| """ | |
| Sentiment mapping utilities for different model outputs. | |
| """ | |
| from typing import Dict | |
| from ..config.settings import SENTIMENT_MAPPINGS | |
| def get_sentiment_mapping(num_classes: int) -> Dict[int, str]: | |
| """ | |
| Get the sentiment mapping based on number of classes. | |
| Args: | |
| num_classes: Number of output classes from the model | |
| Returns: | |
| Dictionary mapping class indices to sentiment labels | |
| """ | |
| return SENTIMENT_MAPPINGS.get( | |
| num_classes, {i: f"Class_{i}" for i in range(num_classes)} | |
| ) | |
| def get_sentiment_colors() -> Dict[str, str]: | |
| """ | |
| Get color-coded sentiment display mapping. | |
| Returns: | |
| Dictionary mapping sentiment labels to emoji indicators | |
| """ | |
| return { | |
| "Positive": "🟢", | |
| "Negative": "🔴", | |
| "Neutral": "🟡", | |
| "Angry": "🔴", | |
| "Sad": "🔵", | |
| "Happy": "🟢", | |
| "Fear": "🟣", | |
| "Disgust": "🟠", | |
| "Surprise": "🟡", | |
| } | |
| def format_sentiment_result( | |
| sentiment: str, confidence: float, input_info: str = "", model_name: str = "" | |
| ) -> str: | |
| """ | |
| Format sentiment analysis result for display. | |
| Args: | |
| sentiment: Predicted sentiment label | |
| confidence: Confidence score | |
| input_info: Information about the input | |
| model_name: Name of the model used | |
| Returns: | |
| Formatted result string | |
| """ | |
| colors = get_sentiment_colors() | |
| emoji = colors.get(sentiment, "❓") | |
| result = f"{emoji} Sentiment: {sentiment}\n" | |
| result += f"Confidence: {confidence:.2f}\n" | |
| if input_info: | |
| result += f"Input: {input_info}\n" | |
| if model_name: | |
| result += f"Model: {model_name}\n" | |
| return result | |