feat: Enhance stealth compatibility with new and legacy APIs, add configuration support

feat: Add stealth option to BrowserConfig for enhanced browser behavior
fix: Update playwright-stealth to v2.0.0+ compatibility
2025-07-16 17:41:47 +08:00 · 2025-07-15 15:48:23 +08:00 · 2025-07-15 15:31:15 +08:00
91 changed files with 2420 additions and 9733 deletions
--- a/.github/FUNDING.yml
+++ b/.github/FUNDING.yml
@@ -1,7 +0,0 @@
-# These are supported funding model platforms
-
-# GitHub Sponsors
-github: unclecode
-
-# Custom links for enterprise inquiries (uncomment when ready)
-# custom: ["https://crawl4ai.com/enterprise"]
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -1,142 +0,0 @@
-name: Release Pipeline
-on:
-  push:
-    tags:
-      - 'v*'
-      - '!test-v*'  # Exclude test tags
-
-jobs:
-  release:
-    runs-on: ubuntu-latest
-    permissions:
-      contents: write  # Required for creating releases
-    
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-      
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-      
-      - name: Extract version from tag
-        id: get_version
-        run: |
-          TAG_VERSION=${GITHUB_REF#refs/tags/v}
-          echo "VERSION=$TAG_VERSION" >> $GITHUB_OUTPUT
-          echo "Releasing version: $TAG_VERSION"
-      
-      - name: Install package dependencies
-        run: |
-          pip install -e .
-      
-      - name: Check version consistency
-        run: |
-          TAG_VERSION=${{ steps.get_version.outputs.VERSION }}
-          PACKAGE_VERSION=$(python -c "from crawl4ai.__version__ import __version__; print(__version__)")
-          
-          echo "Tag version: $TAG_VERSION"
-          echo "Package version: $PACKAGE_VERSION"
-          
-          if [ "$TAG_VERSION" != "$PACKAGE_VERSION" ]; then
-            echo "❌ Version mismatch! Tag: $TAG_VERSION, Package: $PACKAGE_VERSION"
-            echo "Please update crawl4ai/__version__.py to match the tag version"
-            exit 1
-          fi
-          echo "✅ Version check passed: $TAG_VERSION"
-      
-      - name: Install build dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install build twine
-      
-      - name: Build package
-        run: python -m build
-      
-      - name: Check package
-        run: twine check dist/*
-      
-      - name: Upload to PyPI
-        env:
-          TWINE_USERNAME: __token__
-          TWINE_PASSWORD: ${{ secrets.PYPI_TOKEN }}
-        run: |
-          echo "📦 Uploading to PyPI..."
-          twine upload dist/*
-          echo "✅ Package uploaded to https://pypi.org/project/crawl4ai/"
-      
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-      
-      - name: Log in to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          username: ${{ secrets.DOCKER_USERNAME }}
-          password: ${{ secrets.DOCKER_TOKEN }}
-      
-      - name: Extract major and minor versions
-        id: versions
-        run: |
-          VERSION=${{ steps.get_version.outputs.VERSION }}
-          MAJOR=$(echo $VERSION | cut -d. -f1)
-          MINOR=$(echo $VERSION | cut -d. -f1-2)
-          echo "MAJOR=$MAJOR" >> $GITHUB_OUTPUT
-          echo "MINOR=$MINOR" >> $GITHUB_OUTPUT
-      
-      - name: Build and push Docker images
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          push: true
-          tags: |
-            unclecode/crawl4ai:${{ steps.get_version.outputs.VERSION }}
-            unclecode/crawl4ai:${{ steps.versions.outputs.MINOR }}
-            unclecode/crawl4ai:${{ steps.versions.outputs.MAJOR }}
-            unclecode/crawl4ai:latest
-          platforms: linux/amd64,linux/arm64
-      
-      - name: Create GitHub Release
-        uses: softprops/action-gh-release@v2
-        with:
-          tag_name: v${{ steps.get_version.outputs.VERSION }}
-          name: Release v${{ steps.get_version.outputs.VERSION }}
-          body: |
-            ## 🎉 Crawl4AI v${{ steps.get_version.outputs.VERSION }} Released!
-            
-            ### 📦 Installation
-            
-            **PyPI:**
-            ```bash
-            pip install crawl4ai==${{ steps.get_version.outputs.VERSION }}
-            ```
-            
-            **Docker:**
-            ```bash
-            docker pull unclecode/crawl4ai:${{ steps.get_version.outputs.VERSION }}
-            docker pull unclecode/crawl4ai:latest
-            ```
-            
-            ### 📝 What's Changed
-            See [CHANGELOG.md](https://github.com/${{ github.repository }}/blob/main/CHANGELOG.md) for details.
-          draft: false
-          prerelease: false
-          token: ${{ secrets.GITHUB_TOKEN }}
-      
-      - name: Summary
-        run: |
-          echo "## 🚀 Release Complete!" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "### 📦 PyPI Package" >> $GITHUB_STEP_SUMMARY
-          echo "- Version: ${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
-          echo "- URL: https://pypi.org/project/crawl4ai/" >> $GITHUB_STEP_SUMMARY
-          echo "- Install: \`pip install crawl4ai==${{ steps.get_version.outputs.VERSION }}\`" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "### 🐳 Docker Images" >> $GITHUB_STEP_SUMMARY
-          echo "- \`unclecode/crawl4ai:${{ steps.get_version.outputs.VERSION }}\`" >> $GITHUB_STEP_SUMMARY
-          echo "- \`unclecode/crawl4ai:${{ steps.versions.outputs.MINOR }}\`" >> $GITHUB_STEP_SUMMARY
-          echo "- \`unclecode/crawl4ai:${{ steps.versions.outputs.MAJOR }}\`" >> $GITHUB_STEP_SUMMARY
-          echo "- \`unclecode/crawl4ai:latest\`" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "### 📋 GitHub Release" >> $GITHUB_STEP_SUMMARY
-          echo "https://github.com/${{ github.repository }}/releases/tag/v${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
--- a/.github/workflows/test-release.yml.disabled
+++ b/.github/workflows/test-release.yml.disabled
@@ -1,116 +0,0 @@
-name: Test Release Pipeline
-on:
-  push:
-    tags:
-      - 'test-v*'
-
-jobs:
-  test-release:
-    runs-on: ubuntu-latest
-    
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-      
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-      
-      - name: Extract version from tag
-        id: get_version
-        run: |
-          TAG_VERSION=${GITHUB_REF#refs/tags/test-v}
-          echo "VERSION=$TAG_VERSION" >> $GITHUB_OUTPUT
-          echo "Testing with version: $TAG_VERSION"
-      
-      - name: Install package dependencies
-        run: |
-          pip install -e .
-      
-      - name: Check version consistency
-        run: |
-          TAG_VERSION=${{ steps.get_version.outputs.VERSION }}
-          PACKAGE_VERSION=$(python -c "from crawl4ai.__version__ import __version__; print(__version__)")
-          
-          echo "Tag version: $TAG_VERSION"
-          echo "Package version: $PACKAGE_VERSION"
-          
-          if [ "$TAG_VERSION" != "$PACKAGE_VERSION" ]; then
-            echo "❌ Version mismatch! Tag: $TAG_VERSION, Package: $PACKAGE_VERSION"
-            echo "Please update crawl4ai/__version__.py to match the tag version"
-            exit 1
-          fi
-          echo "✅ Version check passed: $TAG_VERSION"
-      
-      - name: Install build dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install build twine
-      
-      - name: Build package
-        run: python -m build
-      
-      - name: Check package
-        run: twine check dist/*
-      
-      - name: Upload to Test PyPI
-        env:
-          TWINE_USERNAME: __token__
-          TWINE_PASSWORD: ${{ secrets.TEST_PYPI_TOKEN }}
-        run: |
-          echo "📦 Uploading to Test PyPI..."
-          twine upload --repository testpypi dist/* || {
-            if [ $? -eq 1 ]; then
-              echo "⚠️ Upload failed - likely version already exists on Test PyPI"
-              echo "Continuing anyway for test purposes..."
-            else
-              exit 1
-            fi
-          }
-          echo "✅ Test PyPI step complete"
-      
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-      
-      - name: Log in to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          username: ${{ secrets.DOCKER_USERNAME }}
-          password: ${{ secrets.DOCKER_TOKEN }}
-      
-      - name: Build and push Docker test images
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          push: true
-          tags: |
-            unclecode/crawl4ai:test-${{ steps.get_version.outputs.VERSION }}
-            unclecode/crawl4ai:test-latest
-          platforms: linux/amd64,linux/arm64
-          cache-from: type=gha
-          cache-to: type=gha,mode=max
-      
-      - name: Summary
-        run: |
-          echo "## 🎉 Test Release Complete!" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "### 📦 Test PyPI Package" >> $GITHUB_STEP_SUMMARY
-          echo "- Version: ${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
-          echo "- URL: https://test.pypi.org/project/crawl4ai/" >> $GITHUB_STEP_SUMMARY
-          echo "- Install: \`pip install -i https://test.pypi.org/simple/ crawl4ai==${{ steps.get_version.outputs.VERSION }}\`" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "### 🐳 Docker Test Images" >> $GITHUB_STEP_SUMMARY
-          echo "- \`unclecode/crawl4ai:test-${{ steps.get_version.outputs.VERSION }}\`" >> $GITHUB_STEP_SUMMARY
-          echo "- \`unclecode/crawl4ai:test-latest\`" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "### 🧹 Cleanup Commands" >> $GITHUB_STEP_SUMMARY
-          echo "\`\`\`bash" >> $GITHUB_STEP_SUMMARY
-          echo "# Remove test tag" >> $GITHUB_STEP_SUMMARY
-          echo "git tag -d test-v${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
-          echo "git push origin :test-v${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
-          echo "" >> $GITHUB_STEP_SUMMARY
-          echo "# Remove Docker test images" >> $GITHUB_STEP_SUMMARY
-          echo "docker rmi unclecode/crawl4ai:test-${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
-          echo "docker rmi unclecode/crawl4ai:test-latest" >> $GITHUB_STEP_SUMMARY
-          echo "\`\`\`" >> $GITHUB_STEP_SUMMARY
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -21,21 +21,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

