a99cd37c0edba5b804de0d72eb08bee56684db0e
12 Commits
| Author | SHA1 | Message | Date | |
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Nasrin
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7cac008c10 |
Release/v0.7.6 (#1556)
* fix(docker-api): migrate to modern datetime library API
Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>
* Fix examples in README.md
* feat(docker): add user-provided hooks support to Docker API
Implements comprehensive hooks functionality allowing users to provide custom Python
functions as strings that execute at specific points in the crawling pipeline.
Key Features:
- Support for all 8 crawl4ai hook points:
• on_browser_created: Initialize browser settings
• on_page_context_created: Configure page context
• before_goto: Pre-navigation setup
• after_goto: Post-navigation processing
• on_user_agent_updated: User agent modification handling
• on_execution_started: Crawl execution initialization
• before_retrieve_html: Pre-extraction processing
• before_return_html: Final HTML processing
Implementation Details:
- Created UserHookManager for validation, compilation, and safe execution
- Added IsolatedHookWrapper for error isolation and timeout protection
- AST-based validation ensures code structure correctness
- Sandboxed execution with restricted builtins for security
- Configurable timeout (1-120 seconds) prevents infinite loops
- Comprehensive error handling ensures hooks don't crash main process
- Execution tracking with detailed statistics and logging
API Changes:
- Added HookConfig schema with code and timeout fields
- Extended CrawlRequest with optional hooks parameter
- Added /hooks/info endpoint for hook discovery
- Updated /crawl and /crawl/stream endpoints to support hooks
Safety Features:
- Malformed hooks return clear validation errors
- Hook errors are isolated and reported without stopping crawl
- Execution statistics track success/failure/timeout rates
- All hook results are JSON-serializable
Testing:
- Comprehensive test suite covering all 8 hooks
- Error handling and timeout scenarios validated
- Authentication, performance, and content extraction examples
- 100% success rate in production testing
Documentation:
- Added extensive hooks section to docker-deployment.md
- Security warnings about user-provided code risks
- Real-world examples using httpbin.org, GitHub, BBC
- Best practices and troubleshooting guide
ref #1377
* fix(deep-crawl): BestFirst priority inversion; remove pre-scoring truncation. ref #1253
Use negative scores in PQ to visit high-score URLs first and drop link cap prior to scoring; add test for ordering.
* docs: Update URL seeding examples to use proper async context managers
- Wrap all AsyncUrlSeeder usage with async context managers
- Update URL seeding adventure example to use "sitemap+cc" source, focus on course posts, and add stream=True parameter to fix runtime error
* fix(crawler): Removed the incorrect reference in browser_config variable #1310
* docs: update Docker instructions to use the latest release tag
* fix(docker): Fix LLM API key handling for multi-provider support
Previously, the system incorrectly used OPENAI_API_KEY for all LLM providers
due to a hardcoded api_key_env fallback in config.yml. This caused authentication
errors when using non-OpenAI providers like Gemini.
Changes:
- Remove api_key_env from config.yml to let litellm handle provider-specific env vars
- Simplify get_llm_api_key() to return None, allowing litellm to auto-detect keys
- Update validate_llm_provider() to trust litellm's built-in key detection
- Update documentation to reflect the new automatic key handling
The fix leverages litellm's existing capability to automatically find the correct
environment variable for each provider (OPENAI_API_KEY, GEMINI_API_TOKEN, etc.)
without manual configuration.
ref #1291
* docs: update adaptive crawler docs and cache defaults; remove deprecated examples (#1330)
- Replace BaseStrategy with CrawlStrategy in custom strategy examples (DomainSpecificStrategy, HybridStrategy)
- Remove “Custom Link Scoring” and “Caching Strategy” sections no longer aligned with current library
- Revise memory pruning example to use adaptive.get_relevant_content and index-based retention of top 500 docs
- Correct Quickstart note: default cache mode is CacheMode.BYPASS; instruct enabling with CacheMode.ENABLED
* fix(utils): Improve URL normalization by avoiding quote/unquote to preserve '+' signs. ref #1332
* feat: Add comprehensive website to API example with frontend
This commit adds a complete, web scraping API example that demonstrates how to get structured data from any website and use it like an API using the crawl4ai library with a minimalist frontend interface.
