El endpoint de Detección de Toxicidad devuelve un objeto JSON que contiene el texto original, una versión censurada del texto y un booleano que indica si el texto contiene profanidad.

Los campos clave en los datos de respuesta son "original" (el texto de entrada), "censurado" (el texto con las groserías reemplazadas por asteriscos) y "tiene_groserías" (un booleano que indica la presencia de lenguaje ofensivo).

Los datos de respuesta están estructurados como un objeto JSON con tres campos: "original," "censurado," y "tiene_profanidad," lo que permite un fácil análisis y utilización en aplicaciones.

El parámetro principal para el endpoint de Detección de Toxicidad es la entrada de texto, que los usuarios deben proporcionar para analizar el lenguaje tóxico.

Los usuarios pueden personalizar sus solicitudes variando el texto de entrada para analizar diferentes frases o comentarios por su toxicidad, adaptando la moderación a tipos de contenido específicos.

Los casos de uso típicos incluyen moderar comentarios en redes sociales, filtrar contenido generado por usuarios en foros y asegurar un lenguaje apropiado en chats de juegos.

La precisión de los datos se mantiene a través de algoritmos de aprendizaje automático avanzados que aprenden continuamente de conjuntos de datos diversos, asegurando una detección efectiva del lenguaje tóxico en varios contextos.

Los controles de calidad incluyen actualizaciones regulares de los modelos de aprendizaje automático, validación contra datos del mundo real y mecanismos de retroalimentación de los usuarios para mejorar las capacidades de detección a lo largo del tiempo.

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