-### Added
- **Flexible LLM Provider Configuration** (Docker): 
-  - Support for `LLM_PROVIDER` environment variable to override default provider
-  - Per-request provider override via optional `provider` parameter in API endpoints
-  - Automatic provider validation with clear error messages
-  - Updated Docker documentation and examples
-
-### Changed
- **WebScrapingStrategy Refactoring**: Simplified content scraping architecture
-  - `WebScrapingStrategy` is now an alias for `LXMLWebScrapingStrategy` for backward compatibility
-  - Removed redundant BeautifulSoup-based implementation (~1000 lines of code)
-  - `LXMLWebScrapingStrategy` now inherits directly from `ContentScrapingStrategy`
-  - All existing code using `WebScrapingStrategy` continues to work without modification
-  - Default scraping strategy remains `LXMLWebScrapingStrategy` for optimal performance
-
 ### Added
 - **AsyncUrlSeeder**: High-performance URL discovery system for intelligent crawling at scale
  - Discover URLs from sitemaps and Common Crawl index
--- a/README-first.md
+++ b/README-first.md
@@ -1,809 +0,0 @@
-# 🚀🤖 Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper.
-
-<div align="center">
-
-<a href="https://trendshift.io/repositories/11716" target="_blank"><img src="https://trendshift.io/api/badge/repositories/11716" alt="unclecode%2Fcrawl4ai | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
-
-[![GitHub Stars](https://img.shields.io/github/stars/unclecode/crawl4ai?style=social)](https://github.com/unclecode/crawl4ai/stargazers)
-[![GitHub Forks](https://img.shields.io/github/forks/unclecode/crawl4ai?style=social)](https://github.com/unclecode/crawl4ai/network/members)
-
-[![PyPI version](https://badge.fury.io/py/crawl4ai.svg)](https://badge.fury.io/py/crawl4ai)
-[![Python Version](https://img.shields.io/pypi/pyversions/crawl4ai)](https://pypi.org/project/crawl4ai/)
-[![Downloads](https://static.pepy.tech/badge/crawl4ai/month)](https://pepy.tech/project/crawl4ai)
-[![GitHub Sponsors](https://img.shields.io/github/sponsors/unclecode?style=flat&logo=GitHub-Sponsors&label=Sponsors&color=pink)](https://github.com/sponsors/unclecode)
-
-<p align="center">
-    <a href="https://x.com/crawl4ai">
-      <img src="https://img.shields.io/badge/Follow%20on%20X-000000?style=for-the-badge&logo=x&logoColor=white" alt="Follow on X" />
-    </a>
-    <a href="https://www.linkedin.com/company/crawl4ai">
-      <img src="https://img.shields.io/badge/Follow%20on%20LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white" alt="Follow on LinkedIn" />
-    </a>
-    <a href="https://discord.gg/jP8KfhDhyN">
-      <img src="https://img.shields.io/badge/Join%20our%20Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white" alt="Join our Discord" />
-    </a>
-  </p>
-</div>
-
-Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant community. It delivers blazing-fast, AI-ready web crawling tailored for LLMs, AI agents, and data pipelines. Open source, flexible, and built for real-time performance, Crawl4AI empowers developers with unmatched speed, precision, and deployment ease.  
-
-[✨ Check out latest update v0.7.0](#-recent-updates)
-
-🎉 **Version 0.7.0 is now available!** The Adaptive Intelligence Update introduces groundbreaking features: Adaptive Crawling that learns website patterns, Virtual Scroll support for infinite pages, intelligent Link Preview with 3-layer scoring, Async URL Seeder for massive discovery, and significant performance improvements. [Read the release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.0.md)
-
-<details>
-<summary>🤓 <strong>My Personal Story</strong></summary>
-
-My journey with computers started in childhood when my dad, a computer scientist, introduced me to an Amstrad computer. Those early days sparked a fascination with technology, leading me to pursue computer science and specialize in NLP during my postgraduate studies. It was during this time that I first delved into web crawling, building tools to help researchers organize papers and extract information from publications a challenging yet rewarding experience that honed my skills in data extraction.
-
-Fast forward to 2023, I was working on a tool for a project and needed a crawler to convert a webpage into markdown. While exploring solutions, I found one that claimed to be open-source but required creating an account and generating an API token. Worse, it turned out to be a SaaS model charging $16, and its quality didn’t meet my standards. Frustrated, I realized this was a deeper problem. That frustration turned into turbo anger mode, and I decided to build my own solution. In just a few days, I created Crawl4AI. To my surprise, it went viral, earning thousands of GitHub stars and resonating with a global community.
-
-I made Crawl4AI open-source for two reasons. First, it’s my way of giving back to the open-source community that has supported me throughout my career. Second, I believe data should be accessible to everyone, not locked behind paywalls or monopolized by a few. Open access to data lays the foundation for the democratization of AI, a vision where individuals can train their own models and take ownership of their information. This library is the first step in a larger journey to create the best open-source data extraction and generation tool the world has ever seen, built collaboratively by a passionate community.
-
-Thank you to everyone who has supported this project, used it, and shared feedback. Your encouragement motivates me to dream even bigger. Join us, file issues, submit PRs, or spread the word. Together, we can build a tool that truly empowers people to access their own data and reshape the future of AI.
-</details>
-
-## 🧐 Why Crawl4AI?
-
-1. **Built for LLMs**: Creates smart, concise Markdown optimized for RAG and fine-tuning applications.  
-2. **Lightning Fast**: Delivers results faster with real-time, cost-efficient performance.  
-3. **Flexible Browser Control**: Offers session management, proxies, and custom hooks for seamless data access.  
-4. **Heuristic Intelligence**: Uses advanced algorithms for efficient extraction, reducing reliance on costly models.  
-5. **Open Source & Deployable**: Fully open-source with no API keys—ready for Docker and cloud integration.  
-6. **Thriving Community**: Actively maintained by a vibrant community and the #1 trending GitHub repository.
-
-## 🚀 Quick Start 
-
-1. Install Crawl4AI:
-```bash
-# Install the package
-pip install -U crawl4ai
-
-# For pre release versions
-pip install crawl4ai --pre
-
-# Run post-installation setup
-crawl4ai-setup
-
-# Verify your installation
-crawl4ai-doctor
-```
-
-If you encounter any browser-related issues, you can install them manually:
-```bash
-python -m playwright install --with-deps chromium
-```
-
-2. Run a simple web crawl with Python:
-```python
-import asyncio
-from crawl4ai import *
-
-async def main():
-    async with AsyncWebCrawler() as crawler:
-        result = await crawler.arun(
-            url="https://www.nbcnews.com/business",
-        )
-        print(result.markdown)
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-3. Or use the new command-line interface:
-```bash
-# Basic crawl with markdown output
-crwl https://www.nbcnews.com/business -o markdown
-
-# Deep crawl with BFS strategy, max 10 pages
-crwl https://docs.crawl4ai.com --deep-crawl bfs --max-pages 10
-
-# Use LLM extraction with a specific question
-crwl https://www.example.com/products -q "Extract all product prices"
-```
-
-## ✨ Features 
-
-<details>
-<summary>📝 <strong>Markdown Generation</strong></summary>
-
- 🧹 **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. 
-</details>
-
-<details>
-<summary>📊 <strong>Structured Data Extraction</strong></summary>
-
- 🤖 **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.
-
-</details>
-
-<details>
-<summary>🌐 <strong>Browser Integration</strong></summary>
-
- 🖥️ **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.
-
-</details>
-
-<details>
-<summary>🔎 <strong>Crawling & Scraping</strong></summary>
-
- 🖼️ **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.
- 💾 **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.
-
-</details>
-
-<details>
-<summary>🚀 <strong>Deployment</strong></summary>
-
- 🐳 **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.
-
-</details>
-
-<details>
-<summary>🎯 <strong>Additional Features</strong></summary>
-
- 🕶️ **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.
-
-</details>
-
-## Try it Now!
-
-✨ Play around with this [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1SgRPrByQLzjRfwoRNq1wSGE9nYY_EE8C?usp=sharing)
-
-✨ Visit our [Documentation Website](https://docs.crawl4ai.com/)
-
-## Installation 🛠️
-
-Crawl4AI offers flexible installation options to suit various use cases. You can install it as a Python package or use Docker.
-
-<details>
