unclecode/crawl4ai
🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper. Don't be shy, join here: discord.gg/jP8KfhDhyN
🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper.
trendshift.io/repositories/11716github.com/unclecode/crawl4ai/stargazers github.com/unclecode/crawl4ai/network/membersbadge.fury.io/py/crawl4ai pypi.org/project/crawl4ai pepy.tech/project/crawl4ai github.com/sponsors/unclecode
🚀 Crawl4AI Cloud API — Closed Beta (Launching Soon)
Reliable, large-scale web extraction, now built to be drastically more cost-effective than any of the existing solutions.
👉 Apply here for early access We’ll be onboarding in phases and working closely with early users. Limited slots.
x.com/crawl4ai linkedin.com/company/crawl4ai discord.gg/jP8KfhDhyN
Crawl4AI turns the web into clean, LLM ready Markdown for RAG, agents, and data pipelines. Fast, controllable, battle tested by a 50k+ star community.
✨ Check out latest update v0.9.1
✨ New in v0.9.1: Patch release with 12 bug fixes across Docker, browser, and core. Adds preserve_classes/preserve_tags whitelist for PruningContentFilter, fixes Windows browser crash, Docker auth gate UI, HTTP timeout unit mismatch, and more. Release notes →
✨ Recent v0.9.0: Major secure-by-default release of the Docker API server. Auth is on by default, the server binds loopback unless given a token, and the request body is now an untrusted trust boundary. Release notes →
✨ Recent v0.8.7: Security-hardening release. Fixes critical Docker API vulnerabilities (RCE, SSRF, auth bypass, file write, XSS, hardcoded JWT secret), adds DomainMapper, and ships scraping, deep-crawl, and LLM fixes. Release notes →
✨ Previous v0.8.0: Crash Recovery & Prefetch Mode! Deep crawl crash recovery with resume_state and on_state_change callbacks for long-running crawls. New prefetch=True mode for 5-10x faster URL discovery. Release notes →
✨ Previous v0.7.8: Stability & Bug Fix Release! 11 bug fixes addressing Docker API issues, LLM extraction improvements, URL handling fixes, and dependency updates. Release notes →
🤓 My Personal Story
I grew up on an Amstrad, thanks to my dad, and never stopped building. In grad school I specialized in NLP and built crawlers for research. That’s where I learned how much extraction matters.
In 2023, I needed web-to-Markdown. The “open source” option wanted an account, API token, and $16, and still under-delivered. I went turbo anger mode, built Crawl4AI in days, and it went viral. Now it’s the most-starred crawler on GitHub.
I made it open source for availability, anyone can use it without a gate. Now I’m building the platform for affordability, anyone can run serious crawls without breaking the bank. If that resonates, join in, send feedback, or just crawl something amazing.
Why developers pick Crawl4AI
• LLM ready output, smart Markdown with headings, tables, code, citation hints
• Fast in practice, async browser pool, caching, minimal hops
• Full control, sessions, proxies, cookies, user scripts, hooks
• Adaptive intelligence, learns site patterns, explores only what matters
• Deploy anywhere, zero keys, CLI and Docker, cloud friendly
🚀 Quick Start
1. Install Crawl4AI:
If you encounter any browser-related issues, you can install them manually:
1. Run a simple web crawl with Python:
1. Or use the new command-line interface:
💖 Support Crawl4AI
🎉 Sponsorship Program Now Open! After powering 51K+ developers and 1 year of growth, Crawl4AI is launching dedicated support for startups and enterprises. Be among the first 50 Founding Sponsors for permanent recognition in our Hall of Fame.
Crawl4AI is the #1 trending open-source web crawler on GitHub. Your support keeps it independent, innovative, and free for the community — while giving you direct access to premium benefits.
github.com/sponsors/unclecodegithub.com/sponsors/unclecode
🤝 Sponsorship Tiers
• 🌱 Believer ($5/mo) — Join the movement for data democratization
• 🚀 Builder ($50/mo) — Priority support & early access to features
• 💼 Growing Team ($500/mo) — Bi-weekly syncs & optimization help
• 🏢 Data Infrastructure Partner ($2000/mo) — Full partnership with dedicated support Custom arrangements available - seeSPONSORS.md for details & contact
Why sponsor? No rate-limited APIs. No lock-in. Build and own your data pipeline with direct guidance from the creator of Crawl4AI.