Core Functionality
- AI-powered web scraping with plain English queries
- Dual scraping approaches: Schema-based (faster) and LLM-based (flexible)
- Intelligent schema caching for improved performance
- Custom LLM model support with API key management
- Automatic duplicate request prevention
Modern Frontend Interface
- Minimalist black-and-white design inspired by modern web apps
- Responsive layout with smooth animations and transitions
- Three main pages: Scrape Data, Models Management, API Request History
- Real-time results display with JSON formatting
- Copy-to-clipboard functionality for extracted data
- Toast notifications for user feedback
- Auto-scroll to results when scraping starts
Model Management System
- Web-based model configuration interface
- Support for any LLM provider (OpenAI, Gemini, Anthropic, etc.)
- Simplified configuration requiring only provider and API token
- Add, list, and delete model configurations
- Secure storage of API keys in local JSON files
API Request History
- Automatic saving of all API requests and responses
- Display of request history with URL, query, and cURL commands
- Duplicate prevention (same URL + query combinations)
- Request deletion functionality
- Clean, simplified display focusing on essential information
Technical Implementation
Backend (FastAPI)
- RESTful API with comprehensive endpoints
- Pydantic models for request/response validation
- Async web scraping with crawl4ai library
- Error handling with detailed error messages
- File-based storage for models and request history
Frontend (Vanilla JS/CSS/HTML)
- No framework dependencies - pure HTML, CSS, JavaScript
- Modern CSS Grid and Flexbox layouts
- Custom dropdown styling with SVG arrows
- Responsive design for mobile and desktop
- Smooth scrolling and animations
Core Library Integration
- WebScraperAgent class for orchestration
- ModelConfig class for LLM configuration management
- Schema generation and caching system
- LLM extraction strategy support
- Browser configuration with headless mode
* fix(dependencies): add cssselect to project dependencies
Fixes bug reported in issue #1405
[Bug]: Excluded selector (excluded_selector) doesn't work
This commit reintroduces the cssselect library which was removed by PR (https://github.com/unclecode/crawl4ai/pull/1368) and merged via (
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ntohidi
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96c4b0de67 |
fix(browser_manager): serialize new_page on persistent context to avoid races ref #1198
- Add _page_lock and guarded creation; handle empty context.pages safely - Prevents BrowserContext.new_page “Target page/context closed” during concurrent arun_many |
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ntohidi
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0ebce590f8 | Merge branch '2025-JUN-1' into next-MAY | ||
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ntohidi
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5d9213a0e9 | fix: Update JavaScript execution in AsyncPlaywrightCrawlerStrategy to handle script errors and add basic download test case. ref #1215 | ||
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UncleCode
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c0fd36982d | Update all documentation to import extraction strategies directly from crawl4ai. | ||
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ntohidi
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4679ee023d | fix: Enhance URLPatternFilter to enforce path boundary checks for prefix matching. ref #1003 | ||
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ntohidi
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5ac19a61d7 | feat: Implement max_scroll_steps parameter for full page scanning. ref: #1168 | ||
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UncleCode
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3048cc1ff9 |
feat: Add AsyncUrlSeeder for intelligent URL discovery and filtering
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. |
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João Martins
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58c1e17170 | Merge branch 'main' into fix-raw-url-parsing | ||
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UncleCode
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7db6b468d9 |
feat(markdown): add content source selection for markdown generation
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 |
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UncleCode
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230f22da86 |
refactor(proxy): move ProxyConfig to async_configs and improve LLM token handling
Moved ProxyConfig class from proxy_strategy.py to async_configs.py for better organization. Improved LLM token handling with new PROVIDER_MODELS_PREFIXES. Added test cases for deep crawling and proxy rotation. Removed docker_config from BrowserConfig as it's handled separately. BREAKING CHANGE: ProxyConfig import path changed from crawl4ai.proxy_strategy to crawl4ai |
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unclecode
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66ac07b4f3 |
feat(crawler): add network request and console message capturing
Implement comprehensive network request and console message capturing functionality: - Add capture_network_requests and capture_console_messages config parameters - Add network_requests and console_messages fields to models - Implement Playwright event listeners to capture requests, responses, and console output - Create detailed documentation and examples - Add comprehensive tests This feature enables deep visibility into web page activity for debugging, security analysis, performance profiling, and API discovery in web applications. |