-<summary>🐍 <strong>Using pip</strong></summary>
-
-Choose the installation option that best fits your needs:
-
-### Basic Installation
-
-For basic web crawling and scraping tasks:
-
-```bash
-pip install crawl4ai
-crawl4ai-setup # Setup the browser
-```
-
-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:
-
-   ```bash
-   playwright install
-   ```
-
-2. If the above doesn't work, try this more specific command:
-
-   ```bash
-   python -m playwright install chromium
-   ```
-
-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:
-
-```bash
-pip install crawl4ai[sync]
-```
-
---
-
-### Development Installation
-
-For contributors who plan to modify the source code:
-
-```bash
-git clone https://github.com/unclecode/crawl4ai.git
-cd crawl4ai
-pip install -e .                    # Basic installation in editable mode
-```
-
-Install optional features:
-
-```bash
-pip install -e ".[torch]"           # With PyTorch features
-pip install -e ".[transformer]"     # With Transformer features
-pip install -e ".[cosine]"          # With cosine similarity features
-pip install -e ".[sync]"            # With synchronous crawling (Selenium)
-pip install -e ".[all]"             # Install all optional features
-```
-
-</details>
-
-<details>
-<summary>🐳 <strong>Docker Deployment</strong></summary>
-
-> 🚀 **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:
- **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
-
-```bash
-# Pull and run the latest release candidate
-docker pull unclecode/crawl4ai:0.7.0
-docker run -d -p 11235:11235 --name crawl4ai --shm-size=1g unclecode/crawl4ai:0.7.0
-
-# Visit the playground at http://localhost:11235/playground
-```
-
-For complete documentation, see our [Docker Deployment Guide](https://docs.crawl4ai.com/core/docker-deployment/).
-
-</details>
-
---
-
-### Quick Test
-
-Run a quick test (works for both Docker options):
-
-```python
-import requests
-
-# Submit a crawl job
-response = requests.post(
-    "http://localhost:11235/crawl",
-    json={"urls": ["https://example.com"], "priority": 10}
-)
-if response.status_code == 200:
-    print("Crawl job submitted successfully.")
-    
-if "results" in response.json():
-    results = response.json()["results"]
-    print("Crawl job completed. Results:")
-    for result in results:
-        print(result)
-else:
-    task_id = response.json()["task_id"]
-    print(f"Crawl job submitted. Task ID:: {task_id}")
-    result = requests.get(f"http://localhost:11235/task/{task_id}")
-```
-
-For more examples, see our [Docker Examples](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/docker_example.py). For advanced configuration, environment variables, and usage examples, see our [Docker Deployment Guide](https://docs.crawl4ai.com/basic/docker-deployment/).
-
-</details>
-
-
-## 🔬 Advanced Usage Examples 🔬
-
-You can check the project structure in the directory [docs/examples](https://github.com/unclecode/crawl4ai/tree/main/docs/examples). Over there, you can find a variety of examples; here, some popular examples are shared.
-
-<details>
-<summary>📝 <strong>Heuristic Markdown Generation with Clean and Fit Markdown</strong></summary>
-
-```python
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
-from crawl4ai.content_filter_strategy import PruningContentFilter, BM25ContentFilter
-from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
-
-async def main():
-    browser_config = BrowserConfig(
-        headless=True,  
-        verbose=True,
-    )
-    run_config = CrawlerRunConfig(
-        cache_mode=CacheMode.ENABLED,
-        markdown_generator=DefaultMarkdownGenerator(
-            content_filter=PruningContentFilter(threshold=0.48, threshold_type="fixed", min_word_threshold=0)
-        ),
-        # markdown_generator=DefaultMarkdownGenerator(
-        #     content_filter=BM25ContentFilter(user_query="WHEN_WE_FOCUS_BASED_ON_A_USER_QUERY", bm25_threshold=1.0)
-        # ),
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(
-            url="https://docs.micronaut.io/4.7.6/guide/",
-            config=run_config
-        )
-        print(len(result.markdown.raw_markdown))
-        print(len(result.markdown.fit_markdown))
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-</details>
-
-<details>
-<summary>🖥️ <strong>Executing JavaScript & Extract Structured Data without LLMs</strong></summary>
-
-```python
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
-from crawl4ai import JsonCssExtractionStrategy
-import json
-
-async def main():
-    schema = {
-    "name": "KidoCode Courses",
-    "baseSelector": "section.charge-methodology .w-tab-content > div",
-    "fields": [
-        {
-            "name": "section_title",
-            "selector": "h3.heading-50",
-            "type": "text",
-        },
-        {
-            "name": "section_description",
-            "selector": ".charge-content",
-            "type": "text",
-        },
-        {
-            "name": "course_name",
-            "selector": ".text-block-93",
-            "type": "text",
-        },
-        {
-            "name": "course_description",
-            "selector": ".course-content-text",
-            "type": "text",
-        },
-        {
-            "name": "course_icon",
-            "selector": ".image-92",
-            "type": "attribute",
-            "attribute": "src"
-        }
-    }
-}
-
-    extraction_strategy = JsonCssExtractionStrategy(schema, verbose=True)
-
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True
-    )
-    run_config = CrawlerRunConfig(
-        extraction_strategy=extraction_strategy,
-        js_code=["""(async () => {const tabs = document.querySelectorAll("section.charge-methodology .tabs-menu-3 > div");for(let tab of tabs) {tab.scrollIntoView();tab.click();await new Promise(r => setTimeout(r, 500));}})();"""],
-        cache_mode=CacheMode.BYPASS
-    )
-        
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        
-        result = await crawler.arun(
-            url="https://www.kidocode.com/degrees/technology",
-            config=run_config
-        )
-
-        companies = json.loads(result.extracted_content)
-        print(f"Successfully extracted {len(companies)} companies")
-        print(json.dumps(companies[0], indent=2))
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-</details>
-
-<details>
-<summary>📚 <strong>Extracting Structured Data with LLMs</strong></summary>
-
-```python
-import os
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode, LLMConfig
-from crawl4ai import LLMExtractionStrategy
-from pydantic import BaseModel, Field
-
-class OpenAIModelFee(BaseModel):
-    model_name: str = Field(..., description="Name of the OpenAI model.")
-    input_fee: str = Field(..., description="Fee for input token for the OpenAI model.")
-    output_fee: str = Field(..., description="Fee for output token for the OpenAI model.")
-
-async def main():
-    browser_config = BrowserConfig(verbose=True)
-    run_config = CrawlerRunConfig(
-        word_count_threshold=1,
-        extraction_strategy=LLMExtractionStrategy(
-            # Here you can use any provider that Litellm library supports, for instance: ollama/qwen2
-            # provider="ollama/qwen2", api_token="no-token", 
-            llm_config = LLMConfig(provider="openai/gpt-4o", api_token=os.getenv('OPENAI_API_KEY')), 
-            schema=OpenAIModelFee.schema(),
-            extraction_type="schema",
-            instruction="""From the crawled content, extract all mentioned model names along with their fees for input and output tokens. 
-            Do not miss any models in the entire content. One extracted model JSON format should look like this: 
-            {"model_name": "GPT-4", "input_fee": "US$10.00 / 1M tokens", "output_fee": "US$30.00 / 1M tokens"}."""
-        ),            
-        cache_mode=CacheMode.BYPASS,
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(
-            url='https://openai.com/api/pricing/',
-            config=run_config
-        )
-        print(result.extracted_content)
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-</details>
-
-<details>
-<summary>🤖 <strong>Using Your own Browser with Custom User Profile</strong></summary>
-
-```python
-import os, sys
-from pathlib import Path
-import asyncio, time
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
-
-async def test_news_crawl():
-    # Create a persistent user data directory
-    user_data_dir = os.path.join(Path.home(), ".crawl4ai", "browser_profile")
-    os.makedirs(user_data_dir, exist_ok=True)
-
-    browser_config = BrowserConfig(
-        verbose=True,
-        headless=True,
-        user_data_dir=user_data_dir,
-        use_persistent_context=True,
-    )
-    run_config = CrawlerRunConfig(
-        cache_mode=CacheMode.BYPASS
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        url = "ADDRESS_OF_A_CHALLENGING_WEBSITE"
