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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