✨ Features
📝 Markdown Generation
• 🧹 Clean Markdown: Generates clean, structured Markdown with accurate formatting.
• 🎯 Fit Markdown: Heuristic-based filtering to remove noise and irrelevant parts for AI-friendly processing.
• 🔗 Citations and References: Converts page links into a numbered reference list with clean citations.
• 🛠️ Custom Strategies: Users can create their own Markdown generation strategies tailored to specific needs.
• 📚 BM25 Algorithm: Employs BM25-based filtering for extracting core information and removing irrelevant content.
📊 Structured Data Extraction
• 🤖 LLM-Driven Extraction: Supports all LLMs (open-source and proprietary) for structured data extraction.
• 🧱 Chunking Strategies: Implements chunking (topic-based, regex, sentence-level) for targeted content processing.
• 🌌 Cosine Similarity: Find relevant content chunks based on user queries for semantic extraction.
• 🔎 CSS-Based Extraction: Fast schema-based data extraction using XPath and CSS selectors.
• 🔧 Schema Definition: Define custom schemas for extracting structured JSON from repetitive patterns.
🌐 Browser Integration
• 🖥️ Managed Browser: Use user-owned browsers with full control, avoiding bot detection.
• 🔄 Remote Browser Control: Connect to Chrome Developer Tools Protocol for remote, large-scale data extraction.
• 👤 Browser Profiler: Create and manage persistent profiles with saved authentication states, cookies, and settings.
• 🔒 Session Management: Preserve browser states and reuse them for multi-step crawling.
• 🧩 Proxy Support: Seamlessly connect to proxies with authentication for secure access.
• ⚙️ Full Browser Control: Modify headers, cookies, user agents, and more for tailored crawling setups.
• 🌍 Multi-Browser Support: Compatible with Chromium, Firefox, and WebKit.
• 📐 Dynamic Viewport Adjustment: Automatically adjusts the browser viewport to match page content, ensuring complete rendering and capturing of all elements.
🔎 Crawling & Scraping
• 🖼️ Media Support: Extract images, audio, videos, and responsive image formats like srcset and picture.
• 🚀 Dynamic Crawling: Execute JS and wait for async or sync for dynamic content extraction.
• 📸 Screenshots: Capture page screenshots during crawling for debugging or analysis.
• 📂 Raw Data Crawling: Directly process raw HTML (raw:) or local files (file://).
• 🔗 Comprehensive Link Extraction: Extracts internal, external links, and embedded iframe content.
• 🛠️ Customizable Hooks: Define hooks at every step to customize crawling behavior (supports both string and function-based APIs).
• 💾 Caching: Cache data for improved speed and to avoid redundant fetches.
• 📄 Metadata Extraction: Retrieve structured metadata from web pages.
• 📡 IFrame Content Extraction: Seamless extraction from embedded iframe content.
• 🕵️ Lazy Load Handling: Waits for images to fully load, ensuring no content is missed due to lazy loading.
• 🔄 Full-Page Scanning: Simulates scrolling to load and capture all dynamic content, perfect for infinite scroll pages.
🚀 Deployment
• 🐳 Dockerized Setup: Optimized Docker image with FastAPI server for easy deployment.
• 🔑 Secure Authentication: Built-in JWT token authentication for API security.
• 🔄 API Gateway: One-click deployment with secure token authentication for API-based workflows.
• 🌐 Scalable Architecture: Designed for mass-scale production and optimized server performance.
• ☁️ Cloud Deployment: Ready-to-deploy configurations for major cloud platforms.
🎯 Additional Features
• 🕶️ Stealth Mode: Avoid bot detection by mimicking real users.
• 🏷️ Tag-Based Content Extraction: Refine crawling based on custom tags, headers, or metadata.
• 🔗 Link Analysis: Extract and analyze all links for detailed data exploration.
• 🛡️ Error Handling: Robust error management for seamless execution.
