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101 lines
4.3 KiB
Python
101 lines
4.3 KiB
Python
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from typing import List
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from gpt_index.readers.base import BaseReader
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from gpt_index.readers.schema.base import Document
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class KnowledgeBaseWebReader(BaseReader):
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"""Knowledge base reader.
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Crawls and reads articles from a knowledge base/help center with Playwright.
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Tested on Zendesk and Intercom CMS, may work on others.
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Can be run in headless mode but it may be blocked by Cloudflare. Run it headed to be safe.
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Times out occasionally, just increase the default time out if it does.
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Requires the `playwright` package.
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Args:
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root_url (string): the base url of the knowledge base, with no trailing slash
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e.g. 'https://support.intercom.com'
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link_selectors (list): list of css selectors to find links to articles while crawling
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e.g. ['.article-list a', '.article-list a']
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article_path (string): the url path of articles on this domain so the crawler knows when to stop
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e.g. '/articles'
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title_selector (string): css selector to find the title of the article
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e.g. '.article-title'
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subtitle_selector (string): css selector to find the subtitle/description of the article
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e.g. '.article-subtitle'
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body_selector (string): css selector to find the body of the article
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e.g. '.article-body'
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"""
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def __init__(self, root_url, link_selectors, article_path, title_selector, subtitle_selector, body_selector) -> None:
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"""Initialize with parameters."""
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self.root_url = root_url
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self.link_selectors = link_selectors
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self.article_path = article_path
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self.title_selector = title_selector
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self.subtitle_selector = subtitle_selector
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self.body_selector = body_selector
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def load_data(self) -> List[Document]:
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from playwright.sync_api import sync_playwright
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with sync_playwright() as p:
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browser = p.chromium.launch(headless=False)
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# Crawl
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article_urls = self.get_article_urls(browser, self.root_url, self.root_url, self.link_selectors, self.article_path)
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# Scrape
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documents = []
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for url in article_urls:
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article = self.scrape_article(browser, url, self.title_selector, self.subtitle_selector, self.body_selector)
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extra_info = {'title': article['title'], 'subtitle': article['subtitle'], 'url': article['url']}
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documents.append(Document(article['body'], extra_info=extra_info))
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browser.close()
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return documents
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def scrape_article(self, browser, url, title_selector, subtitle_selector, body_selector):
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page = browser.new_page(ignore_https_errors=True)
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page.set_default_timeout(60000)
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page.goto(url, wait_until='domcontentloaded')
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title = (page.query_selector(title_selector).evaluate("node => node.innerText")) if title_selector else ''
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subtitle = (page.query_selector(subtitle_selector).evaluate("node => node.innerText")) if subtitle_selector else ''
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body = (page.query_selector(body_selector).evaluate("node => node.innerText")) if body_selector else ''
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page.close()
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print('scraped:', url)
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return {
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'title': title,
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'subtitle': subtitle,
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'body': body,
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'url': url
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}
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def get_article_urls(self, browser, root_url, current_url, link_selectors, article_path):
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page = browser.new_page(ignore_https_errors=True)
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page.set_default_timeout(60000)
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page.goto(current_url, wait_until="domcontentloaded")
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# If this is a leaf node aka article page, return itself
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if article_path in current_url:
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print('Found an article: ', current_url)
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page.close()
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return [current_url]
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# Otherwise crawl this page and find all the articles linked from it
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article_urls = []
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links = []
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for link_selector in link_selectors:
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ahrefs = page.query_selector_all(link_selector)
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links.extend(ahrefs)
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for link in links:
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url = root_url + page.evaluate("(node) => node.getAttribute('href')", link)
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article_urls.extend(self.get_article_urls(browser, root_url, url, link_selectors, article_path))
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page.close()
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return article_urls
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