> ## Documentation Index
> Fetch the complete documentation index at: https://jigsaw-13.mintlify.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Sentiment

> Perform line by line sentiment analysis on any text with detailed emotion detection.

## Request Parameters

### Body

<ParamField body="text" type="string" required>
  The text content to analyze for sentiment and emotion.
</ParamField>

<Snippet file="header.mdx" />

## Response Structure

<ResponseField name="success" type="boolean">
  Indicates whether the call was successful.
</ResponseField>

<ResponseField name="_usage" type="object" optional>
  Usage information for the API call.

  <Expandable title="_usage">
    <ResponseField name="input_tokens" type="number">
      Number of input tokens processed.
    </ResponseField>

    <ResponseField name="output_tokens" type="number">
      Number of output tokens generated.
    </ResponseField>

    <ResponseField name="inference_time_tokens" type="number">
      Number of tokens processed during inference time.
    </ResponseField>

    <ResponseField name="total_tokens" type="number">
      Total number of tokens used (input + output).
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseField name="log_id" type="string" optional>
  A unique identifier for the request
</ResponseField>

<ResponseField name="sentiment" type="object">
  Contains the sentiment analysis results.

  <Expandable title="Sentiment Object Structure" defaultOpen>
    <ResponseField name="emotion" type="string">
      The overall emotional tone of the text.
    </ResponseField>

    <ResponseField name="sentiment" type="string">
      The overall sentiment classification, typically "positive", "negative", or
      "neutral".
    </ResponseField>

    <ResponseField name="score" type="number">
      Numerical score representing the sentiment intensity, typically on a scale
      from 0 to 1, where higher values indicate more positive sentiment.
    </ResponseField>

    <ResponseField name="sentences" type="array">
      Detailed sentiment analysis broken down by individual sentences.

      <Expandable title="Sentence Object">
        <ResponseField name="text" type="string">
          The sentence text.
        </ResponseField>

        <ResponseField name="emotion" type="string">
          The emotional tone detected in this specific sentence.
        </ResponseField>

        <ResponseField name="sentiment" type="string">
          The sentiment classification for this specific sentence.
        </ResponseField>

        <ResponseField name="score" type="number">
          Numerical sentiment score for this specific sentence.
        </ResponseField>
      </Expandable>
    </ResponseField>
  </Expandable>
</ResponseField>

<RequestExample>
  ```javascript Javascript theme={null}
  import { JigsawStack } from "jigsawstack";

  const jigsaw = JigsawStack({ apiKey: "your-api-key" });

  const response = await jigsaw.sentiment({
    "text": "I love this product! It's amazing but the delivery was a bit late."
  })
  ```

  ```python Python theme={null}
  from jigsawstack import JigsawStack

  jigsaw = JigsawStack(api_key="your-api-key")

  response = jigsaw.sentiment({
    "text": "I love this product! It's amazing but the delivery was a bit late."
  })
  ```

  ```bash Curl theme={null}
  curl https://api.jigsawstack.com/v1/ai/sentiment \
  -X POST \
  -H 'Content-Type: application/json' \
  -H 'x-api-key: your-api-key' \
  -d '{"text":"I love this product! It\'s amazing but the delivery was a bit late."}'
  ```

  ```php PHP theme={null}
  <?php
  $ch = curl_init();
  curl_setopt($ch, CURLOPT_URL, 'https://api.jigsawstack.com/v1/ai/sentiment');
  curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
  curl_setopt($ch, CURLOPT_CUSTOMREQUEST, 'POST');
  curl_setopt($ch, CURLOPT_HTTPHEADER, [
  'Content-Type: application/json',
  'x-api-key: your-api-key',
  ]);
  curl_setopt($ch, CURLOPT_POSTFIELDS, '{"text":"I love this product! It\\s');

  $response = curl_exec($ch);

  curl_close($ch);

  ```

  ```ruby Ruby theme={null}
  require 'net/http'

  uri = URI('https://api.jigsawstack.com/v1/ai/sentiment')
  req = Net::HTTP::Post.new(uri)
  req.content_type = 'application/json'
  req['x-api-key'] = 'your-api-key'

  req.body = '{"text":"I love this product! It\\s'

  req_options = {
  use_ssl: uri.scheme == 'https'
  }
  res = Net::HTTP.start(uri.hostname, uri.port, req_options) do |http|
  http.request(req)
  end

