- Created manifest.json for the Crawl4AI Assistant extension.
- Added popup HTML, CSS, and JS files for the extension interface.
- Included icons and favicon for the extension.
- Implemented functionality for schema capture and code generation.
- Updated index.md to reflect the availability of the new extension.
- Enhanced LLM Context Builder layout and styles for consistency.
- Adjusted global styles for better branding and responsiveness.
- Generate OneShot js code geenrator
- Introduced a new C4A-Script tutorial example for login flow using Blockly.
- Updated index.html to include Blockly theme and event editor modal for script editing.
- Created a test HTML file for testing Blockly integration.
- Added comprehensive C4A-Script API reference documentation covering commands, syntax, and examples.
- Developed core documentation for C4A-Script, detailing its features, commands, and real-world examples.
- Updated mkdocs.yml to include new C4A-Script documentation in navigation.
This update introduces a new feature in the URL seeding process that allows for the automatic filtering of utility URLs, such as robots.txt and sitemap.xml, which are not useful for content crawling. The class has been enhanced with a new parameter, , which is enabled by default. This change aims to improve the efficiency of the crawling process by reducing the number of irrelevant URLs processed.
Significant modifications include:
- Added parameter to in .
- Implemented logic in to check and filter out nonsense URLs during the seeding process in .
- Updated documentation to reflect the new filtering feature and provide examples of its usage in .
This change enhances the overall functionality of the URL seeder, making it smarter and more efficient in identifying and excluding non-content URLs.
BREAKING CHANGE: The now requires the parameter to be explicitly set if the default behavior is to be altered.
Related issues: #123
This commit introduces significant updates to the LinkedIn data discovery documentation by adding two new Jupyter notebooks that provide detailed insights into data discovery processes. The previous workshop notebook has been removed to streamline the content and avoid redundancy. Additionally, the URL seeder documentation has been expanded with a new tutorial and several enhancements to existing scripts, improving usability and clarity.
The changes include:
- Added and for comprehensive LinkedIn data discovery.
- Removed to eliminate outdated content.
- Updated to reflect new data visualization requirements.
- Introduced and to facilitate easier access to URL seeding techniques.
- Enhanced existing Python scripts and markdown files in the URL seeder section for better documentation and examples.
These changes aim to improve the overall documentation quality and user experience for developers working with LinkedIn data and URL seeding techniques.
This commit introduces AsyncUrlSeeder, a high-performance URL discovery system that enables intelligent crawling at scale by pre-discovering and filtering URLs before crawling.
## Core Features
### AsyncUrlSeeder Component
- Discovers URLs from multiple sources:
- Sitemaps (including nested and gzipped)
- Common Crawl index
- Combined sources for maximum coverage
- Extracts page metadata without full crawling:
- Title, description, keywords
- Open Graph and Twitter Card tags
- JSON-LD structured data
- Language and charset information
- BM25 relevance scoring for intelligent filtering:
- Query-based URL discovery
- Configurable score thresholds
- Automatic ranking by relevance
- Performance optimizations:
- Async/concurrent processing with configurable workers
- Rate limiting (hits per second)
- Automatic caching with TTL
- Streaming results for large datasets
### SeedingConfig
- Comprehensive configuration for URL seeding:
- Source selection (sitemap, cc, or both)
- URL pattern filtering with wildcards
- Live URL validation options
- Metadata extraction controls
- BM25 scoring parameters
- Concurrency and rate limiting
### Integration with AsyncWebCrawler
- Seamless pipeline: discover → filter → crawl
- Direct compatibility with arun_many()
- Significant resource savings by pre-filtering URLs
## Documentation
- Comprehensive guide comparing URL seeding vs deep crawling
- Complete API reference with parameter tables
- Practical examples showing all features
- Performance benchmarks and best practices
- Integration patterns with AsyncWebCrawler
## Examples
- url_seeder_demo.py: Interactive Rich-based demo with:
- Basic discovery
- Cache management
- Live validation
- BM25 scoring
- Multi-domain discovery
- Complete pipeline integration
- url_seeder_quick_demo.py: Screenshot-friendly examples:
- Pattern-based filtering
- Metadata exploration
- Smart search with BM25
## Testing
- Comprehensive test suite (test_async_url_seeder_bm25.py)
- Coverage of all major features
- Edge cases and error handling
- Performance and consistency tests
## Implementation Details
- Built on httpx with HTTP/2 support
- Optional dependencies: lxml, brotli, rank_bm25
- Cache management in ~/.crawl4ai/seeder_cache/
- Logger integration with AsyncLoggerBase
- Proper error handling and retry logic
## Bug Fixes
- Fixed logger color compatibility (lightblack → bright_black)
- Corrected URL extraction from seeder results for arun_many()
- Updated all examples and documentation with proper usage
This feature enables users to crawl smarter, not harder, by discovering
and analyzing URLs before committing resources to crawling them.
