEY_HERE with the value of your API key.
    require 'json'
require 'uri'
require 'net/http'
require 'openssl'

url = URI('https://api.gainly.ai/v20241104/classify')

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

request = Net::HTTP::Post.new(url)
request['Content-Type'] = 'application/json'
request['X-API-Key'] = 'YOUR_API_KEY_HERE' # (1)!
request.body = {
    input: {
        type: "text",
        value: "Server is down, customers cannot access the service"
    },
    model_id: "support_priority_v1"
}.to_json

response = http.request(request)
puts response.read_body
    1. Replace YOUR_API_KEY_HERE with the value of your API key.

API Response

{
    "object": "classify_result",
    "url": "/v20241104/classify",
    "data": [
      {
        "label": "urgent",
        "confidence_score": 0.89,
        "alternatives": [
            {
                "label": "normal",
                "confidence_score": 0.08
            },
            {
                "label": "low",
                "confidence_score": 0.03
            }
        ]
      }
    ],
    "input": {
        "type": "text",
        "value": "Server is down, customers cannot access the service"
    },
    "model_id": "support_priority_v1",
    "version": "default",
    "max_labels": 3,
    "token_usage": {
        "semantic_tokens": 69,
        "llm_tokens": {
            "llm_output_tokens": 0,
            "llm_input_tokens": 0,
            "model": null
        }
    },
    "livemode": true
}

Label

label indicates the classification assigned by the custom model to the input text. confidence_score is the probability score (0-1) assigned by the custom model to the predicted label. alternatives is a list of other possible labels along with their corresponding probability scores.

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"data": [
    {
        "label": "urgent",          // The predicted label
        "confidence_score": 0.89,   // Confidence score (0-1)
        "alternatives": [           // Optional: other possible labels
            {
                "label": "normal",
                "confidence_score": 0.08
            },
            {
                "label": "low",
                "confidence_score": 0.03
            }
        ]
    }
],

This example is from a model that was trained to assign a priority to support tickets based on the ticket text, and assigns a label of urgent, normal or low.