Support target in sentiment analysis

Author: juliensalinas

README.md

@@ -302,7 +302,7 @@ client.langdetection({text:'<The text you want to analyze>'})
 Call the `question()` method and pass the following:
 
 1. Your question
-1. A context that the model will use to try to answer your question
+1. (Optional) A context that the model will use to try to answer your question
 
 ```js
 client.question({question:'<Your question>', context:'<Your context>'})
@@ -338,10 +338,13 @@ client.sentenceDependencies({text:'<Your block of text>'})
 
 ### Sentiment Analysis Endpoint
 
-Call the `sentiment()` method and pass the text you want to analyze the sentiment of:
+Call the `sentiment()` method and pass the following:
+
+1. The text you want to get the sentiment of
+1. (Optional) The target element that the sentiment should apply to
 
 ```js
-client.sentiment({text:'<Your block of text>'})
+client.sentiment({text:'<Your block of text>', target:'<Your target>'})
 ```
 
 ### Speech Synthesis Endpoint

dist/index.d.ts

@@ -267,7 +267,8 @@ declare class Client {
     }>;
 
     sentiment(params: {
-        text: string
+        text: string,
+        target?: string
     }): Promise<{
         status: number;
         statusText: string;

index.js

@@ -281,9 +281,10 @@ class Client {
 
   sentiment(params) {
     var text = params.text
-
+    var target = params.target ?? null
     const payload = {
-      'text': text
+      'text': text,
+      'target': target
     };
 
     return axios.post(this.rootURL + '/' + 'sentiment', payload, { headers: this.headers })

package.json

@@ -1,6 +1,6 @@
 {
   "name": "nlpcloud",
-  "version": "2.0.7",
+  "version": "2.0.8",
   "description": "NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, text generation, image generation, code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, speech synthesis, embeddings, and dependency parsing. It is ready for production, served through a REST API.\n\nThis is the Node.js client for the NLP Cloud API.\n\nMore details here: https://nlpcloud.com\n\nDocumentation: https://docs.nlpcloud.com",
   "main": "index.js",
   "scripts": {