nlpcloud - npm Package Compare versions

Comparing version 1.0.20 to 1.0.21

dist/index.d.ts

@@ -9,9 +9,18 @@ export = Client;
     rootURL: string;
-    entities(text: string): Promise<{
+
+    adGeneration(keywords: string[]): Promise<{
         status: number;
         statusText: string;
         data: {
-            entities: { start: number; end: number; type: string; text: string }[];
+            generated_text: string;
         };
     }>;
+    chatbot(input: string, history: { input: string, response: string }[]): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            response: string;
+            history: { input: string, response: string }[];
+        };
+    }>;
     classification(text: string, labels: string[], multiClass?: boolean): Promise<{
@@ -25,2 +34,23 @@ status: number;
     }>;
+    dependencies(text: string): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            words: { text: string, tag: string }[];
+        };
+    }>;
+    embeddings(text: string[]): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            score: number[][];
+        };
+    }>;
+    entities(text: string): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            entities: { start: number; end: number; type: string; text: string }[];
+        };
+    }>;
     generation(text: string, minLength?: number, maxLength?: number, lengthNoInput?: boolean, endSequence?: string, removeInput?: boolean, doSample?: boolean, numBeams?: number, earlyStopping?: boolean, noRepeatNgramSize?: number, numReturnSequences?: number, topK?: number, topP?: number, temperature?: number, repetitionPenalty?: number, lengthPenalty?: number, badWords?: string[], removeEndSequence?: boolean): Promise<{
@@ -33,10 +63,43 @@ status: number;
         };
-    }>;;
-    sentiment(text: string): Promise<{
+    }>;
+    gsCorrection(text: string): Promise<{
         status: number;
         statusText: string;
         data: {
-            scored_labels: { label: string, score: number }[];
+            correction: string;
         };
     }>;
+    intentClassification(text: string): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            intent: string;
+        };
+    }>;
+    kwKpExtraction(text: string): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            keywords_and_keyphrases: string[];
+        };
+    }>;
+    langdetection(text: string): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            languages: any[];
+        };
+    }>;
+    libVersions(): Promise<{
+        status: number;
+        statusText: string;
+        data: any;
+    }>;
+    paraphrasing(text: string): Promise<{
+        status: number;
+        statusText: string;
+        data: {
+            paraphrased_text: string;
+        };
+    }>;
     question(context: string, question: string): Promise<{
@@ -52,49 +115,45 @@ status: number;
     }>;
-    summarization(text: string): Promise<{
+    semanticSimilarity(text: string[]): Promise<{
         status: number;
         statusText: string;
         data: {
-            summary_text: string;
+            score: number;
         };
     }>;
-    translation(text: string): Promise<{
+    sentenceDependencies(text: string): Promise<{
         status: number;
         statusText: string;
         data: {
-            translation_text: string;
+            sentence_dependencies: { sentence: string, dependencies: { words: { text: string, tag: string }[], arcs: { start: number, end: number, label: string, text: string, dir: string }[] } }[];
         };
     }>;
-    langdetection(text: string): Promise<{
+    sentiment(text: string): Promise<{
         status: number;
         statusText: string;
         data: {
-            languages: any[];
+            scored_labels: { label: string, score: number }[];
         };
     }>;
-    tokens(text: string): Promise<{
+    summarization(text: string): Promise<{
         status: number;
         statusText: string;
         data: {
-            tokens: { start: number, end: number, index: number, text: string, lemma: string, ws_after: boolean }[];
+            summary_text: string;
         };
     }>;
-    dependencies(text: string): Promise<{
+    translation(text: string): Promise<{
         status: number;
         statusText: string;
         data: {
-            words: { text: string, tag: string }[];
+            translation_text: string;
         };
     }>;
-    sentenceDependencies(text: string): Promise<{
+    tokens(text: string): Promise<{
         status: number;
         statusText: string;
         data: {
-            sentence_dependencies: { sentence: string, dependencies: { words: { text: string, tag: string }[], arcs: { start: number, end: number, label: string, text: string, dir: string }[] } }[];
+            tokens: { start: number, end: number, index: number, text: string, lemma: string, ws_after: boolean }[];
         };
     }>;
-    libVersions(): Promise<{
-        status: number;
-        statusText: string;
-        data: any;
-    }>;
+
 }

index.js

@@ -27,11 +27,20 @@ const axios = require('axios')
 