Add support for controlling browser geolocation, locale and timezone settings:
- New GeolocationConfig class for managing GPS coordinates
- Add locale and timezone_id parameters to CrawlerRunConfig
- Update browser context creation to handle location settings
- Add example script for geolocation usage
- Update documentation with location-based identity features
This enables more precise control over browser identity and location reporting.
Adds a new content_source parameter to MarkdownGenerationStrategy that allows
selecting which HTML content to use for markdown generation:
- cleaned_html (default): uses post-processed HTML
- raw_html: uses original webpage HTML
- fit_html: uses preprocessed HTML for schema extraction
Changes include:
- Added content_source parameter to MarkdownGenerationStrategy
- Updated AsyncWebCrawler to handle HTML source selection
- Added examples and tests for the new feature
- Updated documentation with new parameter details
BREAKING CHANGE: Renamed cleaned_html parameter to input_html in generate_markdown()
method signature to better reflect its generalized purpose
Add new AI assistant chat interface with features:
- Real-time chat with markdown support
- Chat history management
- Citation tracking
- Selection-to-query functionality
Also adds code copy button to documentation code blocks and adjusts layout/styling.
Breaking changes: None
Add ability to capture web pages as MHTML format, which includes all page resources
in a single file. This enables complete page archival and offline viewing.
- Add capture_mhtml parameter to CrawlerRunConfig
- Implement MHTML capture using CDP in AsyncPlaywrightCrawlerStrategy
- Add mhtml field to CrawlResult and AsyncCrawlResponse models
- Add comprehensive tests for MHTML capture functionality
- Update documentation with MHTML capture details
- Add exclude_all_images option for better memory management
Breaking changes: None
Adds new target_elements parameter to CrawlerRunConfig that allows more flexible content selection than css_selector. This enables focusing markdown generation and data extraction on specific elements while still processing the entire page for links and media.
Key changes:
- Added target_elements list parameter to CrawlerRunConfig
- Modified WebScrapingStrategy and LXMLWebScrapingStrategy to handle target_elements
- Updated documentation with examples and comparison between css_selector and target_elements
- Fixed table extraction in content_scraping_strategy.py
BREAKING CHANGE: Table extraction logic has been modified to better handle thead/tbody structures
Add comprehensive table detection and extraction functionality to the web scraping system:
- Implement intelligent table detection algorithm with scoring system
- Add table extraction with support for headers, rows, captions
- Update models to include tables in Media class
- Add table_score_threshold configuration option
- Add documentation and examples for table extraction
- Include crypto analysis example demonstrating table usage
This change enables users to extract structured data from HTML tables while intelligently filtering out layout tables.
Add new features to enhance browser automation and HTML extraction:
- Add CDP browser launch capability with customizable ports and profiles
- Implement JsonLxmlExtractionStrategy for faster HTML parsing
- Add CLI command 'crwl cdp' for launching standalone CDP browsers
- Support connecting to external CDP browsers via URL
- Optimize selector caching and context-sensitive queries
BREAKING CHANGE: LLMConfig import path changed from crawl4ai.types to crawl4ai
Rename LlmConfig to LLMConfig across the codebase to follow consistent naming conventions.
Update all imports and usages to use the new name.
Update documentation and examples to reflect the change.
BREAKING CHANGE: LlmConfig has been renamed to LLMConfig. Users need to update their imports and usage.
Add max_pages parameter to all deep crawling strategies to limit total pages crawled.
Add score_threshold parameter to BFS/DFS strategies for quality control.
Remove legacy parameter handling in AsyncWebCrawler.
Improve error handling and logging in crawl strategies.
