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Take an object as input instead of positional parameters.
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@juliensalinas
juliensalinas committed Oct 2, 2023
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66 changes: 33 additions & 33 deletions README.md
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Expand Up @@ -29,7 +29,7 @@ Here is a full example that summarizes a text using Facebook's Bart Large CNN mo
```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('bart-large-cnn','4eC39HqLyjWDarjtT1zdp7dc')
const client = new NLPCloudClient({model:'bart-large-cnn', token:'4eC39HqLyjWDarjtT1zdp7dc'})

client.summarization(`One month after the United States began what has become a
troubled rollout of a national COVID vaccination campaign, the effort is finally
Expand Down Expand Up @@ -57,7 +57,7 @@ Here is a full example that does the same thing, but on a GPU:
```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('bart-large-cnn','4eC39HqLyjWDarjtT1zdp7dc', true)
const client = new NLPCloudClient({model:'bart-large-cnn', token:'4eC39HqLyjWDarjtT1zdp7dc'}, true)

client.summarization(`One month after the United States began what has become a
troubled rollout of a national COVID vaccination campaign, the effort is finally
Expand Down Expand Up @@ -85,7 +85,7 @@ Here is a full example that does the same thing, but on a French text:
```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('bart-large-cnn','4eC39HqLyjWDarjtT1zdp7dc', true, 'fra_Latn')
const client = new NLPCloudClient({model:'bart-large-cnn', token:'4eC39HqLyjWDarjtT1zdp7dc', gpu:true, lang:'fra_Latn'})

client.summarization(`Sur des images aériennes, prises la veille par un vol de surveillance
de la Nouvelle-Zélande, la côte d’une île est bordée d’arbres passés du vert
Expand Down Expand Up @@ -130,31 +130,31 @@ Your token can be retrieved from your [NLP Cloud dashboard](https://nlpcloud.io/
```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('<model>','<your token>')
const client = new NLPCloudClient({model:'<model>', token:'<your token>'})
```

If you want to use a GPU, pass `true` as the 3rd argument.
If you want to use a GPU, pass `true` as the gpu argument.

```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('<model>', '<your token>', true)
const client = new NLPCloudClient({model:'<model>', token:'<your token>', gpu:true})
```

If you want to use the multilingual add-on in order to process non-English texts, set `lang='<your language code>'` as the 4th argument. For example, if you want to process French text, you should set `lang='fra_Latn'` as the 4th argument.
If you want to use the multilingual add-on in order to process non-English texts, set `'<your language code>'` as the lang argument. For example, if you want to process French text, you should set `lang:'fra_Latn'`.

```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('<model>', '<your token>', false, '<your language code>')
const client = new NLPCloudClient({model:'<model>', token:'<your token>', lang:'<your language code>'})
```

If you want to make asynchronous requests, pass `true` as the 4th argument.
If you want to make asynchronous requests, pass `true` as the async argument.

```js
const NLPCloudClient = require('nlpcloud');

