- New Hook: Added
before_retrieve_html
hook inAsyncPlaywrightCrawlerStrategy
. - Delayed HTML Retrieval: Introduced
delay_before_return_html
parameter to allow waiting before retrieving HTML content.- Useful for pages with delayed content loading.
- Flexible Timeout:
smart_wait
function now usespage_timeout
(default 60 seconds) instead of a fixed 30-second timeout.- Provides better handling for slow-loading pages.
- How to use: Set
page_timeout=your_desired_timeout
(in milliseconds) when callingcrawler.arun()
.
- Added support for different browser types (Chromium, Firefox, WebKit).
- Users can now specify the browser type when initializing AsyncWebCrawler.
- How to use: Set
browser_type="firefox"
orbrowser_type="webkit"
when initializing AsyncWebCrawler.
- Added ability to capture screenshots during crawling.
- Useful for debugging and content verification.
- How to use: Set
screenshot=True
when callingcrawler.arun()
.
- Added support for multiple LLM providers (OpenAI, Hugging Face, Ollama).
- Custom Arguments: Added support for passing extra arguments to LLM providers via
extra_args
parameter. - Custom Headers: Users can now pass custom headers to the extraction strategy.
- How to use: Specify the desired provider and custom arguments when using
LLMExtractionStrategy
.
- New feature to process and extract content from iframes.
- How to use: Set
process_iframes=True
in the crawl method.
- Introduced
get_delayed_content
method inAsyncCrawlResponse
. - Allows retrieval of content after a specified delay, useful for dynamically loaded content.
- How to use: Access
result.get_delayed_content(delay_in_seconds)
after crawling.
- Flexible Initialization: Now accepts arbitrary keyword arguments, passed directly to the crawler strategy.
- Allows for more customized setups.
- Enhanced image handling in WebScrappingStrategy.
- Added filtering for small, invisible, or irrelevant images.
- Improved image scoring system for better content relevance.
- Implemented JavaScript-based image dimension updating for more accurate representation.
- Automatic database schema updates ensure compatibility with the latest version.
- Improved error messages and logging for easier debugging.
- Refined HTML sanitization process.
- Improved handling of base64 encoded images.
- Enhanced Markdown conversion process.
- Optimized content extraction algorithms.
perform_completion_with_backoff
function now supports additional arguments for more customized API calls to LLM providers.
- Fixed an issue where image tags were being prematurely removed during content extraction.
- Updated
quickstart_async.py
with examples of:- Using custom headers in LLM extraction.
- Different LLM provider usage (OpenAI, Hugging Face, Ollama).
- Custom browser type usage.
- Refactored code for better maintainability, flexibility, and performance.
- Enhanced type hinting throughout the codebase for improved development experience.
- Expanded error handling for more robust operation.
These updates significantly enhance the flexibility, accuracy, and robustness of crawl4ai, providing users with more control and options for their web crawling and content extraction tasks.
Enhance AsyncWebCrawler with smart waiting and screenshot capabilities
- Implement smart_wait function in AsyncPlaywrightCrawlerStrategy
- Add screenshot support to AsyncCrawlResponse and AsyncWebCrawler
- Improve error handling and timeout management in crawling process
- Fix typo in CrawlResult model (responser_headers -> response_headers)
Significant improvements in text processing and performance:
- ๐ Dependency reduction: Removed dependency on spaCy model for text chunk labeling in cosine extraction strategy.
- ๐ค Transformer upgrade: Implemented text sequence classification using a transformer model for labeling text chunks.
- โก Performance enhancement: Improved model loading speed due to removal of spaCy dependency.
- ๐ง Future-proofing: Laid groundwork for potential complete removal of spaCy dependency in future versions.
These changes address issue #68 and provide a foundation for faster, more efficient text processing in Crawl4AI.
Major improvements in functionality, performance, and cross-platform compatibility! ๐
- ๐ณ Docker enhancements: Significantly improved Dockerfile for easy installation on Linux, Mac, and Windows.
- ๐ Official Docker Hub image: Launched our first official image on Docker Hub for streamlined deployment.