• 🔐 CORS & Static Serving: Supports filesystem-based caching and cross-origin requests.
• 📖 Clear Documentation: Simplified and updated guides for onboarding and advanced usage.
• 🙌 Community Recognition: Acknowledges contributors and pull requests for transparency.
Try it Now!
✨ Play around with this colab.research.google.com/drive/1SgRPrByQLzjRfwoRNq1wSGE9nYY_EE8C
✨ Visit our Documentation Website
Installation 🛠️
Crawl4AI offers flexible installation options to suit various use cases. You can install it as a Python package or use Docker.
🐍 Using pip
Choose the installation option that best fits your needs:
Basic Installation
For basic web crawling and scraping tasks:
By default, this will install the asynchronous version of Crawl4AI, using Playwright for web crawling.
👉 Note: When you install Crawl4AI, the crawl4ai-setup should automatically install and set up Playwright. However, if you encounter any Playwright-related errors, you can manually install it using one of these methods:
1. Through the command line:
2. If the above doesn't work, try this more specific command:
This second method has proven to be more reliable in some cases.
Installation with Synchronous Version
The sync version is deprecated and will be removed in future versions. If you need the synchronous version using Selenium:
Development Installation
For contributors who plan to modify the source code:
Install optional features:
🐳 Docker Deployment
🚀 Now Available! Our completely redesigned Docker implementation is here! This new solution makes deployment more efficient and seamless than ever.
New Docker Features
The new Docker implementation includes:
• Real-time Monitoring Dashboard with live system metrics and browser pool visibility
• Browser pooling with page pre-warming for faster response times
• Interactive playground to test and generate request code
• MCP integration for direct connection to AI tools like Claude Code
• Comprehensive API endpoints including HTML extraction, screenshots, PDF generation, and JavaScript execution
• Multi-architecture support with automatic detection (AMD64/ARM64)
• Optimized resources with improved memory management
Getting Started
Quick Test
Run a quick test (works for both Docker options):
For more examples, see our Docker Examples. For advanced configuration, monitoring features, and production deployment, see our Self-Hosting Guide.
🔬 Advanced Usage Examples 🔬
You can check the project structure in the directory docs/examples. Over there, you can find a variety of examples; here, some popular examples are shared.
📝 Heuristic Markdown Generation with Clean and Fit Markdown
🖥️ Executing JavaScript & Extract Structured Data without LLMs
📚 Extracting Structured Data with LLMs
🤖 Using Your own Browser with Custom User Profile
✨ Recent Updates
Version 0.9.1 Release Highlights - Bug Fixes & PruningContentFilter Whitelist
A patch release with 12 bug fixes and one new feature. The new preserve_classes / preserve_tags parameters for PruningContentFilter let you whitelist CSS classes or HTML tags that should never be pruned — useful for protecting short metadata elements like author names and timestamps.
Bug fixes span Docker (auth gate UI, supervisord/redis dirs, FastAPI compatibility, redis auth), browser (Windows channel crash, context snapshot leak), core (HTTP timeout unit mismatch, best-first ordering), and extraction (html2text table attributes).
Version 0.9.0 Release Highlights - Secure-by-Default Docker Server
A major, secure-by-default release of the Docker API server. The out-of-the-box deployment is hardened with defense in depth: authentication is on by default, the server binds loopback unless you give it a token, and the network request body is treated as an untrusted trust boundary.
Migration Guide → · Full v0.9.0 Release Notes →
Version 0.8.7 Release Highlights - Security Hardening, DomainMapper & Community Fixes
A security-hardening release. Fixes critical Docker API vulnerabilities (AST sandbox escape RCE, hook sandbox RCE, hardcoded JWT secret, SSRF on webhook and crawl endpoints, arbitrary file write, monitor auth bypass, stored XSS, and unauthenticated JS execution), adds the DomainMapper feature, and ships a batch of scraping, deep-crawl, and LLM fixes. If you self-host the Docker API, upgrade immediately.
Version 0.8.6 - Security Hotfix: litellm Supply Chain Fix
Replaced litellm dependency with unclecode-litellm due to a PyPI supply chain compromise affecting the original package. If you're on v0.8.5 or earlier, upgrade immediately.
