To use this API, users must enter a text to detect the language.

Language Text Detector API identifies the language of a given text accurately and efficiently.

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Zyla provides a wide range of integration methods for almost all programming languages. You can use these codes to integrate with your project as you need.

Language detection is crucial for various applications such as multilingual customer support, content filtering, and personalized recommendations.

The Detect Language endpoint returns a JSON object containing the detected language code of the input text. For example, a response may look like `{"detectedLanguageCode":"es"}` indicating Spanish.

The primary field in the response is `detectedLanguageCode`, which specifies the ISO 639-1 code of the identified language. Additional fields may be included in future updates for enhanced functionality.

The response data is structured in JSON format, making it easy to parse and integrate into applications. The main object contains key-value pairs, with the detected language code as the primary output.

The primary parameter for the Detect Language endpoint is the text input, which should be a string containing the text whose language you want to identify. No additional parameters are required.

Data accuracy is maintained through advanced natural language processing techniques and continuous model improvements using large datasets. This ensures reliable detection of languages, even for nuanced text.

Typical use cases include multilingual customer support, content localization, language-driven analytics, social media monitoring, and global marketing campaigns, allowing businesses to tailor their strategies effectively.

Users can utilize the returned language code to route customer queries to appropriate support teams, filter content for localization, or analyze trends in multilingual data for insights and decision-making.

The Detect Language endpoint provides information on the language of the input text, enabling applications to understand and respond to user content in the correct language, enhancing user experience.

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