- ๐ง Selenium upgrade: Removed dependency on ChromeDriver, now using Selenium's built-in capabilities for better compatibility.
- ๐ผ๏ธ Image description: Implemented ability to generate textual descriptions for extracted images from web pages.
- โก Performance boost: Various improvements to enhance overall speed and performance.
A big shoutout to our amazing community contributors:
- @aravindkarnam for developing the textual description extraction feature.
- @FractalMind for creating the first official Docker Hub image and fixing Dockerfile errors.
- @ketonkss4 for identifying Selenium's new capabilities, helping us reduce dependencies.
Your contributions are driving Crawl4AI forward! ๐
Minor improvements for a more maintainable codebase:
- ๐ Fixed typos in
chunking_strategy.py
andcrawler_strategy.py
to improve code readability - ๐ Removed
.test_pads/
directory from.gitignore
to keep our repository clean and organized
These changes may seem small, but they contribute to a more stable and sustainable codebase. By fixing typos and updating our .gitignore
settings, we're ensuring that our code is easier to maintain and scale in the long run.
A slew of exciting updates to improve the crawler's stability and robustness! ๐
- ๐ป UTF encoding fix: Resolved the Windows "charmap" error by adding UTF encoding.
- ๐ก๏ธ Error handling: Implemented MaxRetryError exception handling in LocalSeleniumCrawlerStrategy.
- ๐งน Input sanitization: Improved input sanitization and handled encoding issues in LLMExtractionStrategy.
- ๐ฎ Database cleanup: Removed existing database file and initialized a new one.
๐ก In this release, we've bumped the version to v0.2.73 and refreshed our documentation to ensure you have the best experience with our project.
- Supporting website need "with-head" mode to crawl the website with head.
- Fixing the installation issues for setup.py and dockerfile.
- Resolve multiple issues.
This release brings exciting updates and improvements to our project! ๐
- ๐ Documentation Updates: Our documentation has been revamped to reflect the latest changes and additions.
- ๐ New Modes in setup.py: We've added support for three new modes in setup.py: default, torch, and transformers. This enhances the project's flexibility and usability.
- ๐ณ Docker File Updates: The Docker file has been updated to ensure seamless compatibility with the new modes and improvements.
- ๐ท๏ธ Temporary Solution for Headless Crawling: We've implemented a temporary solution to overcome issues with crawling websites in headless mode.
These changes aim to improve the overall user experience, provide more flexibility, and enhance the project's performance. We're thrilled to share these updates with you and look forward to continuing to evolve and improve our project!
Improved Error Handling and Performance ๐ง
- ๐ซ Refactored
crawler_strategy.py
to handle exceptions and provide better error messages, making it more robust and reliable. - ๐ป Optimized the
get_content_of_website_optimized
function inutils.py
for improved performance, reducing potential bottlenecks. - ๐ป Updated
utils.py
with the latest changes, ensuring consistency and accuracy. - ๐ซ Migrated to
ChromeDriverManager
to resolve Chrome driver download issues, providing a smoother user experience.
These changes focus on refining the existing codebase, resulting in a more stable, efficient, and user-friendly experience. With these improvements, you can expect fewer errors and better performance in the crawler strategy and utility functions.
- Speed up twice the extraction function.
- Fix issue #19: Update Dockerfile to ensure compatibility across multiple platforms.
- Added five important hooks to the crawler:
- on_driver_created: Called when the driver is ready for initializations.
- before_get_url: Called right before Selenium fetches the URL.
- after_get_url: Called after Selenium fetches the URL.
- before_return_html: Called when the data is parsed and ready.
- on_user_agent_updated: Called when the user changes the user_agent, causing the driver to reinitialize.
- Added an example in
quickstart.py
in the example folder under the docs. - Enhancement issue #24: Replaced inline HTML tags (e.g., DEL, INS, SUB, ABBR) with textual format for better context handling in LLM.
- Maintaining the semantic context of inline tags (e.g., abbreviation, DEL, INS) for improved LLM-friendliness.
- Updated Dockerfile to ensure compatibility across multiple platforms (Hopefully!).
- Fix issue #22: Use MD5 hash for caching HTML files to handle long URLs