-        
-        result = await crawler.arun(
-            url,
-            config=run_config,
-            magic=True,
-        )
-        
-        print(f"Successfully crawled {url}")
-        print(f"Content length: {len(result.markdown)}")
-```
-
-</details>
-
-## ✨ Recent Updates
-
-### Version 0.7.0 Release Highlights - The Adaptive Intelligence Update
-
- **🧠 Adaptive Crawling**: Your crawler now learns and adapts to website patterns automatically:
-  ```python
-  config = AdaptiveConfig(
-      confidence_threshold=0.7, # Min confidence to stop crawling
-      max_depth=5, # Maximum crawl depth
-      max_pages=20, # Maximum number of pages to crawl
-      strategy="statistical"
-  )
-  
-  async with AsyncWebCrawler() as crawler:
-      adaptive_crawler = AdaptiveCrawler(crawler, config)
-      state = await adaptive_crawler.digest(
-          start_url="https://news.example.com",
-          query="latest news content"
-      )
-  # Crawler learns patterns and improves extraction over time
-  ```
-
- **🌊 Virtual Scroll Support**: Complete content extraction from infinite scroll pages:
-  ```python
-  scroll_config = VirtualScrollConfig(
-      container_selector="[data-testid='feed']",
-      scroll_count=20,
-      scroll_by="container_height",
-      wait_after_scroll=1.0
-  )
-  
-  result = await crawler.arun(url, config=CrawlerRunConfig(
-      virtual_scroll_config=scroll_config
-  ))
-  ```
-
- **🔗 Intelligent Link Analysis**: 3-layer scoring system for smart link prioritization:
-  ```python
-  link_config = LinkPreviewConfig(
-      query="machine learning tutorials",
-      score_threshold=0.3,
-      concurrent_requests=10
-  )
-  
-  result = await crawler.arun(url, config=CrawlerRunConfig(
-      link_preview_config=link_config,
-      score_links=True
-  ))
-  # Links ranked by relevance and quality
-  ```
-
- **🎣 Async URL Seeder**: Discover thousands of URLs in seconds:
-  ```python
-  seeder = AsyncUrlSeeder(SeedingConfig(
-      source="sitemap+cc",
-      pattern="*/blog/*",
-      query="python tutorials",
-      score_threshold=0.4
-  ))
-  
-  urls = await seeder.discover("https://example.com")
-  ```
-
- **⚡ Performance Boost**: Up to 3x faster with optimized resource handling and memory efficiency
-
-Read the full details in our [0.7.0 Release Notes](https://docs.crawl4ai.com/blog/release-v0.7.0) or check the [CHANGELOG](https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md).
-
-## 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):
-  ```bash
-  pip install -U crawl4ai
-  ```
-
- Install pre-release versions:
-  ```bash
-  pip install crawl4ai --pre
-  ```
-
- Install specific version:
-  ```bash
-  pip install crawl4ai==0.4.3b1
-  ```
-
-#### 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](https://docs.crawl4ai.com/).
-
-To check our development plans and upcoming features, visit our [Roadmap](https://github.com/unclecode/crawl4ai/blob/main/ROADMAP.md).
-
-<details>
-<summary>📈 <strong>Development TODOs</strong></summary>
-
- [x] 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
-
-</details>
-
-## 🤝 Contributing 
-
-We welcome contributions from the open-source community. Check out our [contribution guidelines](https://github.com/unclecode/crawl4ai/blob/main/CONTRIBUTORS.md) 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](https://github.com/unclecode/crawl4ai/blob/main/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:
-
-| Theme | Badge |
-|-------|-------|
-| **Disco Theme (Animated)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-disco.svg" alt="Powered by Crawl4AI" width="200"/></a> |
-| **Night Theme (Dark with Neon)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-night.svg" alt="Powered by Crawl4AI" width="200"/></a> |
-| **Dark Theme (Classic)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-dark.svg" alt="Powered by Crawl4AI" width="200"/></a> |
-| **Light Theme (Classic)** | <a href="https://github.com/unclecode/crawl4ai"><img src="./docs/assets/powered-by-light.svg" alt="Powered by Crawl4AI" width="200"/></a> |
- 
-
-HTML code for adding the badges:
-```html
-<!-- Disco Theme (Animated) -->
-<a href="https://github.com/unclecode/crawl4ai">
-  <img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-disco.svg" alt="Powered by Crawl4AI" width="200"/>
-</a>
-
-<!-- Night Theme (Dark with Neon) -->
-<a href="https://github.com/unclecode/crawl4ai">
-  <img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-night.svg" alt="Powered by Crawl4AI" width="200"/>
-</a>
-
-<!-- Dark Theme (Classic) -->
-<a href="https://github.com/unclecode/crawl4ai">
-  <img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-dark.svg" alt="Powered by Crawl4AI" width="200"/>
-</a>
-
-<!-- Light Theme (Classic) -->
-<a href="https://github.com/unclecode/crawl4ai">
-  <img src="https://raw.githubusercontent.com/unclecode/crawl4ai/main/docs/assets/powered-by-light.svg" alt="Powered by Crawl4AI" width="200"/>
-</a>
-
-<!-- Simple Shield Badge -->
-<a href="https://github.com/unclecode/crawl4ai">
-  <img src="https://img.shields.io/badge/Powered%20by-Crawl4AI-blue?style=flat-square" alt="Powered by Crawl4AI"/>
-</a>
-```
-
-#### 2. Text Attribution
-Add this line to your documentation:
-```
-This project uses Crawl4AI (https://github.com/unclecode/crawl4ai) for web data extraction.
-```
-
-## 📚 Citation
-
-If you use Crawl4AI in your research or project, please cite:
-
-```bibtex
-@software{crawl4ai2024,
-  author = {UncleCode},
-  title = {Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper},
-  year = {2024},
-  publisher = {GitHub},
-  journal = {GitHub Repository},
-  howpublished = {\url{https://github.com/unclecode/crawl4ai}},
-  commit = {Please use the commit hash you're working with}
-}
-```
-
-Text citation format:
-```
-UncleCode. (2024). Crawl4AI: Open-source LLM Friendly Web Crawler & Scraper [Computer software]. 
-GitHub. https://github.com/unclecode/crawl4ai
-```
-
-## 📧 Contact 
-
-For questions, suggestions, or feedback, feel free to reach out:
-
- GitHub: [unclecode](https://github.com/unclecode)
- Twitter: [@unclecode](https://twitter.com/unclecode)
- Website: [crawl4ai.com](https://crawl4ai.com)
-
-Happy Crawling! 🕸️🚀
-
-## 💖 Support Crawl4AI
-
-> 🎉 **Sponsorship Program Just Launched!** Be among the first 50 **Founding Sponsors** and get permanent recognition in our Hall of Fame!
-
-Crawl4AI is the #1 trending open-source web crawler with 51K+ stars. Your support ensures we stay independent, innovative, and free forever.
-
-<div align="center">
-
-[![Become a Sponsor](https://img.shields.io/badge/Become%20a%20Sponsor-pink?style=for-the-badge&logo=github-sponsors&logoColor=white)](https://github.com/sponsors/unclecode)
-[![Current Sponsors](https://img.shields.io/github/sponsors/unclecode?style=for-the-badge&logo=github&label=Current%20Sponsors&color=green)](https://github.com/sponsors/unclecode)
-
-</div>
-
-### 🤝 Sponsorship Tiers
-
- **🌱 Believer ($5/mo)**: Join the movement for data democratization
- **🚀 Builder ($50/mo)**: Get priority support and early feature access  
- **💼 Growing Team ($500/mo)**: Bi-weekly syncs and optimization help
- **🏢 Data Infrastructure Partner ($2000/mo)**: Full partnership with dedicated support
-
-**Why sponsor?** Every tier includes real benefits. No more rate-limited APIs. Own your data pipeline. Build data sovereignty together.
-
-[View All Tiers & Benefits →](https://github.com/sponsors/unclecode)
-
-### 🏆 Our Sponsors
-
-#### 👑 Founding Sponsors (First 50)
-*Be part of history - [Become a Founding Sponsor](https://github.com/sponsors/unclecode)*
-
-<!-- Founding sponsors will be permanently recognized here -->
-
-#### Current Sponsors
-Thank you to all our sponsors who make this project possible!
-
-<!-- Sponsors will be automatically added here -->
-
-## 🗾 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.
-
-<details>
-<summary>🔑 <strong>Key Opportunities</strong></summary>
- 
- **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.  
-
-</details>
-
-<details>
-<summary>🚀 <strong>Development Pathway</strong></summary>
-
-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](./MISSION.md).
-</details>
-
-## Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=unclecode/crawl4ai&type=Date)](https://star-history.com/#unclecode/crawl4ai&Date)
--- a/README.md
+++ b/README.md
@@ -10,7 +10,6 @@
 [![PyPI version](https://badge.fury.io/py/crawl4ai.svg)](https://badge.fury.io/py/crawl4ai)
 [![Python Version](https://img.shields.io/pypi/pyversions/crawl4ai)](https://pypi.org/project/crawl4ai/)
 [![Downloads](https://static.pepy.tech/badge/crawl4ai/month)](https://pepy.tech/project/crawl4ai)
-[![GitHub Sponsors](https://img.shields.io/github/sponsors/unclecode?style=flat&logo=GitHub-Sponsors&label=Sponsors&color=pink)](https://github.com/sponsors/unclecode)

