patruff's picture
Upload tool
f9e805b verified
raw
history blame
4.86 kB
from smolagents.tools import Tool
import pronouncing
import json
import difflib
import string
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}}
output_type = "string"
def forward(self, target: str, word_list_str: str, min_similarity: str = "0.5") -> str:
"""Get rhyming word suggestions."""
import pronouncing
import string
import json
from difflib import SequenceMatcher
target = target.lower().strip(string.punctuation)
min_similarity = float(min_similarity)
suggestions = []
# 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}' not found in CMU dictionary",
"suggestions": []
}, indent=2)
target_phones = target_phones[0]
target_phone_list = target_phones.split()
# Check each word
for word in words:
word = word.lower().strip(string.punctuation)
phones = pronouncing.phones_for_word(word)
if phones:
word_phones = phones[0]
word_phone_list = word_phones.split()
# 1. Rhyme score (most important - 60%)
rhyme_score = 0
if len(word_phone_list) > 1 and len(target_phone_list) > 1:
# Check if words share the same ending (vowel + final consonants)
vowel_plus_end = -2 # Index of the vowel in final syllable
while vowel_plus_end < -1:
if 'A' in word_phone_list[vowel_plus_end] or 'E' in word_phone_list[vowel_plus_end] or 'I' in word_phone_list[vowel_plus_end] or 'O' in word_phone_list[vowel_plus_end] or 'U' in word_phone_list[vowel_plus_end]:
break
vowel_plus_end += 1
if vowel_plus_end == -1:
vowel_plus_end = -2 # Fall back if no vowel found
# Check if the ending (from vowel onwards) matches
if word_phone_list[vowel_plus_end:] == target_phone_list[vowel_plus_end:]:
rhyme_score = 1.0
# 2. Syllable match (25%)
target_syl = pronouncing.syllable_count(target_phones)
word_syl = pronouncing.syllable_count(word_phones)
syllable_score = 1.0 if target_syl == word_syl else 0.0
# 3. Overall similarity (15%) - using string similarity
string_similarity = SequenceMatcher(None, target, word).ratio()
# Combined score (60% rhyme, 25% syllables, 15% similarity)
similarity = (rhyme_score * 0.6) + (syllable_score * 0.25) + (string_similarity * 0.15)
if similarity >= min_similarity:
suggestions.append({
"word": word,
"similarity": round(similarity, 3),
"rhyme_match": rhyme_score == 1.0,
"syllable_match": syllable_score == 1.0,
"string_similarity": round(string_similarity, 3),
"syllables": word_syl,
"phones": word_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),
"target_phones": target_phones,
"suggestions": suggestions
}
return json.dumps(result, indent=2)
def __init__(self, *args, **kwargs):
self.is_initialized = False