Open Issues Need Help
View All on GitHubAI Summary: This issue proposes adding logging to the `emotion_detector` function to aid in debugging and final output verification. It involves printing the type of the returned object to confirm it's a dictionary and then logging the full dictionary to ensure all keys match the specified format and spelling.
EmotionSense API is a Python-based web application that detects emotions from text input using IBM Watson NLP. It includes a modular design, unit tests, error handling, static code analysis, and deployment using Flask. Ideal for learning DevOps and Software Engineering best practices.
AI Summary: This issue focuses on verifying the accuracy of the dominant emotion identification logic by creating and running specific test cases. It requires testing with sentences designed to elicit joy, anger, and fear, as well as an edge case with a blank input, to ensure the `max()` function works correctly and no exceptions are thrown.
EmotionSense API is a Python-based web application that detects emotions from text input using IBM Watson NLP. It includes a modular design, unit tests, error handling, static code analysis, and deployment using Flask. Ideal for learning DevOps and Software Engineering best practices.
AI Summary: This issue requires refactoring the emotion detection output. The goal is to parse the raw JSON string from IBM Watson, extract specific emotion scores (anger, disgust, fear, joy, sadness), calculate the dominant emotion, and return a clean Python dictionary. It also includes handling blank input by returning a dictionary with `None` values.
EmotionSense API is a Python-based web application that detects emotions from text input using IBM Watson NLP. It includes a modular design, unit tests, error handling, static code analysis, and deployment using Flask. Ideal for learning DevOps and Software Engineering best practices.
EmotionSense API is a Python-based web application that detects emotions from text input using IBM Watson NLP. It includes a modular design, unit tests, error handling, static code analysis, and deployment using Flask. Ideal for learning DevOps and Software Engineering best practices.
EmotionSense API is a Python-based web application that detects emotions from text input using IBM Watson NLP. It includes a modular design, unit tests, error handling, static code analysis, and deployment using Flask. Ideal for learning DevOps and Software Engineering best practices.