- Introduced a demo script (`demo_monitor_dashboard.py`) to showcase various monitoring features through simulated activity.
- Implemented a test script (`test_monitor_demo.py`) to generate dashboard activity and verify monitor health and endpoint statistics.
- Added a logo image to the static assets for branding purposes.
- Return comprehensive error messages along with status codes for api internal errors.
- Fix fit_html property serialization issue in both /crawl and /crawl/stream endpoints
- Add sanitization to ensure fit_html is always JSON-serializable (string or None)
- Add comprehensive error handling test suite.
Implement hierarchical configuration for LLM parameters with support for:
- Temperature control (0.0-2.0) to adjust response creativity
- Custom base_url for proxy servers and alternative endpoints
- 4-tier priority: request params > provider env > global env > defaults
Add helper functions in utils.py, update API schemas and handlers,
support environment variables (LLM_TEMPERATURE, OPENAI_TEMPERATURE, etc.),
and provide comprehensive documentation with examples.
- Add raw HTML URL validation alongside http/https checks
- Fix URL preprocessing logic to handle raw: and raw:// prefixes
- Update error message and add comprehensive test cases
- 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
Implements new asynchronous endpoints for handling long-running crawl and LLM tasks:
- POST /crawl/job and GET /crawl/job/{task_id} for crawl operations
- POST /llm/job and GET /llm/job/{task_id} for LLM operations
- Added Redis-based task management with configurable TTL
- Moved schema definitions to dedicated schemas.py
- Added example polling client demo_docker_polling.py
This change allows clients to handle long-running operations asynchronously through a polling pattern rather than holding connections open.
Major updates to Docker deployment infrastructure:
- Switch default port to 11235 for all services
- Add MCP (Model Context Protocol) support with WebSocket/SSE endpoints
- Simplify docker-compose.yml with auto-platform detection
- Update documentation with new features and examples
- Consolidate configuration and improve resource management
BREAKING CHANGE: Default port changed from 8020 to 11235. Update your configurations and deployment scripts accordingly.
This commit introduces several significant enhancements to the Crawl4AI Docker deployment:
1. Add MCP Protocol Support:
- Implement WebSocket and SSE transport layers for MCP server communication
- Create mcp_bridge.py to expose existing API endpoints via MCP protocol
- Add comprehensive tests for both socket and SSE transport methods
2. Enhance Docker Server Capabilities:
- Add PDF generation endpoint with file saving functionality
- Add screenshot capture endpoint with configurable wait time
- Implement JavaScript execution endpoint for dynamic page interaction
- Add intelligent file path handling for saving generated assets
3. Improve Search and Context Functionality:
- Implement syntax-aware code function chunking using AST parsing
- Add BM25-based intelligent document search with relevance scoring
- Create separate code and documentation context endpoints
- Enhance response format with structured results and scores
4. Rename and Fix File Organization:
- Fix typo in test_docker_config_gen.py filename
- Update import statements and dependencies
- Add FileResponse for context endpoints
This enhancement significantly improves the machine-to-machine communication
capabilities of Crawl4AI, making it more suitable for integration with LLM agents
and other automated systems.
The CHANGELOG update has been applied successfully, highlighting the key features and improvements made in this release. The commit message provides a detailed explanation of all the
changes, which will be helpful for tracking the project's evolution.
Replace crawler_manager.py with simpler crawler_pool.py implementation:
- Add global page semaphore for hard concurrency cap
- Implement browser pool with idle cleanup
- Add playground UI for testing and stress testing
- Update API handlers to use pooled crawlers
- Enhance logging levels and symbols
BREAKING CHANGE: Removes CrawlerManager class in favor of simpler pool-based approach
Adds a new CrawlerManager class to handle browser instance pooling and failover:
- Implements auto-scaling based on system resources
- Adds primary/backup crawler management
- Integrates memory monitoring and throttling
- Adds streaming support with memory tracking
- Updates API endpoints to use pooled crawlers
BREAKING CHANGE: API endpoints now require CrawlerManager initialization
Modify authentication system to gracefully handle cases where JWT is not enabled or token is missing. This includes:
- Making HTTPBearer auto_error=False to prevent automatic 403 errors
- Updating token dependency to return None when JWT is disabled
- Fixing model deserialization in CrawlResult
- Updating documentation links
- Cleaning up imports
BREAKING CHANGE: Authentication behavior changed to be more permissive when JWT is disabled
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 JWT token-based authentication to Docker server and client.
Refactor server architecture for better code organization and error handling.
Move Dockerfile to root deploy directory and update configuration.
Add comprehensive documentation and examples.
BREAKING CHANGE: Docker server now requires authentication by default.
Endpoints require JWT tokens when security.jwt_enabled is true in config.
Add supervisor configuration for managing Redis and Gunicorn processes
Replace direct process management with supervisord
Add secure and token-free API server variants
Implement JWT authentication for protected endpoints
Update datetime handling in async dispatcher
Add email domain verification
BREAKING CHANGE: Server startup now uses supervisord instead of direct process management
Complete overhaul of Docker deployment setup with improved architecture:
- Add Redis integration for task management
- Implement rate limiting and security middleware
- Add Prometheus metrics and health checks
- Improve error handling and logging
- Add support for streaming responses
- Implement proper configuration management
- Add platform-specific optimizations for ARM64/AMD64
BREAKING CHANGE: Docker deployment now requires Redis and new config.yml structure
Add Docker service integration with FastAPI server and client implementation.
Implement serialization utilities for BrowserConfig and CrawlerRunConfig to support
Docker service communication. Clean up imports and improve error handling.
- Add Crawl4aiDockerClient class
- Implement config serialization/deserialization
- Add FastAPI server with streaming support
- Add health check endpoint
- Clean up imports and type hints
Add Docker deployment setup with FastAPI server implementation for Crawl4AI:
- Create Dockerfile with Python 3.10 and Playwright dependencies
- Implement FastAPI server with streaming and non-streaming endpoints
- Add request/response models and JSON serialization
- Include test script for API verification
Also includes:
- Update .gitignore for Continue development files
- Add project rules in .continuerules
- Clean up async_dispatcher.py formatting