-  entities(text, searchedEntity = null) {
+
+  adGeneration(keywords) {
     const payload = {
-      'text': text,
-      'searchedEntity': searchedEntity
+      'keywords': keywords
     };
 
-    return axios.post(this.rootURL + '/' + 'entities', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'ad-generation', payload, { headers: this.headers })
   }
 
+  chatbot(input, history = null) {
+    const payload = {
+      'input': input,
+      'history': history
+    };
+
+    return axios.post(this.rootURL + '/' + 'chatbot', payload, { headers: this.headers })
+  }
+
   classification(text, labels = null, multiClass = null) {
@@ -47,2 +56,27 @@ const payload = {
 
+  dependencies(text) {
+    const payload = {
+      'text': text
+    };
+
+    return axios.post(this.rootURL + '/' + 'dependencies', payload, { headers: this.headers })
+  }
+
+  embeddings(sentences) {
+    const payload = {
+      'sentences': sentences
+    };
+
+    return axios.post(this.rootURL + '/' + 'embeddings', payload, { headers: this.headers })
+  }
+
+  entities(text, searchedEntity = null) {
+    const payload = {
+      'text': text,
+      'searchedEntity': searchedEntity
+    };
+
+    return axios.post(this.rootURL + '/' + 'entities', payload, { headers: this.headers })
+  }
+
   generation(text, minLength = null, maxLength = null, lengthNoInput = null,
@@ -76,3 +110,3 @@ endSequence = null, removeInput = null, doSample = null, numBeams = null, earlyStopping = null,
 
-  sentiment(text) {
+  gsCorrection(text) {
     const payload = {
@@ -82,15 +116,14 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'sentiment', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'gs-correction', payload, { headers: this.headers })
   }
 
-  question(question, context = null) {
+  intentClassification(text) {
     const payload = {
-      'question': question,
-      'context': context
+      'text': text
     };
 
-    return axios.post(this.rootURL + '/' + 'question', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'intent-classification', payload, { headers: this.headers })
   }
 
-  summarization(text) {
+  kwKpExtraction(text) {
     const payload = {
@@ -100,6 +133,6 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'summarization', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'kw-kp-extraction', payload, { headers: this.headers })
   }
 
-  paraphrasing(text) {
+  langdetection(text) {
     const payload = {
@@ -109,6 +142,11 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'paraphrasing', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'langdetection', payload, { headers: this.headers })
   }
 
-  translation(text) {
+
+  libVersions() {
+    return axios.get(this.rootURL + '/' + 'versions', { headers: this.headers })
+  }
+
+  paraphrasing(text) {
     const payload = {
@@ -118,11 +156,12 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'translation', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'paraphrasing', payload, { headers: this.headers })
   }
 
-  langdetection(text) {
+  question(question, context = null) {
     const payload = {
-      'text': text
+      'question': question,
+      'context': context
     };
 
-    return axios.post(this.rootURL + '/' + 'langdetection', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'question', payload, { headers: this.headers })
   }
@@ -138,3 +177,3 @@
 
-  tokens(text) {
+  sentenceDependencies(text) {
     const payload = {
@@ -144,6 +183,6 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'tokens', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'sentence-dependencies', payload, { headers: this.headers })
   }
 
-  dependencies(text) {
+  sentiment(text) {
     const payload = {
@@ -153,6 +192,6 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'dependencies', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'sentiment', payload, { headers: this.headers })
   }
 
-  sentenceDependencies(text) {
+  summarization(text) {
     const payload = {
@@ -162,18 +201,23 @@ 'text': text
 
-    return axios.post(this.rootURL + '/' + 'sentence-dependencies', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'summarization', payload, { headers: this.headers })
   }
 