Version 0.8.5 Release Highlights - Anti-Bot Detection, Shadow DOM & 60+ Bug Fixes
Our biggest release since v0.8.0. Anti-bot detection with proxy escalation, Shadow DOM flattening, deep crawl cancellation, and over 60 bug fixes.
• 🛡️ Anti-Bot Detection & Proxy Escalation:
• 3-tier detection: known vendors, generic block indicators, structural integrity checks
• Automatic retry with proxy chain and fallback fetch function
• 🌑 Shadow DOM Flattening:
• Extract content hidden inside shadow DOM components
• 🛑 Deep Crawl Cancellation:
• Stop long crawls gracefully with cancel() or should_cancel callback
• Works with BFS, DFS, and BestFirst strategies
• ⚙️ Config Defaults API:
• set_defaults() / get_defaults() / reset_defaults() on BrowserConfig and CrawlerRunConfig
• 🔒 Critical Security Fixes:
• RCE via deserialization in Docker /crawl endpoint — removed eval(), added allowlist
• Redis CVE-2025-49844 (CVSS 10.0) — upgraded to 7.2.7
• 60+ Bug Fixes across browser management, proxy, deep crawling, extraction, CLI, and Docker
Version 0.8.0 Release Highlights - Crash Recovery & Prefetch Mode
This release introduces crash recovery for deep crawls, a new prefetch mode for fast URL discovery, and critical security fixes for Docker deployments.
• 🔄 Deep Crawl Crash Recovery:
• on_state_change callback fires after each URL for real-time state persistence
• resume_state parameter to continue from a saved checkpoint
• JSON-serializable state for Redis/database storage
• Works with BFS, DFS, and Best-First strategies
• ⚡ Prefetch Mode for Fast URL Discovery:
• prefetch=True skips markdown, extraction, and media processing
• 5-10x faster than full processing
• Perfect for two-phase crawling: discover first, process selectively
• 🔒 Security Fixes (Docker API):
• Hooks disabled by default (CRAWL4AI_HOOKS_ENABLED=false)
• file:// URLs blocked on API endpoints to prevent LFI
• import removed from hook execution sandbox
Version 0.7.8 Release Highlights - Stability & Bug Fix Release
This release focuses on stability with 11 bug fixes addressing issues reported by the community. No new features, but significant improvements to reliability.
• 🐳 Docker API Fixes:
• Fixed ContentRelevanceFilter deserialization in deep crawl requests (#1642)
• Fixed ProxyConfig JSON serialization in BrowserConfig.to_dict() (#1629)
• Fixed .cache folder permissions in Docker image (#1638)
• 🤖 LLM Extraction Improvements:
• Configurable rate limiter backoff with new LLMConfig parameters (#1269):
• HTML input format support for LLMExtractionStrategy (#1178):
• Fixed raw HTML URL variable - extraction strategies now receive "Raw HTML" instead of HTML blob (#1116)
• 🔗 URL Handling:
• Fixed relative URL resolution after JavaScript redirects (#1268)
• Fixed import statement formatting in extracted code (#1181)
• 📦 Dependency Updates:
• Replaced deprecated PyPDF2 with pypdf (#1412)
• Pydantic v2 ConfigDict compatibility - no more deprecation warnings (#678)
• 🧠 AdaptiveCrawler:
• Fixed query expansion to actually use LLM instead of hardcoded mock data (#1621)
Version 0.7.7 Release Highlights - The Self-Hosting & Monitoring Update
• 📊 Real-time Monitoring Dashboard: Interactive web UI with live system metrics and browser pool visibility
• 🔌 Comprehensive Monitor API: Complete REST API for programmatic access to all monitoring data
• ⚡ WebSocket Streaming: Real-time updates every 2 seconds for custom dashboards
• 🔥 Smart Browser Pool: 3-tier architecture (permanent/hot/cold) with automatic promotion and cleanup
• 🧹 Janitor System: Automatic resource management with event logging
• 🎮 Control Actions: Manual browser management (kill, restart, cleanup) via API
• 📈 Production Metrics: 6 critical metrics for operational excellence with Prometheus integration
• 🐛 Critical Bug Fixes:
• Fixed async LLM extraction blocking issue (#1055)
• Enhanced DFS deep crawl strategy (#1607)