 <p align="center">
    <a href="https://x.com/crawl4ai">
@@ -25,33 +24,32 @@
  </p>
 </div>

-Crawl4AI turns the web into clean, LLM ready Markdown for RAG, agents, and data pipelines. Fast, controllable, battle tested by a 50k+ star community.
+Crawl4AI is the #1 trending GitHub repository, actively maintained by a vibrant community. It delivers blazing-fast, AI-ready web crawling tailored for LLMs, AI agents, and data pipelines. Open source, flexible, and built for real-time performance, Crawl4AI empowers developers with unmatched speed, precision, and deployment ease.  

 [✨ Check out latest update v0.7.0](#-recent-updates)

-✨ New in v0.7.0, Adaptive Crawling, Virtual Scroll, Link Preview scoring, Async URL Seeder, big performance gains. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.0.md)
+🎉 **Version 0.7.0 is now available!** The Adaptive Intelligence Update introduces groundbreaking features: Adaptive Crawling that learns website patterns, Virtual Scroll support for infinite pages, intelligent Link Preview with 3-layer scoring, Async URL Seeder for massive discovery, and significant performance improvements. [Read the release notes →](https://docs.crawl4ai.com/blog/release-v0.7.0)

 <details>
-  <summary>🤓 <strong>My Personal Story</strong></summary>
+<summary>🤓 <strong>My Personal Story</strong></summary>

-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.
+My journey with computers started in childhood when my dad, a computer scientist, introduced me to an Amstrad computer. Those early days sparked a fascination with technology, leading me to pursue computer science and specialize in NLP during my postgraduate studies. It was during this time that I first delved into web crawling, building tools to help researchers organize papers and extract information from publications a challenging yet rewarding experience that honed my skills in data extraction.

-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.
+Fast forward to 2023, I was working on a tool for a project and needed a crawler to convert a webpage into markdown. While exploring solutions, I found one that claimed to be open-source but required creating an account and generating an API token. Worse, it turned out to be a SaaS model charging $16, and its quality didn’t meet my standards. Frustrated, I realized this was a deeper problem. That frustration turned into turbo anger mode, and I decided to build my own solution. In just a few days, I created Crawl4AI. To my surprise, it went viral, earning thousands of GitHub stars and resonating with a global community.