BREAKING CHANGE: Removed support for legacy parameters in AsyncWebCrawler.run_many()
* 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
* feature: Add LlmConfig to easily configure and pass LLM configs to different strategies
* pulled in next branch and resolved conflicts
* feat: Add gemini and deepseek providers. Make ignore_cache in llm content filter to true by default to avoid confusions
* Refactor: Update LlmConfig in LLMExtractionStrategy class and deprecate old params
* updated tests, docs and readme
Implements a full-featured CLI for Crawl4AI with the following capabilities:
- Basic and advanced web crawling
- Configuration management via YAML/JSON files
- Multiple extraction strategies (CSS, XPath, LLM)
- Content filtering and optimization
- Interactive Q&A capabilities
- Various output formats
- Comprehensive documentation and examples
Also includes:
- Home directory setup for configuration and cache
- Environment variable support for API tokens
- Test suite for CLI functionality
Implements a new proxy rotation system with the following changes:
- Add ProxyRotationStrategy abstract base class
- Add RoundRobinProxyStrategy concrete implementation
- Integrate proxy rotation with AsyncWebCrawler
- Add proxy_rotation_strategy parameter to CrawlerRunConfig
- Add example script demonstrating proxy rotation usage
- Remove deprecated synchronous WebCrawler code
- Clean up rate limiting documentation
BREAKING CHANGE: Removed synchronous WebCrawler support and related rate limiting configurations
Prepare the v0.4.3 beta release with major feature additions and improvements:
- Add JsonXPathExtractionStrategy and LLMContentFilter to exports
- Update version to 0.4.3b1
- Improve documentation for dispatchers and markdown generation
- Update development status to Beta
- Reorganize changelog format
BREAKING CHANGE: Memory threshold in MemoryAdaptiveDispatcher increased to 90% and SemaphoreDispatcher parameter renamed to max_session_permit
Adds new static method generate_schema() to JsonElementExtractionStrategy classes
that can automatically generate extraction schemas using LLM (OpenAI or Ollama).
This provides a convenient way to bootstrap extraction schemas while maintaining
the performance benefits of selector-based extraction.
Key changes:
- Added generate_schema() static method to base extraction strategy
- Added support for both CSS and XPath schema generation
- Updated documentation with examples and best practices
- Added new prompt templates for schema generation
Add comprehensive documentation for the new streaming mode feature in arun_many():
- Update arun_many() API docs to reflect streaming return type
- Add streaming examples in quickstart and multi-url guides
- Document stream parameter in configuration classes
- Add clone() helper method documentation for configs
This change improves documentation for processing large numbers of URLs efficiently.
Add new LLMContentFilter class that uses LLMs to generate high-quality markdown content:
- Implement intelligent content filtering with customizable instructions
- Add chunk processing for handling large documents
- Support parallel processing of content chunks
- Include caching mechanism for filtered results
- Add usage tracking and statistics
- Update documentation with examples and use cases
Also includes minor changes:
- Disable Pydantic warnings in __init__.py
- Add new prompt template for content filtering
Replace the ScrapingMode enum with a proper strategy pattern implementation for content scraping.
This change introduces:
- New ContentScrapingStrategy abstract base class
- Concrete WebScrapingStrategy and LXMLWebScrapingStrategy implementations
- New Pydantic models for structured scraping results
- Updated documentation reflecting the new strategy-based approach
BREAKING CHANGE: ScrapingMode enum has been removed. Users should now use ContentScrapingStrategy implementations instead.
Adds a new ScrapingMode enum to allow switching between BeautifulSoup and LXML parsing.
LXML mode offers 10-20x better performance for large HTML documents.
Key changes:
- Added ScrapingMode enum with BEAUTIFULSOUP and LXML options
- Implemented LXMLWebScrapingStrategy class
- Added LXML-based metadata extraction
- Updated documentation with scraping mode usage and performance considerations
- Added cssselect dependency
BREAKING CHANGE: None
Reorganize dispatcher functionality into separate components:
- Create dedicated dispatcher classes (MemoryAdaptive, Semaphore)
- Add RateLimiter for smart request throttling
- Implement CrawlerMonitor for real-time progress tracking
- Move dispatcher config from CrawlerRunConfig to separate classes
BREAKING CHANGE: Dispatcher configuration moved from CrawlerRunConfig to dedicated dispatcher classes. Users need to update their configuration approach for multi-URL crawling.
Update all documentation URLs from crawl4ai.com/mkdocs to docs.crawl4ai.com
Improve badges styling and layout in documentation
Increase code font size in documentation CSS
BREAKING CHANGE: Documentation URLs have changed from crawl4ai.com/mkdocs to docs.crawl4ai.com
Reorganize documentation into core/advanced/extraction sections for better navigation.
Update terminal theme styles and add rich library for better CLI output.
Remove redundant tutorial files and consolidate content into core sections.
Add personal story to index page for project context.
BREAKING CHANGE: Documentation structure has been significantly reorganized
