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| from transformers import pipeline | |
| # Define the PoliteGuard tool | |
| # Classify text into politeness categories | |
| class PoliteGuardTool(Tool): | |
| name = "polite_guard" | |
| description = "Calls an tool to classifify text by 4 labels from polite to impolite" | |
| inputs = {'input_text': {'type': 'any', 'description': 'Enter text for assessing whether it is respectful'}} | |
| output_type = "any" | |
| def forward(self, input_text: Any) -> Any: | |
| self.label, self.sccore = self.ask_polite_guard(input_text) | |
| def __init__(self, *args, **kwargs): | |
| self.is_initialized = False | |
| self.label = None | |
| self.score = None | |
| #@tool | |
| def ask_polite_guard(self, input_text: str) -> dict: | |
| """ | |
| Args: | |
| input_text: The text to classify. | |
| """ | |
| try: | |
| classifier = pipeline("text-classification", "Intel/polite-guard") | |
| return { | |
| "label": result['label'], | |
| "score": result['score'] | |
| } | |
| except Exception as e: | |
| return f"Error fetching classification for text '{input_text}': {str(e)}" |