-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.
+I made Crawl4AI open-source for two reasons. First, it’s my way of giving back to the open-source community that has supported me throughout my career. Second, I believe data should be accessible to everyone, not locked behind paywalls or monopolized by a few. Open access to data lays the foundation for the democratization of AI, a vision where individuals can train their own models and take ownership of their information. This library is the first step in a larger journey to create the best open-source data extraction and generation tool the world has ever seen, built collaboratively by a passionate community.
+
+Thank you to everyone who has supported this project, used it, and shared feedback. Your encouragement motivates me to dream even bigger. Join us, file issues, submit PRs, or spread the word. Together, we can build a tool that truly empowers people to access their own data and reshape the future of AI.
 </details>

+## 🧐 Why Crawl4AI?

-<details>
-  <summary>Why developers pick Crawl4AI</summary>
-
- **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
-</details>
-
+1. **Built for LLMs**: Creates smart, concise Markdown optimized for RAG and fine-tuning applications.  
+2. **Lightning Fast**: Delivers results 6x faster with real-time, cost-efficient performance.  
+3. **Flexible Browser Control**: Offers session management, proxies, and custom hooks for seamless data access.  
+4. **Heuristic Intelligence**: Uses advanced algorithms for efficient extraction, reducing reliance on costly models.  
+5. **Open Source & Deployable**: Fully open-source with no API keys—ready for Docker and cloud integration.  
+6. **Thriving Community**: Actively maintained by a vibrant community and the #1 trending GitHub repository.

 ## 🚀 Quick Start 

@@ -103,33 +101,6 @@ crwl https://docs.crawl4ai.com --deep-crawl bfs --max-pages 10
 crwl https://www.example.com/products -q "Extract all product prices"
 ```

-## 💖 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.
-
-<div align="">
-  
-[![Become a Sponsor](https://img.shields.io/badge/Become%20a%20Sponsor-pink?style=for-the-badge&logo=github-sponsors&logoColor=white)](https://github.com/sponsors/unclecode)  
-[![Current Sponsors](https://img.shields.io/github/sponsors/unclecode?style=for-the-badge&logo=github&label=Current%20Sponsors&color=green)](https://github.com/sponsors/unclecode)
-
-</div>
-
-### 🤝 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 - see [SPONSORS.md](SPONSORS.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.
-
-[See All Tiers & Benefits →](https://github.com/sponsors/unclecode)
-
-
 ## ✨ Features 

 <details>
@@ -309,6 +280,12 @@ docker run -d -p 11235:11235 --name crawl4ai --shm-size=1g unclecode/crawl4ai:0.
 # Visit the playground at http://localhost:11235/playground
 ```

+For complete documentation, see our [Docker Deployment Guide](https://docs.crawl4ai.com/core/docker-deployment/).
+
+</details>
+
+---
+
 ### Quick Test

 Run a quick test (works for both Docker options):
@@ -339,11 +316,10 @@ For more examples, see our [Docker Examples](https://github.com/unclecode/crawl4

 </details>

---

 ## 🔬 Advanced Usage Examples 🔬

-You can check the project structure in the directory [docs/examples](https://github.com/unclecode/crawl4ai/tree/main/docs/examples). Over there, you can find a variety of examples; here, some popular examples are shared.
+You can check the project structure in the directory [https://github.com/unclecode/crawl4ai/docs/examples](docs/examples). Over there, you can find a variety of examples; here, some popular examples are shared.

 <details>
 <summary>📝 <strong>Heuristic Markdown Generation with Clean and Fit Markdown</strong></summary>
@@ -502,7 +478,7 @@ if __name__ == "__main__":
 </details>

 <details>
-<summary>🤖 <strong>Using Your own Browser with Custom User Profile</strong></summary>
+<summary>🤖 <strong>Using You own Browser with Custom User Profile</strong></summary>

 ```python
 import os, sys
@@ -547,18 +523,15 @@ async def test_news_crawl():
 - **🧠 Adaptive Crawling**: Your crawler now learns and adapts to website patterns automatically:
  ```python
  config = AdaptiveConfig(
-      confidence_threshold=0.7, # Min confidence to stop crawling
-      max_depth=5, # Maximum crawl depth
-      max_pages=20, # Maximum number of pages to crawl
-      strategy="statistical"
+      confidence_threshold=0.7,
+      max_history=100,
+      learning_rate=0.2
  )
  
