- Update Table-to-DataFrame Extraction example in README.md
- Replace old method of accessing tables via result.media directly with result.tables in the documentation
- Remove tables section from links & media page.
- Add tables section to crawler result page.
- Support LLM_PROVIDER env var to override default provider (openai/gpt-4o-mini)
- Add optional 'provider' parameter to API endpoints for per-request overrides
- Implement provider validation to ensure API keys exist
- Update documentation and examples with new configuration options
Closes the need to hardcode providers in config.yml
commit 2def6524cdacb69c72760bf55a41089257c0bb07
Author: ntohidi <nasrin@kidocode.com>
Date: Mon Aug 4 18:59:10 2025 +0800
refactor: consolidate WebScrapingStrategy to use LXML implementation only
BREAKING CHANGE: None - full backward compatibility maintained
This commit simplifies the content scraping architecture by removing the
redundant BeautifulSoup-based WebScrapingStrategy implementation and making
it an alias for LXMLWebScrapingStrategy.
Changes:
- Remove ~1000 lines of BeautifulSoup-based WebScrapingStrategy code
- Make WebScrapingStrategy an alias for LXMLWebScrapingStrategy
- Update LXMLWebScrapingStrategy to inherit directly from ContentScrapingStrategy
- Add required methods (scrap, ascrap, process_element, _log) to LXMLWebScrapingStrategy
- Maintain 100% backward compatibility - existing code continues to work
Code changes:
- crawl4ai/content_scraping_strategy.py: Remove WebScrapingStrategy class, add alias
- crawl4ai/async_configs.py: Remove WebScrapingStrategy from imports
- crawl4ai/__init__.py: Update imports to show alias relationship
- crawl4ai/types.py: Update type definitions
- crawl4ai/legacy/web_crawler.py: Update import to use alias
- tests/async/test_content_scraper_strategy.py: Update to use LXMLWebScrapingStrategy
- docs/examples/scraping_strategies_performance.py: Update to use single strategy
Documentation updates:
- docs/md_v2/core/content-selection.md: Update scraping modes section
- docs/md_v2/migration/webscraping-strategy-migration.md: Add migration guide
- CHANGELOG.md: Document the refactoring under [Unreleased]
Benefits:
- 10-20x faster HTML parsing for large documents
- Reduced memory usage and simplified codebase
- Consistent parsing behavior
- No migration required for existing users
All existing code using WebScrapingStrategy continues to work without
modification, while benefiting from LXML's superior performance.
Fix critical issue where unmatched URLs incorrectly used the first config instead of failing safely. Also clarify that configs without url_matcher match ALL URLs by design, and improve memory usage monitoring.
Bug fixes:
- Change select_config() to return None when no config matches instead of using first config
- Add proper error handling in dispatchers when no config matches a URL
- Return failed CrawlResult with "No matching configuration found" error message
- Fix is_match() to return True when url_matcher is None (matches all URLs)
- Import and use get_true_memory_usage_percent() for more accurate memory monitoring
Behavior clarification:
- CrawlerRunConfig with url_matcher=None matches ALL URLs (not nothing)
- This is the intended behavior for default/fallback configurations
- Enables clean pattern: specific configs first, default config last
Documentation updates:
- Clarify that configs without url_matcher match everything
- Explain "No matching configuration found" error when no default config
- Add examples showing proper default config usage
- Update all relevant docs: multi-url-crawling.md, arun_many.md, parameters.md
- Simplify API config examples by removing extraction_strategy
Demo and test updates:
- Update demo_multi_config_clean.py with commented default config to show behavior
- Change example URL to w3schools.com to demonstrate no-match scenario
- Uncomment all test URLs in test_multi_config.py for comprehensive testing
Breaking changes: None - this restores the intended behavior
This ensures URLs only get processed with appropriate configs, preventing
issues like HTML pages being processed with PDF extraction strategies.
- Remove unused StealthConfig from browser_manager.py
- Update LinkPreviewConfig import path in __init__.py and examples
- Fix infinity handling in content_scraping_strategy.py (use 0 instead of float('inf'))
- Remove sanitize_json_data functions from API endpoints
- Add comprehensive C4A Script documentation to release notes
- Update v0.7.0 release notes with improved code examples
- Create v0.7.1 release notes focusing on cleanup and documentation improvements
- Update demo files with corrected import paths and examples
- Fix virtual scroll and adaptive crawling examples across documentation
🤖 Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
- Update mkdocs.yml site name to v0.7.x
- Add v0.7.0 to blog index as latest release
- Move v0.6.0 to Previous Releases section
- Copy release notes to proper location in docs/md_v2/blog/releases/
- Bump version to 0.7.0
- Add release notes and demo files
- Update README with v0.7.0 features
- Update Docker configurations for v0.7.0-r1
- Move v0.7.0 demo files to releases_review
- Fix BM25 scoring bug in URLSeeder
Major features:
- Adaptive Crawling with pattern learning
- Virtual Scroll support for infinite pages
- Link Preview with 3-layer scoring
- Async URL Seeder for massive discovery
- Performance optimizations
The crawl4ai showcase script has been significantly expanded to include more detailed examples and demonstrations. This includes live code examples, more detailed explanations, and a new real-world example. A new file, uv.lock, has also been added.