const client = new NLPCloudClient('<model>', '<your token>', false, '<your language code>', true)
const client = new NLPCloudClient({model:'<model>', token:'<your token>', async:true)
```
If you are making asynchronous requests, you will always receive a quick response containing a URL. You should then poll this URL with `asyncResult()` on a regular basis (every 10 seconds for example) in order to check if the result is available. Here is an example:
Expand All @@ -168,7 +168,7 @@ client.asyncResult('https://api.nlpcloud.io/v1/get-async-result/21718218-42e8-4b
Call the `adGeneration()` method and pass the keywords you want to use to generate your ad or product description.
```js
client.adGeneration(['keyword 1', 'keyword 2', ...])
client.adGeneration({keywords:['keyword 1', 'keyword 2', ...]})
```
### Automatic Speech Recognition (Speech to Text) Endpoint
Expand All @@ -180,7 +180,7 @@ Call the `asr()` method and pass the following arguments:
1. (Optional) `inputLanguage`: the language of your file as ISO code
```js
client.asr('Your url')
client.asr({url:'Your url'})
```
### Chatbot Endpoint
Expand All @@ -192,7 +192,7 @@ Call the `chatbot()` method and pass the following arguments:
1. (Optional) `history` The history of your previous exchanges with the model
```js
client.chatbot('<Your input>')
client.chatbot({text:'<Your input>'})
```
### Classification Endpoint
Expand All @@ -204,31 +204,31 @@ Call the `classification()` method and pass the following arguments:
1. (Optional) `multiClass` Whether the classification should be multi-class or not, as a boolean
```js
client.classification('<Your block of text>', ['label 1', 'label 2', ...])
client.classification({text:'<Your block of text>', labels:['label 1', 'label 2', ...]})
```
### Code Generation Endpoint
Call the `codeGeneration()` method and pass the instruction for the code you want to generate.
```js
client.codeGeneration('<Your instruction>')
client.codeGeneration({instruction:'<Your instruction>'})
```
### 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>')
client.dependencies({text:'<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>', ...])
client.embeddings({sentences:['<Text 1>', '<Text 2>', '<Text 3>', ...]})
```
The above command returns a JSON object.
Expand All @@ -238,7 +238,7 @@ The above command returns a JSON object.
Call the `entities()` method and pass the text you want to perform named entity recognition (NER) on.
```js
client.entities('<Your block of text>')
client.entities({text:'<Your block of text>'})
```
### Generation Endpoint
Expand All @@ -260,47 +260,47 @@ Call the `generation()` method and pass the following arguments:
1. (Optional) `removeEndSequence`: Optional. Whether you want to remove the `endSequence` string from the result. Defaults to false.
```js
client.generation('<Your input text>')
client.generation({text:'<Your input text>'})
```
### Grammar and Spelling Correction Endpoint
Call the `gsCorrection()` method and pass the text you want to correct.
```js
client.gsCorrection('<The text you want to correct>')
client.gsCorrection({text:'<The text you want to correct>'})
```
### Image Generation Endpoint
Call the `imageGeneration()` method and pass the text you want to use to generate your image.
```js
client.imageGeneration('<Your text instruction>')
client.imageGeneration({text:'<Your text instruction>'})
```
### Intent Classification Endpoint
Call the `intentClassification()` method and pass the text you want to analyze in order to detect the intent.
```js
client.intentClassification('<The text you want to analyze>')
client.intentClassification({text:'<The text you want to analyze>'})
```
### Keywords and Keyphrases Extraction Endpoint
Call the `kwKpExtraction()` method and pass the text you want to extract keywords and keyphrases from.
```js
client.kwKpExtraction('<The text you want to analyze>')
client.kwKpExtraction({text:'<The text you want to analyze>'})
```
### Language Detection Endpoint
Call the `langdetection()` method and pass the text you want to analyze in order to detect the languages.
```js
client.langdetection('<The text you want to analyze>')
client.langdetection({text:'<The text you want to analyze>'})
```
### Library Versions Endpoint
Expand All @@ -319,7 +319,7 @@ Call the `question()` method and pass the following:
1. A context that the model will use to try to answer your question
```js
client.question('<Your question>','<Your context>')
client.question({question:'<Your question>', context:'<Your context>'})
```
### Semantic Search Endpoint
Expand All @@ -337,7 +337,7 @@ The above command returns a JSON object.
Call the `semanticSimilarity()` method and pass an array made up of 2 blocks of text that you want to compare.
```python
client.semanticSimilarity(['<Block of text 1>', '<Block of text 2>'])
client.semanticSimilarity({sentences:['<Block of text 1>', '<Block of text 2>']})
```
The above command returns a JSON object.
Expand All @@ -347,23 +347,23 @@ The above command returns a JSON object.
Call the `sentenceDependencies()` method and pass a block of text made up of several sentences you want to perform POS + arcs on.
```js
client.sentenceDependencies('<Your block of text>')
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:
```js
client.sentiment('<Your block of text>')
client.sentiment({text:'<Your block of text>'})
```
### Speech Synthesis Endpoint
Call the `speechSynthesis()` method and pass the text you want to convert to audio:
```js
client.speechSynthesis("<Your block of text>")
client.speechSynthesis({text:"<Your block of text>"})
```
The above command returns a JSON object.
Expand All @@ -373,29 +373,29 @@ The above command returns a JSON object.
Call the `summarization()` method and pass the text you want to summarize.
```js
client.summarization('<Your text to summarize>')
client.summarization({text:'<Your text to summarize>'})
```
### Paraphrasing Endpoint
Call the `paraphrasing()` method and pass the text you want to paraphrase.
```js
client.paraphrasing('<Your text to paraphrase>')
client.paraphrasing({text:'<Your text to paraphrase>'})
```
### Tokenization Endpoint
Call the `tokens()` method and pass the text you want to tokenize.
```js
client.tokens('<Your block of text>')
client.tokens({text:'<Your block of text>'})
```
### Translation Endpoint
Call the `translation()` method and pass the text you want to translate.
```js
client.translation('<Your text to translate>')
client.translation({text:'<Your text to translate>'})
```
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