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3 changed files with 117 additions and 6 deletions

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@@ -27,3 +27,13 @@ WORD_TOKEN_RATE = 1.3
# Threshold for the minimum number of word in a HTML tag to be considered
MIN_WORD_THRESHOLD = 1
# Threshold for the Image extraction - Range is 1 to 6
# Images are scored based on point based system, to filter based on usefulness. Points are assigned
# to each image based on the following aspects.
# If either height or width exceeds 150px
# If image size is greater than 10Kb
# If alt property is set
# If image format is in jpg, png or webp
# If image is in the first half of the total images extracted from the page
IMAGE_SCORE_THRESHOLD = 2

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@@ -3,7 +3,7 @@ from pathlib import Path
import subprocess, os
import shutil
import tarfile
from crawl4ai.config import MODEL_REPO_BRANCH
from .model_loader import *
import argparse
import urllib.request
__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))

View File

@@ -11,6 +11,9 @@ from .prompts import PROMPT_EXTRACT_BLOCKS
from .config import *
from pathlib import Path
from typing import Dict, Any
from urllib.parse import urljoin
import requests
from requests.exceptions import InvalidSchema
class InvalidCSSSelectorError(Exception):
pass
@@ -447,6 +450,101 @@ def get_content_of_website_optimized(url: str, html: str, word_count_threshold:
links = {'internal': [], 'external': []}
media = {'images': [], 'videos': [], 'audios': []}
def process_image(img, url, index, total_images):
#Check if an image has valid display and inside undesired html elements
def is_valid_image(img, parent, parent_classes):
style = img.get('style', '')
src = img.get('src', '')
classes_to_check = ['button', 'icon', 'logo']
tags_to_check = ['button', 'input']
return all([
'display:none' not in style,
src,
not any(s in var for var in [src, img.get('alt', ''), *parent_classes] for s in classes_to_check),
parent.name not in tags_to_check
])
#Score an image for it's usefulness
def score_image_for_usefulness(img, base_url, index, images_count):
# Function to parse image height/width value and units
def parse_dimension(dimension):
if dimension:
match = re.match(r"(\d+)(\D*)", dimension)
if match:
number = int(match.group(1))
unit = match.group(2) or 'px' # Default unit is 'px' if not specified
return number, unit
return None, None
# Fetch image file metadata to extract size and extension
def fetch_image_file_size(img, base_url):
#If src is relative path construct full URL, if not it may be CDN URL
img_url = urljoin(base_url,img.get('src'))
try:
response = requests.head(img_url)
if response.status_code == 200:
return response.headers.get('Content-Length',None)
else:
print(f"Failed to retrieve file size for {img_url}")
return None
except InvalidSchema as e:
return None
finally:
return
image_height = img.get('height')
height_value, height_unit = parse_dimension(image_height)
image_width = img.get('width')
width_value, width_unit = parse_dimension(image_width)
image_size = int(fetch_image_file_size(img,base_url) or 0)
image_format = os.path.splitext(img.get('src',''))[1].lower()
score = 0
if height_value:
if height_unit == 'px' and height_value > 150:
score += 1
if height_unit in ['%','vh','vmin','vmax'] and height_value >30:
score += 1
if width_value:
if width_unit == 'px' and width_value > 150:
score += 1
if width_unit in ['%','vh','vmin','vmax'] and width_value >30:
score += 1
if image_size > 10000:
score += 1
if img.get('alt') != '':
score+=1
if any(image_format==format for format in ['jpg','png','webp']):
score+=1
if index/images_count<0.5:
score+=1
return score
# Extract meaningful text for images from closest parent
def find_closest_parent_with_useful_text(tag):
current_tag = tag
while current_tag:
current_tag = current_tag.parent
# Get the text content of the parent tag
if current_tag:
text_content = current_tag.get_text(separator=' ',strip=True)
# Check if the text content has at least word_count_threshold
if len(text_content.split()) >= word_count_threshold:
return text_content
return None
if not is_valid_image(img, img.parent, img.parent.get('class', [])):
return None
score = score_image_for_usefulness(img, url, index, total_images)
if score <= IMAGE_SCORE_THRESHOLD:
return None
return {
'src': img.get('src', ''),
'alt': img.get('alt', ''),
'desc': find_closest_parent_with_useful_text(img),
'score': score,
'type': 'image'
}
def process_element(element: element.PageElement) -> bool:
try:
if isinstance(element, NavigableString):
@@ -471,11 +569,6 @@ def get_content_of_website_optimized(url: str, html: str, word_count_threshold:
keep_element = True
elif element.name == 'img':
media['images'].append({
'src': element.get('src'),
'alt': element.get('alt'),
'type': 'image'
})
return True # Always keep image elements
elif element.name in ['video', 'audio']:
@@ -518,6 +611,14 @@ def get_content_of_website_optimized(url: str, html: str, word_count_threshold:
print('Error processing element:', str(e))
return False
#process images by filtering and extracting contextual text from the page
imgs = body.find_all('img')
media['images'] = [
result for result in
(process_image(img, url, i, len(imgs)) for i, img in enumerate(imgs))
if result is not None
]
process_element(body)
def flatten_nested_elements(node):