mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-22 05:32:12 -03:00
607ab35cce
- Introduced a new fuzzy_match utility function for improved search accuracy across Lora and Recipe scanners. - Updated search logic in LoraScanner and RecipeScanner to leverage fuzzy matching for titles, tags, and filenames, enhancing user experience. - Removed deprecated search methods to streamline the codebase and improve maintainability. - Adjusted API routes to ensure compatibility with the new search options, including recursive search handling.
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
from difflib import SequenceMatcher
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import requests
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import tempfile
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import re
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from bs4 import BeautifulSoup
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def download_twitter_image(url):
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"""Download image from a URL containing twitter:image meta tag
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Args:
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url (str): The URL to download image from
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Returns:
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str: Path to downloaded temporary image file
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"""
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try:
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# Download page content
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response = requests.get(url)
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response.raise_for_status()
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# Parse HTML
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soup = BeautifulSoup(response.text, 'html.parser')
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# Find twitter:image meta tag
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meta_tag = soup.find('meta', attrs={'property': 'twitter:image'})
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if not meta_tag:
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return None
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image_url = meta_tag['content']
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# Download image
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image_response = requests.get(image_url)
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image_response.raise_for_status()
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# Save to temp file
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with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as temp_file:
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temp_file.write(image_response.content)
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return temp_file.name
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except Exception as e:
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print(f"Error downloading twitter image: {e}")
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return None
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def fuzzy_match(text: str, pattern: str, threshold: float = 0.7) -> bool:
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"""
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Check if text matches pattern using fuzzy matching.
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Returns True if similarity ratio is above threshold.
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"""
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if not pattern or not text:
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return False
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# Convert both to lowercase for case-insensitive matching
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text = text.lower()
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pattern = pattern.lower()
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# Split pattern into words
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search_words = pattern.split()
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# Check each word
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for word in search_words:
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# First check if word is a substring (faster)
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if word in text:
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continue
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# If not found as substring, try fuzzy matching
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# Check if any part of the text matches this word
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found_match = False
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for text_part in text.split():
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ratio = SequenceMatcher(None, text_part, word).ratio()
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if ratio >= threshold:
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found_match = True
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break
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if not found_match:
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return False
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# All words found either as substrings or fuzzy matches
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return True
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