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"""
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
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