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How to use Sentiment Analysis API with JavaScript | Eden AI

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Enhancing Chat Applications with Eden AI’s Sentiment Analysis API

Utilizing AI for a Positive Chat Experience

Artificial intelligence (AI) has the potential to revolutionize how we interact online. Eden AI, a provider of AI solutions, offers an application programming interface (API) that can be used to analyze the sentiment of text. With this API, developers can easily integrate sentiment analysis into JavaScript projects, creating a chat application where only positive messages are accepted.

Integrating Sentiment Analysis into a Chat Application

The integration process begins by understanding the structure of your application. For instance, in a simple chat app developed using Vue.js, the sendMessage function is triggered when a user clicks the send button. This function is where we will integrate Eden AI's sentiment analysis logic.

Generating and Integrating the API Key

Eden AI's sentiment analysis API requires an API key for authorization. This key can be generated on the Eden AI platform and then stored in an environment file in your project. You can then import the key into your JavaScript file where you'll use it to authorize requests.

Leveraging the Sentiment Analysis API

To use the API, you must specify the provider and language parameters. In this context, the provider is the source of the AI model, such as Google or Microsoft, and the language is the language of the text being analyzed. To automate language detection, you can use Eden AI’s language detection API, which returns the detected language with the highest confidence score.

Implementing the Sentiment Analysis Logic

Having integrated the sentiment analysis API, you can implement its logic in your sendMessage function. This function should send a request to the API each time a user attempts to send a message. The API will return a sentiment score, which you can store as an attribute of the message object.

Filtering Messages Based on Sentiment

The next step is to decide what score threshold you want to use for accepting messages. Any messages with a score below this threshold will be considered negative and won't be sent. This threshold can be set in a variable, such as minimumRate.

Providing User Feedback

To enhance user experience, you can provide visual feedback whenever a message is rejected due to a low sentiment score. This feedback could be a simple message like «Your message is not kind enough» along with the score the message received.

Creating a More Positive Chat Environment with Eden AI

Thanks to Eden AI's sentiment analysis and language detection APIs, you can create chat applications that foster a more positive environment. By automatically rejecting negative messages, you can ensure that the conversation remains uplifting and friendly. These AI-powered tools are easy to integrate, making them a valuable addition to any chat application.



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