1. Tone
Evaluates the sentiment of content to ensure it’s appropriate for the given context. Click here to read the eval definition of Tonea. Using Interface
Required Parameters- Input: The text content to evaluate for tone
b. Using SDK
Export your API key and Secret key into your environment variables.
2. Sexist
Identifies content with gender bias or sexist language. Checks for use of stereotypes or discriminatory language or the content has imbalanced representation or assumptions based on gender. Click here to read the eval definition of Sexista. Using Interface
Required Parameters- Input: The text content to check for sexist content
b. Using SDK
3. Toxicity
Evaluates content for toxic, harmful, or aggressive language. Such as use of profanity, threats, or abusive language. Content that could harm user relationships or escalate conflicts. Click here to read the eval definition of Toxicitya. Using Interface
Required Parameters- Input: The text content to analyse for toxic content
b. Using SDK
4. Content Moderation
Evaluates content safety using OpenAI’s content moderation system to detect and flag potentially harmful, inappropriate, or unsafe content Click here to read the eval definition of Content Moderationa. Using Interface
Required Parameters- Text: The text content to moderate
b. Using SDK
5. Bias Detection
Identifies biases in the output, including gender, racial, cultural, or ideological biases. An ideal AI generated response must be neutral language use without favouring or discriminating against any group. Click here to read the eval definition of Bias Detectiona. Using Interface
Required Parameters- Input: The text content to analyse for bias
b. Using SDK
6. Cultural Sensitivity
Analyses the output for cultural appropriateness, inclusive language, and awareness of cultural nuances. Click here to read the eval definition of Cultural Sensitivitya. Using Interface
Required Parameters- Input: The text content to analyse for cultural appropriateness
b. Using SDK
By integrating these evaluation methods, AI systems can consistently produce responsible, reliable, and socially aware outputs that enhance user trust and engagement.