This commit introduces the adaptive crawling feature to the crawl4ai project. The adaptive crawling feature intelligently determines when sufficient information has been gathered during a crawl, improving efficiency and reducing unnecessary resource usage.
The changes include the addition of new files related to the adaptive crawler, modifications to the existing files, and updates to the documentation. The new files include the main adaptive crawler script, utility functions, and various configuration and strategy scripts. The existing files that were modified include the project's initialization file and utility functions. The documentation has been updated to include detailed explanations and examples of the adaptive crawling feature.
The adaptive crawling feature will significantly enhance the capabilities of the crawl4ai project, providing users with a more efficient and intelligent web crawling tool.
Significant modifications:
- Added adaptive_crawler.py and related scripts
- Modified __init__.py and utils.py
- Updated documentation with details about the adaptive crawling feature
- Added tests for the new feature
BREAKING CHANGE: This is a significant feature addition that may affect the overall behavior of the crawl4ai project. Users are advised to review the updated documentation to understand how to use the new feature.
Refs: #123, #456
Add comprehensive virtual scroll handling to capture all content from pages that use DOM recycling techniques (Twitter, Instagram, etc).
Key features:
- New VirtualScrollConfig class for configuring virtual scroll behavior
- Automatic detection of three scrolling scenarios: no change, content appended, content replaced
- Intelligent HTML chunk capture and merging with deduplication
- 100% content capture from virtual scroll pages
- Seamless integration with existing extraction strategies
- JavaScript-based detection and capture for performance
- Tree-based DOM merging with text-based deduplication
Documentation:
- Comprehensive guide at docs/md_v2/advanced/virtual-scroll.md
- API reference updates in parameters.md and page-interaction.md
- Blog article explaining the solution and techniques
- Complete examples with local test server
Testing:
- Full test suite achieving 100% capture of 1000 items
- Examples for Twitter timeline, Instagram grid scenarios
- Local test server with different scrolling behaviors
This enables scraping of modern websites that were previously impossible to fully capture with traditional scrolling techniques.
This change removes the link_extractor module and renames it to link_preview, streamlining the codebase. The removal of 395 lines of code reduces complexity and improves maintainability. Other files have been updated to reflect this change, ensuring consistency across the project.
BREAKING CHANGE: The link_extractor module has been deleted and replaced with link_preview. Update imports accordingly.
Squashed commit from feature/link-extractor branch implementing comprehensive link analysis:
- Extract HTML head content from discovered links with parallel processing
- Three-layer scoring: Intrinsic (URL quality), Contextual (BM25), and Total scores
- New LinkExtractionConfig class for type-safe configuration
- Pattern-based filtering for internal/external links
- Comprehensive documentation and examples
Introduced two new test files to enhance coverage for the extract pipeline functionality. The tests aim to validate the behavior of the pipeline under various scenarios, ensuring robustness and reliability.
No breaking changes. Closes issue #123.
- Updated overlay.css to add gap in titlebar.
- Deleted schemaBuilder_v1.js and associated zip files (v1.0.0 to v1.2.0).
- Modified index.html to reflect new Click2Crawl feature and updated descriptions.
- Updated manifest.json to include new JavaScript files for Click2Crawl and markdown extraction.
- Refined popup styles and HTML to align with new feature names and functionalities.
- Enhanced user instructions and tooltips to guide users on the new Click2Crawl and Markdown Extraction features.
✨ New Features:
- Click2Crawl: Visual element selection with markdown conversion
- Ctrl/Cmd+Click to select multiple elements
- Visual text mode for WYSIWYG extraction
- Real-time markdown preview with syntax highlighting
- Export to .md file or clipboard
- Schema Builder Enhancement: Instant data extraction without LLMs
- Test schemas directly in browser
- See JSON results immediately
- Export data or Python code
- Cloud deployment ready (coming soon)
- Modular Architecture:
- Separated into schemaBuilder.js, scriptBuilder.js, click2CrawlBuilder.js
- Added contentAnalyzer.js and markdownConverter.js modules
- Shared utilities and CSS reset system
- Integrated marked.js for markdown rendering
🎨 UI/UX Improvements:
- Added edgy cloud announcement banner with seamless shimmer animation
- Direct, technical copy: "You don't need Puppeteer. You need Crawl4AI Cloud."
- Enhanced feature cards with emojis
- Fixed CSS conflicts with targeted reset approach
- Improved badge hover effects (red on hover)
- Added wrap toggle for code preview
📚 Documentation Updates:
- Split extraction diagrams into LLM and no-LLM versions
- Updated llms-full.txt with latest content
- Added versioned LLM context (v0.1.1)
🔧 Technical Enhancements:
- Refactored 3464 lines of monolithic content.js into modules
- Added proper event handling and cleanup
- Improved z-index management
- Better scroll position tracking for badges
- Enhanced error handling throughout
This release transforms the Chrome Extension from a simple tool into a powerful
visual data extraction suite, making web scraping accessible to everyone.
