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from smolagents.tools import Tool
import pronouncing
import json
import string
import difflib
class ParodyWordSuggestionTool(Tool):
name = "parody_word_suggester"
description = """Suggests rhyming funny words using CMU dictionary pronunciations.
Returns similar-sounding words that rhyme, especially focusing on common vowel sounds."""
inputs = {'target': {'type': 'string', 'description': 'The word you want to find rhyming alternatives for'}, 'word_list_str': {'type': 'string', 'description': 'JSON string of word list (e.g. \'["word1", "word2"]\')'}, 'min_similarity': {'type': 'string', 'description': 'Minimum similarity threshold (0.0-1.0)', 'nullable': True, 'default': '0.5'}}
output_type = "string"
VOWEL_REF = "AH,AX|UH|AE,EH|IY,IH|AO,AA|UW|AY,EY|OW,AO|AW,AO|OY,OW|ER,AXR"
CONSONANT_REF = "M,N,NG|P,B|T,D|K,G|F,V|TH,DH|S,Z|SH,ZH|L,R|W,Y"
def _get_vowel_groups(self):
groups = []
group_strs = self.VOWEL_REF.split("|")
for group_str in group_strs:
groups.append(group_str.split(","))
return groups
def _get_consonant_groups(self):
groups = []
group_strs = self.CONSONANT_REF.split("|")
for group_str in group_strs:
groups.append(group_str.split(","))
return groups
def _get_last_syllable(self, phones: list) -> tuple:
"""Extract the last syllable (vowel + remaining consonants)."""
last_vowel_idx = -1
last_vowel = None
vowel_groups = self._get_vowel_groups()
for i, phone in enumerate(phones):
base_phone = phone.rstrip('012')
for group in vowel_groups:
if base_phone in group:
last_vowel_idx = i
last_vowel = base_phone
break
if last_vowel_idx == -1:
return None, []
remaining = phones[last_vowel_idx + 1:]
return last_vowel, remaining
def _strip_stress(self, phones: list) -> list:
result = []
for phone in phones:
result.append(phone.rstrip('012'))
return result
def _vowels_match(self, v1: str, v2: str) -> bool:
v1 = v1.rstrip('012')
v2 = v2.rstrip('012')
if v1 == v2:
return True
vowel_groups = self._get_vowel_groups()
for group in vowel_groups:
if v1 in group and v2 in group:
return True
return False
def _calculate_similarity(self, word1, phones1, word2, phones2):
"""Calculate similarity with heavy emphasis on rhyming."""
from difflib import SequenceMatcher
import pronouncing
# Initialize all variables
rhyme_score = 0.0
string_score = 0.0
pattern_score = 0.0
phone_list1 = []
phone_list2 = []
vowel1 = None
vowel2 = None
end1 = []
end2 = []
end1_clean = []
end2_clean = []
matching_consonants = 0
phone_list1 = phones1.split()
phone_list2 = phones2.split()
# Get last syllables
vowel1, end1 = self._get_last_syllable(phone_list1)
vowel2, end2 = self._get_last_syllable(phone_list2)
# Calculate rhyme score (60%)
if vowel1 and vowel2:
# Perfect vowel match
if vowel1.rstrip('012') == vowel2.rstrip('012'):
rhyme_score = 1.0
# Similar vowel match
elif self._vowels_match(vowel1, vowel2):
rhyme_score = 0.8
# Check endings
if end1 and end2:
end1_clean = self._strip_stress(end1)
end2_clean = self._strip_stress(end2)
# Perfect ending match
if end1_clean == end2_clean:
rhyme_score = min(1.0, rhyme_score + 0.2)
# Partial ending match
else:
consonant_groups = self._get_consonant_groups()
matching_consonants = 0
for c1, c2 in zip(end1_clean, end2_clean):
if c1 == c2:
matching_consonants += 1
else:
# Check if consonants are in same group
for group in consonant_groups:
if c1 in group and c2 in group:
matching_consonants += 0.5
break
if matching_consonants > 0:
rhyme_score = min(1.0, rhyme_score + (0.1 * matching_consonants))
# String similarity (25%)
if len(word1) > 1 and len(word2) > 1:
end_similarity = SequenceMatcher(None, word1[1:], word2[1:]).ratio()
string_score = end_similarity
else:
string_score = SequenceMatcher(None, word1, word2).ratio()