-  async with AsyncWebCrawler() as crawler:
-      adaptive_crawler = AdaptiveCrawler(crawler, config)
-      state = await adaptive_crawler.digest(
-          start_url="https://news.example.com",
-          query="latest news content"
-      )
+  result = await crawler.arun(
+      "https://news.example.com",
+      config=CrawlerRunConfig(adaptive_config=config)
+  )
  # Crawler learns patterns and improves extraction over time
  ```

@@ -607,12 +580,97 @@ async def test_news_crawl():

 Read the full details in our [0.7.0 Release Notes](https://docs.crawl4ai.com/blog/release-v0.7.0) or check the [CHANGELOG](https://github.com/unclecode/crawl4ai/blob/main/CHANGELOG.md).

+### Previous Version: 0.6.0 Release Highlights
+
+- **🌎 World-aware Crawling**: Set geolocation, language, and timezone for authentic locale-specific content:
+  ```python
+    crun_cfg = CrawlerRunConfig(
+        url="https://browserleaks.com/geo",          # test page that shows your location
+        locale="en-US",                              # Accept-Language & UI locale
+        timezone_id="America/Los_Angeles",           # JS Date()/Intl timezone
+        geolocation=GeolocationConfig(                 # override GPS coords
+            latitude=34.0522,
+            longitude=-118.2437,
+            accuracy=10.0,
+        )
+    )
+  ```
+
+- **📊 Table-to-DataFrame Extraction**: Extract HTML tables directly to CSV or pandas DataFrames:
+  ```python
+    crawler = AsyncWebCrawler(config=browser_config)
+    await crawler.start()
+
+    try:
+        # Set up scraping parameters
+        crawl_config = CrawlerRunConfig(
+            table_score_threshold=8,  # Strict table detection
+        )
+
+        # Execute market data extraction
+        results: List[CrawlResult] = await crawler.arun(
+            url="https://coinmarketcap.com/?page=1", config=crawl_config
+        )
+
+        # Process results
+        raw_df = pd.DataFrame()
+        for result in results:
+            if result.success and result.media["tables"]:
+                raw_df = pd.DataFrame(
+                    result.media["tables"][0]["rows"],
+                    columns=result.media["tables"][0]["headers"],
+                )
+                break
+        print(raw_df.head())
+
+    finally:
+        await crawler.stop()
+  ```
+
+- **🚀 Browser Pooling**: Pages launch hot with pre-warmed browser instances for lower latency and memory usage
+
+- **🕸️ Network and Console Capture**: Full traffic logs and MHTML snapshots for debugging:
+  ```python
+  crawler_config = CrawlerRunConfig(
+      capture_network=True,
+      capture_console=True,
+      mhtml=True
+  )
+  ```
+
+- **🔌 MCP Integration**: Connect to AI tools like Claude Code through the Model Context Protocol
+  ```bash
+  # Add Crawl4AI to Claude Code
+  claude mcp add --transport sse c4ai-sse http://localhost:11235/mcp/sse
+  ```
+
+- **🖥️ Interactive Playground**: Test configurations and generate API requests with the built-in web interface at `http://localhost:11235//playground`
+
+- **🐳 Revamped Docker Deployment**: Streamlined multi-architecture Docker image with improved resource efficiency
+
+- **📱 Multi-stage Build System**: Optimized Dockerfile with platform-specific performance enhancements
+
+
+### Previous Version: 0.5.0 Major Release Highlights
+
+-   **🚀 Deep Crawling System**: Explore websites beyond initial URLs with BFS, DFS, and BestFirst strategies
+-   **⚡ Memory-Adaptive Dispatcher**: Dynamically adjusts concurrency based on system memory
+-   **🔄 Multiple Crawling Strategies**: Browser-based and lightweight HTTP-only crawlers
+-   **💻 Command-Line Interface**: New `crwl` CLI provides convenient terminal access
+-   **👤 Browser Profiler**: Create and manage persistent browser profiles
+-   **🧠 Crawl4AI Coding Assistant**: AI-powered coding assistant
+-   **🏎️ LXML Scraping Mode**: Fast HTML parsing using the `lxml` library
+-   **🌐 Proxy Rotation**: Built-in support for proxy switching
+-   **🤖 LLM Content Filter**: Intelligent markdown generation using LLMs
+-   **📄 PDF Processing**: Extract text, images, and metadata from PDF files
+
+Read the full details in our [0.5.0 Release Notes](https://docs.crawl4ai.com/blog/releases/0.5.0.html).
+
 ## Version Numbering in Crawl4AI

 Crawl4AI follows standard Python version numbering conventions (PEP 440) to help users understand the stability and features of each release.

-<details>
-<summary>📈 <strong>Version Numbers Explained</strong></summary>
+### Version Numbers Explained

 Our version numbers follow this pattern: `MAJOR.MINOR.PATCH` (e.g., 0.4.3)

@@ -649,8 +707,6 @@ We use pre-releases to:

 For production environments, we recommend using the stable version. For testing new features, you can opt-in to pre-releases using the `--pre` flag.

-</details>
-
 ## 📖 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!
@@ -663,16 +719,16 @@ To check our development plans and upcoming features, visit our [Roadmap](https:
 <summary>📈 <strong>Development TODOs</strong></summary>

 - [x] 0. Graph Crawler: Smart website traversal using graph search algorithms for comprehensive nested page extraction
- [x] 1. Question-Based Crawler: Natural language driven web discovery and content extraction
- [x] 2. Knowledge-Optimal Crawler: Smart crawling that maximizes knowledge while minimizing data extraction
- [x] 3. Agentic Crawler: Autonomous system for complex multi-step crawling operations
- [x] 4. Automated Schema Generator: Convert natural language to extraction schemas
- [x] 5. Domain-Specific Scrapers: Pre-configured extractors for common platforms (academic, e-commerce)
- [x] 6. Web Embedding Index: Semantic search infrastructure for crawled content
- [x] 7. Interactive Playground: Web UI for testing, comparing strategies with AI assistance
- [x] 8. Performance Monitor: Real-time insights into crawler operations
+- [ ] 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
- [x] 10. Sponsorship Program: Structured support system with tiered benefits
+- [ ] 10. Sponsorship Program: Structured support system with tiered benefits
 - [ ] 11. Educational Content: "How to Crawl" video series and interactive tutorials

 </details>
@@ -687,13 +743,12 @@ 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](https://github.com/unclecode/crawl4ai/blob/main/LICENSE) file for details.
+This project is licensed under the Apache License 2.0 with a required attribution clause. See the [Apache 2.0 License](https://github.com/unclecode/crawl4ai/blob/main/LICENSE) file for details.

 ### Attribution Requirements
 When using Crawl4AI, you must include one of the following attribution methods:

-<details>
-<summary>📈 <strong>1. Badge Attribution (Recommended)</strong></summary>
+#### 1. Badge Attribution (Recommended)
 Add one of these badges to your README, documentation, or website:

 | Theme | Badge |
@@ -732,15 +787,11 @@ HTML code for adding the badges:
 </a>
 ```

-</details>
-
-<details>
-<summary>📖 <strong>2. Text Attribution</strong></summary>
+#### 2. Text Attribution
 Add this line to your documentation:
 ```
 This project uses Crawl4AI (https://github.com/unclecode/crawl4ai) for web data extraction.
 ```
-</details>

 ## 📚 Citation

--- a/SPONSORS.md
+++ b/SPONSORS.md
@@ -1,65 +0,0 @@
-# 💖 Sponsors & Supporters
-
-Thank you to everyone supporting Crawl4AI! Your sponsorship helps keep this project open-source and actively maintained.
-
-## 👑 Founding Sponsors
-*The first 50 sponsors who believed in our vision - permanently recognized*
-
-<!-- Founding sponsors will be listed here with special recognition -->
-🎉 **Become a Founding Sponsor!** Only [X/50] spots remaining! [Join now →](https://github.com/sponsors/unclecode)
-
---
-
-## 🏢 Data Infrastructure Partners ($2000/month)
-*These organizations are building their data sovereignty with Crawl4AI at the core*
-
-<!-- Data Infrastructure Partners will be listed here -->
-*Be the first Data Infrastructure Partner! [Join us →](https://github.com/sponsors/unclecode)*
-
---
-
-## 💼 Growing Teams ($500/month)
-*Teams scaling their data extraction with Crawl4AI*
-
-<!-- Growing Teams will be listed here -->
-*Your team could be here! [Become a sponsor →](https://github.com/sponsors/unclecode)*
-
---
-
-## 🚀 Builders ($50/month)
-*Developers and entrepreneurs building with Crawl4AI*
-
-<!-- Builders will be listed here -->
-*Join the builders! [Start sponsoring →](https://github.com/sponsors/unclecode)*
-
---
-
-## 🌱 Believers ($5/month)
-*The community supporting data democratization*
-
-<!-- Believers will be listed here -->
-*Thank you to all our community believers!*
-
---
-
-## 🤝 Want to Sponsor?
-
-Crawl4AI is the #1 trending open-source web crawler. We're building the future of data extraction - where organizations own their data pipelines instead of relying on rate-limited APIs.
-
-### Available Sponsorship Tiers:
- **🌱 Believer** ($5/mo) - Support the movement
- **🚀 Builder** ($50/mo) - Priority support & early access
- **💼 Growing Team** ($500/mo) - Bi-weekly syncs & optimization
- **🏢 Data Infrastructure Partner** ($2000/mo) - Full partnership & dedicated support
-
-[View all tiers and benefits →](https://github.com/sponsors/unclecode)
-
-### Enterprise & Custom Partnerships
-
-Building data extraction at scale? Need dedicated support or infrastructure? Let's talk about a custom partnership.
-
-📧 Contact: [hello@crawl4ai.com](mailto:hello@crawl4ai.com) | 📅 [Schedule a call](https://calendar.app.google/rEpvi2UBgUQjWHfJ9)
-
---
-
-*This list is updated regularly. Sponsors at $50+ tiers can submit their logos via [hello@crawl4ai.com](mailto:hello@crawl4ai.com)*
--- a/crawl4ai/init.py
+++ b/crawl4ai/init.py
@@ -3,12 +3,12 @@ import warnings

 from .async_webcrawler import AsyncWebCrawler, CacheMode
 # MODIFIED: Add SeedingConfig and VirtualScrollConfig here
-from .async_configs import BrowserConfig, CrawlerRunConfig, HTTPCrawlerConfig, LLMConfig, ProxyConfig, GeolocationConfig, SeedingConfig, VirtualScrollConfig, LinkPreviewConfig, MatchMode
+from .async_configs import BrowserConfig, CrawlerRunConfig, HTTPCrawlerConfig, LLMConfig, ProxyConfig, GeolocationConfig, SeedingConfig, VirtualScrollConfig

 from .content_scraping_strategy import (
    ContentScrapingStrategy,
+    WebScrapingStrategy,
    LXMLWebScrapingStrategy,
-    WebScrapingStrategy,  # Backward compatibility alias
 )
 from .async_logger import (
    AsyncLoggerBase,
@@ -88,13 +88,6 @@ from .script import (
    ErrorDetail
 )

