from smolagents.tools import Tool import string import pronouncing import json class ParodyWordSuggestionTool(Tool): name = "parody_word_suggester" description = """Suggests phonetically similar funny words using CMU dictionary pronunciations. Returns similar words from a curated list of funny words, along with their similarity scores.""" inputs = {'target': {'type': 'string', 'description': 'The word you want to find funny alternatives for'}, 'word_list': {'type': 'string', 'description': 'JSON string of words list, e.g. \'["word1", "word2"]\''}, 'min_similarity': {'type': 'string', 'description': 'Minimum similarity threshold (0.0-1.0)', 'nullable': True}} output_type = "string" def forward(self, target: str, word_list: str, min_similarity: str = "0.7") -> str: """Get phonetically similar funny word suggestions.""" import pronouncing import string import json target = target.lower().strip(string.punctuation) min_similarity = float(min_similarity) suggestions = [] # Parse word list from JSON string try: words = json.loads(word_list) if not isinstance(words, list): return json.dumps({ "error": "word_list must be a JSON string representing a list of words", "suggestions": [] }, indent=2) except json.JSONDecodeError: return json.dumps({ "error": "Invalid JSON string for word_list", "suggestions": [] }, indent=2) # Get target pronunciation target_phones = pronouncing.phones_for_word(target) if not target_phones: return json.dumps({ "error": f"'{target}' not found in CMU dictionary", "suggestions": [] }, indent=2) target_phones = target_phones[0].split() # Check each word for word in words: phones = pronouncing.phones_for_word(word) if phones: # Only process if word is in dictionary phones = phones[0].split() # Calculate similarity using overlap overlap = len(set(phones) & set(target_phones)) total = min(len(phones), len(target_phones)) similarity = overlap / total if total > 0 else 0.0 if similarity >= min_similarity: suggestions.append({ "word": word, "similarity": round(similarity, 3), "syllables": pronouncing.syllable_count(phones) }) # Sort by similarity score descending suggestions.sort(key=lambda x: x["similarity"], reverse=True) result = { "target": target, "target_syllables": pronouncing.syllable_count(target_phones), "suggestions": suggestions } return json.dumps(result, indent=2) def __init__(self, *args, **kwargs): self.is_initialized = False