• Fixed sitemap parsing in AsyncUrlSeeder (#1598)
• Resolved browser viewport configuration (#1495)
• Fixed CDP timing with exponential backoff (#1528)
• Security update for pyOpenSSL (>=25.3.0)
Version 0.7.5 Release Highlights - The Docker Hooks & Security Update
• 🔧 Docker Hooks System: Complete pipeline customization with user-provided Python functions at 8 key points
• ✨ Function-Based Hooks API (NEW): Write hooks as regular Python functions with full IDE support:
• 🤖 Enhanced LLM Integration: Custom providers with temperature control and base_url configuration
• 🔒 HTTPS Preservation: Secure internal link handling with preserve_https_for_internal_links=True
• 🐍 Python 3.10+ Support: Modern language features and enhanced performance
• 🛠️ Bug Fixes: Resolved multiple community-reported issues including URL processing, JWT authentication, and proxy configuration
Version 0.7.4 Release Highlights - The Intelligent Table Extraction & Performance Update
• 🚀 LLMTableExtraction: Revolutionary table extraction with intelligent chunking for massive tables:
• ⚡ Dispatcher Bug Fix: Fixed sequential processing bottleneck in arun_many for fast-completing tasks
• 🧹 Memory Management Refactor: Consolidated memory utilities into main utils module for cleaner architecture
• 🔧 Browser Manager Fixes: Resolved race conditions in concurrent page creation with thread-safe locking
• 🔗 Advanced URL Processing: Better handling of raw:// URLs and base tag link resolution
• 🛡️ Enhanced Proxy Support: Flexible proxy configuration supporting both dict and string formats
Version 0.7.3 Release Highlights - The Multi-Config Intelligence Update
• 🕵️ Undetected Browser Support: Bypass sophisticated bot detection systems:
• 🎨 Multi-URL Configuration: Different strategies for different URL patterns in one batch:
• 🧠 Memory Monitoring: Track and optimize memory usage during crawling:
• 📊 Enhanced Table Extraction: Direct DataFrame conversion from web tables:
• 💰 GitHub Sponsors: 4-tier sponsorship system for project sustainability
• 🐳 Docker LLM Flexibility: Configure providers via environment variables
Version 0.7.0 Release Highlights - The Adaptive Intelligence Update
• 🧠 Adaptive Crawling: Your crawler now learns and adapts to website patterns automatically:
• 🌊 Virtual Scroll Support: Complete content extraction from infinite scroll pages:
• 🔗 Intelligent Link Analysis: 3-layer scoring system for smart link prioritization:
• 🎣 Async URL Seeder: Discover thousands of URLs in seconds:
• ⚡ Performance Boost: Up to 3x faster with optimized resource handling and memory efficiency
Read the full details in our 0.7.0 Release Notes or check the CHANGELOG.
Version Numbering in Crawl4AI
Crawl4AI follows standard Python version numbering conventions (PEP 440) to help users understand the stability and features of each release.
📈 Version Numbers Explained
Our version numbers follow this pattern: MAJOR.MINOR.PATCH (e.g., 0.4.3)
Pre-release Versions
We use different suffixes to indicate development stages:
• dev (0.4.3dev1): Development versions, unstable
• a (0.4.3a1): Alpha releases, experimental features
• b (0.4.3b1): Beta releases, feature complete but needs testing
• rc (0.4.3): Release candidates, potential final version
Installation
• Regular installation (stable version):
• Install pre-release versions:
• Install specific version:
Why Pre-releases?
We use pre-releases to:
• Test new features in real-world scenarios
• Gather feedback before final releases
• Ensure stability for production users
• Allow early adopters to try new features
For production environments, we recommend using the stable version. For testing new features, you can opt-in to pre-releases using the --pre flag.
📖 Documentation & Roadmap
🚨 Documentation Update Alert: We're undertaking a major documentation overhaul next week to reflect recent updates and improvements. Stay tuned for a more comprehensive and up-to-date guide!