  ```

  ```go Go theme={null}
  package main

  import (
  "fmt"
  "io"
  "log"
  "net/http"
  "strings"
  )

  func main() {
  client := &http.Client{}
  var data = strings.NewReader(`{"text":"I love this product! It\s`)
  req, err := http.NewRequest("POST", "https://api.jigsawstack.com/v1/ai/sentiment", data)
  if err != nil {
  	log.Fatal(err)
  }
  req.Header.Set("Content-Type", "application/json")
  req.Header.Set("x-api-key", "your-api-key")
  resp, err := client.Do(req)
  if err != nil {
  	log.Fatal(err)
  }
  defer resp.Body.Close()
  bodyText, err := io.ReadAll(resp.Body)
  if err != nil {
  	log.Fatal(err)
  }
  fmt.Printf("%s\n", bodyText)
  }

  ```

  ```java Java theme={null}
  import java.io.IOException;
  import java.net.URI;
  import java.net.http.HttpClient;
  import java.net.http.HttpRequest;
  import java.net.http.HttpRequest.BodyPublishers;
  import java.net.http.HttpResponse;

  HttpClient client = HttpClient.newHttpClient();

  HttpRequest request = HttpRequest.newBuilder()
  .uri(URI.create("https://api.jigsawstack.com/v1/ai/sentiment"))
  .POST(BodyPublishers.ofString("{\"text\":\"I love this product! It\\s"))
  .setHeader("Content-Type", "application/json")
  .setHeader("x-api-key", "your-api-key")
  .build();

  HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());

  ```

  ```swift Swift theme={null}
  import Foundation

  let url = URL(string: "https://api.jigsawstack.com/v1/ai/sentiment")!
  let headers = [
  "Content-Type": "application/json",
  "x-api-key": "your-api-key"
  ]

  var request = URLRequest(url: url)
  request.httpMethod = "POST"
  request.allHTTPHeaderFields = headers
  request.httpBody = "{\"text\":\"I love this product! It\\s".data(using: .utf8)

  let task = URLSession.shared.dataTask(with: request) { (data, response, error) in
  if let error = error {
      print(error)
  } else if let data = data {
      let str = String(data: data, encoding: .utf8)
      print(str ?? "")
  }
  }

  task.resume()

  ```

  ```dart Dart theme={null}
  import 'package:http/http.dart' as http;

  void main() async {
  final headers = {
  'Content-Type': 'application/json',
  'x-api-key': 'your-api-key',
  };

  final data = '{"text":"I love this product! It\\s';

  final url = Uri.parse('https://api.jigsawstack.com/v1/ai/sentiment');

  final res = await http.post(url, headers: headers, body: data);
  final status = res.statusCode;
  if (status != 200) throw Exception('http.post error: statusCode= $status');

  print(res.body);
  }

  ```

  ```kotlin Kotlin theme={null}
  import java.io.IOException
  import okhttp3.MediaType.Companion.toMediaType
  import okhttp3.OkHttpClient
  import okhttp3.Request
  import okhttp3.RequestBody.Companion.toRequestBody

  val client = OkHttpClient()

  val MEDIA_TYPE = "application/json".toMediaType()

  val requestBody = "{\"text\":\"I love this product! It\\s"

  val request = Request.Builder()
  .url("https://api.jigsawstack.com/v1/ai/sentiment")
  .post(requestBody.toRequestBody(MEDIA_TYPE))
  .header("Content-Type", "application/json")
  .header("x-api-key", "your-api-key")
  .build()

  client.newCall(request).execute().use { response ->
  if (!response.isSuccessful) throw IOException("Unexpected code $response")
  response.body!!.string()
  }

  ```

  ```csharp C# theme={null}
  using System.Net.Http.Headers;
  using System.Net.Http.Json;

  HttpClient client = new HttpClient();

  HttpRequestMessage request = new HttpRequestMessage(HttpMethod.Post, "https://api.jigsawstack.com/v1/ai/sentiment");
  request.Headers.Add("x-api-key", "your-api-key");
  request.Content = JsonContent.Create(new
  {
  text = "I love this product! It's amazing but the delivery was a bit late."
  });
  request.Content.Headers.ContentType = new MediaTypeHeaderValue("application/json");

  HttpResponseMessage response = await client.SendAsync(request);
  response.EnsureSuccessStatusCode();
  string responseBody = await response.Content.ReadAsStringAsync();

  Console.WriteLine(responseBody);
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "success": true,
    "sentiment": {
          "emotion": "love",
          "sentiment": "positive",
          "score": 0.85,
          "sentences": [
                {
                      "text": "I love this product!",
                      "emotion": "love",
                      "sentiment": "positive",
                      "score": 0.9
                },
                {
                      "text": "It's amazing but the delivery was a bit late.",
                      "emotion": "satisfaction",
                      "sentiment": "positive",
                      "score": 0.8
                }
          ]
    },
    "_usage": {
          "input_tokens": 20,
          "output_tokens": 75,
          "inference_time_tokens": 2594,
          "total_tokens": 2689
    }
  }
  ```
</ResponseExample>