Add support for checking and respecting robots.txt rules before crawling websites:
- Implement RobotsParser class with SQLite caching
- Add check_robots_txt parameter to CrawlerRunConfig
- Integrate robots.txt checking in AsyncWebCrawler
- Update documentation with robots.txt compliance examples
- Add tests for robot parser functionality
The cache uses WAL mode for better concurrency and has a default TTL of 7 days.
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 streaming capability to crawler configurations and introduce clone() methods
for both BrowserConfig and CrawlerRunConfig to support immutable config updates.
Move stream parameter from arun_many() method to CrawlerRunConfig.
BREAKING CHANGE: Removed stream parameter from AsyncWebCrawler.arun_many() method.
Use config.stream=True instead.
Add shared_data parameter to CrawlerRunConfig to allow data sharing between hooks.
Implement browser context reuse based on config signatures to improve memory usage.
Fix Firefox/Webkit channel settings.
Add config parameter to hook callbacks for better context access.
Remove debug print statements.
BREAKING CHANGE: Hook callback signatures now include config parameter
Add new streaming capability to the MemoryAdaptiveDispatcher and AsyncWebCrawler
to allow processing URLs with real-time result streaming. This enables
processing results as they become available rather than waiting for all
URLs to complete.
Key changes:
- Add run_urls_stream method to MemoryAdaptiveDispatcher
- Update AsyncWebCrawler.arun_many to support streaming mode
- Add result queue for better result handling
- Improve type hints and documentation
BREAKING CHANGE: The return type of arun_many now depends on the 'stream'
parameter, returning either List[CrawlResult] or AsyncGenerator[CrawlResult, None]
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
Make fields in MediaItem and Link models optional with default values to prevent validation errors when data is incomplete. Also expose BaseDispatcher in __init__ and fix markdown field handling in database manager.
BREAKING CHANGE: MediaItem and Link model fields are now optional with default values which may affect existing code expecting required fields.