-  embeddings(sentences) {
+  tokens(text) {
     const payload = {
-      'sentences': sentences
+      'text': text
     };
 
-    return axios.post(this.rootURL + '/' + 'embeddings', payload, { headers: this.headers })
+    return axios.post(this.rootURL + '/' + 'tokens', payload, { headers: this.headers })
   }
 
-  libVersions() {
-    return axios.get(this.rootURL + '/' + 'versions', { headers: this.headers })
+  translation(text) {
+    const payload = {
+      'text': text
+    };
+
+    return axios.post(this.rootURL + '/' + 'translation', payload, { headers: this.headers })
   }
+
 }
 
 module.exports = Client

package.json

 {
   "name": "nlpcloud",
-  "version": "1.0.20",
+  "version": "1.0.21",
   "description": "NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, text generation, question answering, machine translation, language detection, semantic similarity, tokenization, POS tagging, 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.io\n\nDocumentation: https://docs.nlpcloud.io",
@@ -5,0 +5,0 @@ "main": "index.js",

README.md

 # Node.js Client For NLP Cloud
 
-This is the Node.js client for the [NLP Cloud](https://nlpcloud.io) API. See the [documentation](https://docs.nlpcloud.io) for more details.
+This is the Node.js client (with Typescript types) for the [NLP Cloud](https://nlpcloud.io) API. See the [documentation](https://docs.nlpcloud.io) for more details.
 
-NLP Cloud serves high performance pre-trained for NER, sentiment-analysis, classification, summarization, text generation, question answering, machine translation, language detection, tokenization, lemmatization, POS tagging, and dependency parsing. It is ready for production, served through a REST API.
+NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, question answering, machine translation, language detection, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. production, served through a REST API.
 
@@ -118,10 +118,21 @@ You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models.
 
-### Entities Endpoint
+### Ad Generation and Product Description Generation Endpoint
 
-Call the `entities()` method and pass the text you want to perform named entity recognition (NER) on.
+Call the `adGeneration()` method and pass the keywords you want to use to generate your ad or product description.
 
 ```js
-client.entities("<Your block of text>")
+client.adGeneration(["keyword 1", "keyword 2", ...])
 ```
 
+### Chatbot/Conversational AI Endpoint
+
+Call the `chatbot()` method and pass the following arguments:
+
+1. Your input
+1. (Optional) `history` The history of your previous exchanges with the model
+
+```js
+client.chatbot("<Your input>")
+```
+
 ### Classification Endpoint
@@ -136,7 +147,33 @@
 ```js
-client.classification("<Your block of text>", ["label 1", "label 2", "..."])
+client.classification("<Your block of text>", ["label 1", "label 2", ...])
 ```
 
-### Text Generation Endpoint
+### Dependencies Endpoint
 
+Call the `dependencies()` method and pass the text you want to perform part of speech tagging (POS) + arcs on.
+
+```js
+client.dependencies("<Your block of text>")
+```
+
+### Embeddings Endpoint
+
+Call the `embeddings()` method and pass an array of blocks of text that you want to extract embeddings from.
+
+```js
+client.embeddings(["<Text 1>", "<Text 2>", "<Text 3>", ...])
+```
+
+The above command returns a JSON object.
+
+### Entities Endpoint
+
+Call the `entities()` method and pass the text you want to perform named entity recognition (NER) on.
+
+```js
+client.entities("<Your block of text>")
+```
+
+### Generation Endpoint
+
 Call the `generation()` method and pass the following arguments:
@@ -167,51 +204,51 @@
 
-### Sentiment Analysis Endpoint
+### Grammar and Spelling Correction Endpoint
 
-Call the `sentiment()` method and pass the text you want to analyze the sentiment of:
+Call the `gsCorrection()` method and pass the text you want to correct.
 
 ```js
-client.sentiment("<Your block of text>")
+client.gsCorrection("<The text you want to correct>")
 ```
 
-### Question Answering Endpoint
+### Intent Classification Endpoint
 
-Call the `question()` method and pass the following:
+Call the `intentClassification()` method and pass the text you want to analyze in order to detect the intent.
 