# Pattern/Length score (15%)
if len(phone_list1) == len(phone_list2):
pattern_score = 1.0
else:
pattern_score = 1.0 - (abs(len(phone_list1) - len(phone_list2)) / max(len(phone_list1), len(phone_list2)))
# Final weighted score
similarity = (
(rhyme_score * 0.60) +
(string_score * 0.25) +
(pattern_score * 0.15)
)
# Extra boost for exact matches minus first letter
if len(word1) == len(word2) and word1[1:] == word2[1:]:
similarity = min(1.0, similarity * 1.2)
# Extra penalty for very different lengths
if abs(len(word1) - len(word2)) > 2:
similarity *= 0.7
return {
"similarity": round(similarity, 3),
"rhyme_score": round(rhyme_score, 3),
"string_score": round(string_score, 3),
"pattern_score": round(pattern_score, 3),
"details": {
"last_vowel_match": vowel1.rstrip('012') == vowel2.rstrip('012') if vowel1 and vowel2 else False,
"similar_vowels": self._vowels_match(vowel1, vowel2) if vowel1 and vowel2 else False,
"ending_match": " ".join(end1_clean) == " ".join(end2_clean) if end1 and end2 else False,
"string_length_diff": abs(len(word1) - len(word2))
}
}
def forward(self, target: str, word_list_str: str, min_similarity: str = "0.5") -> str:
import pronouncing
import string
import json
# Initialize all variables
target = target.lower().strip(string.punctuation)
min_similarity = float(min_similarity)
suggestions = []
word_vowel = None
word_end = []
target_vowel = None
target_end = []
valid_words = []
invalid_words = []
target_phone_list = []
words = []
target_phones = ""
word_phones = ""
word = ""
word_phone_list = []
similarity_result = {}
# Parse JSON string to list
try:
words = json.loads(word_list_str)
except json.JSONDecodeError:
return json.dumps({
"error": "Invalid JSON string for word_list_str",
"suggestions": []
}, indent=2)
# Get target pronunciation
target_phones = pronouncing.phones_for_word(target)
if not target_phones:
return json.dumps({
"error": f"Target word '{target}' not found in CMU dictionary",
"suggestions": []
}, indent=2)
# Filter word list to only words in CMU dictionary
valid_words = []
invalid_words = []
for word in words:
word = word.lower().strip(string.punctuation)
if pronouncing.phones_for_word(word):
valid_words.append(word)
else:
invalid_words.append(word)
if not valid_words:
return json.dumps({
"error": "No valid words found in CMU dictionary",
"invalid_words": invalid_words,
"suggestions": []
}, indent=2)
target_phones = target_phones[0]
target_phone_list = target_phones.split()
target_vowel, target_end = self._get_last_syllable(target_phone_list)
# Check each word
for word in valid_words:
phones = pronouncing.phones_for_word(word)
if phones:
word_phones = phones[0]
similarity_result = self._calculate_similarity(word, word_phones, target, target_phones)
if similarity_result["similarity"] >= min_similarity:
word_phone_list = word_phones.split()
word_vowel, word_end = self._get_last_syllable(word_phone_list)
suggestions.append({
"word": word,
"similarity": similarity_result["similarity"],
"rhyme_score": similarity_result["rhyme_score"],
"string_score": similarity_result["string_score"],
"pattern_score": similarity_result["pattern_score"],
"phones": word_phones,
"last_vowel": word_vowel,
"ending": " ".join(word_end) if word_end else "",
"details": similarity_result["details"]
})
# Sort by similarity score descending
suggestions.sort(key=lambda x: x["similarity"], reverse=True)
result = {
"target": target,
"target_phones": target_phones,
"target_last_vowel": target_vowel,
"target_ending": " ".join(target_end) if target_end else "",
"invalid_words": invalid_words,
"suggestions": suggestions
}
return json.dumps(result, indent=2)
def __init__(self, *args, **kwargs):
self.is_initialized = False
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