For current documentation, including installation instructions, advanced features, and API reference, visit our Documentation Website.
To check our development plans and upcoming features, visit our Roadmap.
📈 Development TODOs
• 0. Graph Crawler: Smart website traversal using graph search algorithms for comprehensive nested page extraction
• 1. Question-Based Crawler: Natural language driven web discovery and content extraction
• 2. Knowledge-Optimal Crawler: Smart crawling that maximizes knowledge while minimizing data extraction
• 3. Agentic Crawler: Autonomous system for complex multi-step crawling operations
• 4. Automated Schema Generator: Convert natural language to extraction schemas
• 5. Domain-Specific Scrapers: Pre-configured extractors for common platforms (academic, e-commerce)
• 6. Web Embedding Index: Semantic search infrastructure for crawled content
• 7. Interactive Playground: Web UI for testing, comparing strategies with AI assistance
• 8. Performance Monitor: Real-time insights into crawler operations
• 9. Cloud Integration: One-click deployment solutions across cloud providers
• 10. Sponsorship Program: Structured support system with tiered benefits
• 11. Educational Content: "How to Crawl" video series and interactive tutorials
🤝 Contributing
We welcome contributions from the open-source community. Check out our contribution guidelines for more information.
I'll help modify the license section with badges. For the halftone effect, here's a version with it:
Here's the updated license section:
📄 License & Attribution
This project is licensed under the Apache License 2.0, attribution is recommended via the badges below. See the Apache 2.0 License file for details.
Attribution Requirements
When using Crawl4AI, you must include one of the following attribution methods:
📈 1. Badge Attribution (Recommended) Add one of these badges to your README, documentation, or website:
HTML code for adding the badges:
📖 2. Text Attribution Add this line to your documentation: `` This project uses Crawl4AI (github.com/unclecode/crawl4ai) for web data extraction. ``
📚 Citation
If you use Crawl4AI in your research or project, please cite:
Text citation format:
📧 Contact
For questions, suggestions, or feedback, feel free to reach out:
• GitHub: unclecode
• Twitter: @unclecode
• Website: crawl4ai.com
Happy Crawling! 🕸️🚀
🗾 Mission
Our mission is to unlock the value of personal and enterprise data by transforming digital footprints into structured, tradeable assets. Crawl4AI empowers individuals and organizations with open-source tools to extract and structure data, fostering a shared data economy.
We envision a future where AI is powered by real human knowledge, ensuring data creators directly benefit from their contributions. By democratizing data and enabling ethical sharing, we are laying the foundation for authentic AI advancement.
🔑 Key Opportunities
• Data Capitalization: Transform digital footprints into measurable, valuable assets.
• Authentic AI Data: Provide AI systems with real human insights.
• Shared Economy: Create a fair data marketplace that benefits data creators.
🚀 Development Pathway
1. Open-Source Tools: Community-driven platforms for transparent data extraction.
2. Digital Asset Structuring: Tools to organize and value digital knowledge.
3. Ethical Data Marketplace: A secure, fair platform for exchanging structured data.
For more details, see our full mission statement.
🌟 Current Sponsors
🤝 Strategic Partners
These companies provide core infrastructure and technology that power Crawl4AI’s capabilities — from web access and proxy networks to AI tooling and data pipelines.
🏢 Enterprise Sponsors
Our enterprise sponsors support Crawl4AI and help scale it to power production-grade data pipelines.
💼 Become a Strategic Partner or Sponsor
Interested in partnering with Crawl4AI?
Whether you’re a proxy provider, AI infrastructure company, cloud platform, or an organization looking to support the Crawl4AI ecosystem, we’d love to hear from you.
📩 Contact: hello@crawl4ai.com
🧑🤝 Individual Sponsors
A heartfelt thanks to our individual supporters! Every contribution helps us keep our opensource mission alive and thriving!
github.com/hafezparast github.com/ntohidi github.com/Sjoeborg github.com/romek-rozen github.com/Kourosh-Kiyani github.com/Etherdrake github.com/shaman247 github.com/work-flow-manager
Want to join them? Sponsor Crawl4AI →
Star History
点赞
收藏
点踩
分享