Release prep (#749)
* fix: Update export of URLPatternFilter * chore: Add dependancy for cchardet in requirements * docs: Update example for deep crawl in release note for v0.5 * Docs: update the example for memory dispatcher * docs: updated example for crawl strategies * Refactor: Removed wrapping in if __name__==main block since this is a markdown file. * chore: removed cchardet from dependancy list, since unclecode is planning to remove it * docs: updated the example for proxy rotation to a working example * feat: Introduced ProxyConfig param * Add tutorial for deep crawl & update contributor list for bug fixes in feb alpha-1 * chore: update and test new dependancies * feat:Make PyPDF2 a conditional dependancy * updated tutorial and release note for v0.5 * docs: update docs for deep crawl, and fix a typo in docker-deployment markdown filename * refactor: 1. Deprecate markdown_v2 2. Make markdown backward compatible to behave as a string when needed. 3. Fix LlmConfig usage in cli 4. Deprecate markdown_v2 in cli 5. Update AsyncWebCrawler for changes in CrawlResult * fix: Bug in serialisation of markdown in acache_url * Refactor: Added deprecation errors for fit_html and fit_markdown directly on markdown. Now access them via markdown * fix: remove deprecated markdown_v2 from docker * Refactor: remove deprecated fit_markdown and fit_html from result * refactor: fix cache retrieval for markdown as a string * chore: update all docs, examples and tests with deprecation announcements for markdown_v2, fit_html, fit_markdown
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@@ -26,7 +26,7 @@ async def little_hello_web():
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result : CrawlResult = await crawler.arun(
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url="https://www.helloworld.org"
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)
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print(result.markdown_v2.raw_markdown[:500])
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print(result.markdown.raw_markdown[:500])
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async def hello_web():
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browser_config = BrowserConfig(headless=True, verbose=True)
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@@ -42,7 +42,7 @@ async def hello_web():
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result : CrawlResult = await crawler.arun(
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url="https://www.helloworld.org", config=crawler_config
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)
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print(result.markdown_v2.fit_markdown[:500])
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print(result.markdown.fit_markdown[:500])
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# Naive Approach Using Large Language Models
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async def extract_using_llm():
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