-1. Your question
-1. A context that the model will use to try to answer your question
-
 ```js
-client.question("<Your question>","<Your context>")
+client.intentClassification("<The text you want to analyze>")
 ```
 
-### Summarization Endpoint
+### Keywords and Keyphrases Extraction Endpoint
 
-Call the `summarization()` method and pass the text you want to summarize.
+Call the `kwKpExtraction()` method and pass the text you want to extract keywords and keyphrases from.
 
 ```js
-client.summarization("<Your text to summarize>")
+client.kwKpExtraction("<The text you want to analyze>")
 ```
 
-### Paraphrasing Endpoint
+### Language Detection Endpoint
 
-Call the `paraphrasing()` method and pass the text you want to paraphrase.
+Call the `langdetection()` method and pass the text you want to analyze in order to detect the languages.
 
 ```js
-client.paraphrasing("<Your text to paraphrase>")
+client.langdetection("<The text you want to analyze>")
 ```
 
-### Translation Endpoint
+### Library Versions Endpoint
 
-Call the `translation()` method and pass the text you want to translate.
+Call the `libVersions()` method to know the versions of the libraries used behind the hood with the model (for example the PyTorch, TensorFlow, or spaCy version used).
 
 ```js
-client.translation("<Your text to translate>")
+client.libVersions()
 ```
 
-### Language Detection Endpoint
+### Question Answering Endpoint
 
-Call the `langdetection()` method and pass the text you want to analyze in order to detect the languages.
+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
+
 ```js
-client.langdetection("<The text you want to analyze>")
+client.question("<Your question>","<Your context>")
 ```
@@ -229,42 +266,48 @@
 
-### Tokenization Endpoint
+### Sentence Dependencies Endpoint
 
-Call the `tokens()` method and pass the text you want to tokenize.
+Call the `sentenceDependencies()` method and pass a block of text made up of several sentencies you want to perform POS + arcs on.
 
 ```js
-client.tokens("<Your block of text>")
+client.sentenceDependencies("<Your block of text>")
 ```
 
-### Dependencies Endpoint
+### Sentiment Analysis Endpoint
 
-Call the `dependencies()` method and pass the text you want to perform part of speech tagging (POS) + arcs on.
+Call the `sentiment()` method and pass the text you want to analyze the sentiment of:
 
 ```js
-client.dependencies("<Your block of text>")
+client.sentiment("<Your block of text>")
 ```
 
-### Sentence Dependencies Endpoint
+### Summarization Endpoint
 
-Call the `sentenceDependencies()` method and pass a block of text made up of several sentencies you want to perform POS + arcs on.
+Call the `summarization()` method and pass the text you want to summarize.
 
 ```js
-client.sentenceDependencies("<Your block of text>")
+client.summarization("<Your text to summarize>")
 ```
 
-### Embeddings Endpoint
+### Paraphrasing Endpoint
 
-Call the `embeddings()` method and pass an array of blocks of text that you want to extract embeddings from.
+Call the `paraphrasing()` method and pass the text you want to paraphrase.
 
 ```js
-client.embeddings(["<Text 1>", "<Text 2>", "<Tex 3>", ...])
+client.paraphrasing("<Your text to paraphrase>")
 ```
 
-The above command returns a JSON object.
+### Tokenization Endpoint
 
-### Library Versions Endpoint
+Call the `tokens()` method and pass the text you want to tokenize.
 
-Call the `libVersions()` method to know the versions of the libraries used behind the hood with the model (for example the PyTorch, TensorFlow, or spaCy version used).
+```js
+client.tokens("<Your block of text>")
+```
 
+### Translation Endpoint
+
+Call the `translation()` method and pass the text you want to translate.
+
 ```js
-client.libVersions()
+client.translation("<Your text to translate>")
 ```

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Improved metrics

Total package byte prevSize

25847

increased by16.5%

Lines of code

362

increased by32.12%

Number of lines in readme file

310

increased by16.1%

No dependency changes