-# Browser Adapters
-from .browser_adapter import (
-    BrowserAdapter,
-    PlaywrightAdapter,
-    UndetectedAdapter
-)
-
 from .utils import (
    start_colab_display_server,
    setup_colab_environment
@@ -139,7 +132,6 @@ __all__ = [
    "CrawlResult",
    "CrawlerHub",
    "CacheMode",
-    "MatchMode",
    "ContentScrapingStrategy",
    "WebScrapingStrategy",
    "LXMLWebScrapingStrategy",
@@ -181,11 +173,6 @@ __all__ = [
    "CompilationResult",
    "ValidationResult",
    "ErrorDetail",
-    # Browser Adapters
-    "BrowserAdapter",
-    "PlaywrightAdapter", 
-    "UndetectedAdapter",
-    "LinkPreviewConfig"
 ]


--- a/crawl4ai/version.py
+++ b/crawl4ai/version.py
@@ -1,7 +1,7 @@
 # crawl4ai/__version__.py

 # This is the version that will be used for stable releases
-__version__ = "0.7.3"
+__version__ = "0.7.0"

 # For nightly builds, this gets set during build process
 __nightly_version__ = None
--- a/crawl4ai/async_configs.py
+++ b/crawl4ai/async_configs.py
@@ -18,24 +18,17 @@ from .extraction_strategy import ExtractionStrategy, LLMExtractionStrategy
 from .chunking_strategy import ChunkingStrategy, RegexChunking

 from .markdown_generation_strategy import MarkdownGenerationStrategy, DefaultMarkdownGenerator
-from .content_scraping_strategy import ContentScrapingStrategy, LXMLWebScrapingStrategy
+from .content_scraping_strategy import ContentScrapingStrategy, WebScrapingStrategy, LXMLWebScrapingStrategy
 from .deep_crawling import DeepCrawlStrategy

 from .cache_context import CacheMode
 from .proxy_strategy import ProxyRotationStrategy

-from typing import Union, List, Callable
+from typing import Union, List
 import inspect
 from typing import Any, Dict, Optional
 from enum import Enum

-# Type alias for URL matching
-UrlMatcher = Union[str, Callable[[str], bool], List[Union[str, Callable[[str], bool]]]]
-
-class MatchMode(Enum):
-    OR = "or"
-    AND = "and"
-
 # from .proxy_strategy import ProxyConfig


@@ -390,8 +383,6 @@ class BrowserConfig:
        light_mode (bool): Disables certain background features for performance gains. Default: False.
        extra_args (list): Additional command-line arguments passed to the browser.
                           Default: [].
-        enable_stealth (bool): If True, applies playwright-stealth to bypass basic bot detection.
-                              Cannot be used with use_undetected browser mode. Default: False.
    """

    def __init__(
@@ -432,7 +423,6 @@ class BrowserConfig:
        extra_args: list = None,
        debugging_port: int = 9222,
        host: str = "localhost",
-        enable_stealth: bool = False,
    ):
        self.browser_type = browser_type
        self.headless = headless 
@@ -473,7 +463,6 @@ class BrowserConfig:
        self.verbose = verbose
        self.debugging_port = debugging_port
        self.host = host
-        self.enable_stealth = enable_stealth

        fa_user_agenr_generator = ValidUAGenerator()
        if self.user_agent_mode == "random":
@@ -505,13 +494,6 @@ class BrowserConfig:
        # If persistent context is requested, ensure managed browser is enabled
        if self.use_persistent_context:
            self.use_managed_browser = True
-            
-        # Validate stealth configuration
-        if self.enable_stealth and self.use_managed_browser and self.browser_mode == "builtin":
-            raise ValueError(
-                "enable_stealth cannot be used with browser_mode='builtin'. "
-                "Stealth mode requires a dedicated browser instance."
-            )

    @staticmethod
    def from_kwargs(kwargs: dict) -> "BrowserConfig":
@@ -548,7 +530,6 @@ class BrowserConfig:
            extra_args=kwargs.get("extra_args", []),
            debugging_port=kwargs.get("debugging_port", 9222),
            host=kwargs.get("host", "localhost"),
-            enable_stealth=kwargs.get("enable_stealth", False),
        )

    def to_dict(self):
@@ -583,7 +564,6 @@ class BrowserConfig:
            "verbose": self.verbose,
            "debugging_port": self.debugging_port,
            "host": self.host,
-            "enable_stealth": self.enable_stealth,
        }

                
@@ -882,7 +862,7 @@ class CrawlerRunConfig():
        parser_type (str): Type of parser to use for HTML parsing.
                           Default: "lxml".
        scraping_strategy (ContentScrapingStrategy): Scraping strategy to use.
-                           Default: LXMLWebScrapingStrategy.
+                           Default: WebScrapingStrategy.
        proxy_config (ProxyConfig or dict or None): Detailed proxy configuration, e.g. {"server": "...", "username": "..."}.
                                     If None, no additional proxy config. Default: None.

@@ -1133,9 +1113,6 @@ class CrawlerRunConfig():
        link_preview_config: Union[LinkPreviewConfig, Dict[str, Any]] = None,
        # Virtual Scroll Parameters
        virtual_scroll_config: Union[VirtualScrollConfig, Dict[str, Any]] = None,
-        # URL Matching Parameters
-        url_matcher: Optional[UrlMatcher] = None,
-        match_mode: MatchMode = MatchMode.OR,
        # Experimental Parameters
        experimental: Dict[str, Any] = None,
    ):
@@ -1289,10 +1266,6 @@ class CrawlerRunConfig():
        else:
            raise ValueError("virtual_scroll_config must be VirtualScrollConfig object or dict")
        
-        # URL Matching Parameters
-        self.url_matcher = url_matcher
-        self.match_mode = match_mode
-        
        # Experimental Parameters
        self.experimental = experimental or {}
        
@@ -1348,51 +1321,6 @@ class CrawlerRunConfig():
            if "compilation error" not in str(e).lower():
                raise ValueError(f"Failed to compile C4A script: {str(e)}")
            raise
-    
-    def is_match(self, url: str) -> bool:
-        """Check if this config matches the given URL.
-        
-        Args:
-            url: The URL to check against this config's matcher
-            
-        Returns:
-            bool: True if this config should be used for the URL or if no matcher is set.
-        """
-        if self.url_matcher is None:
-            return True
-            
-        if callable(self.url_matcher):
-            # Single function matcher
-            return self.url_matcher(url)
-        
-        elif isinstance(self.url_matcher, str):
-            # Single pattern string
-            from fnmatch import fnmatch
-            return fnmatch(url, self.url_matcher)
-        
-        elif isinstance(self.url_matcher, list):
-            # List of mixed matchers
-            if not self.url_matcher:  # Empty list
-                return False
-                
-            results = []
-            for matcher in self.url_matcher:
-                if callable(matcher):
-                    results.append(matcher(url))
-                elif isinstance(matcher, str):
-                    from fnmatch import fnmatch
-                    results.append(fnmatch(url, matcher))
-                else:
-                    # Skip invalid matchers
-                    continue
-            
-            # Apply match mode logic
-            if self.match_mode == MatchMode.OR:
-                return any(results) if results else False
-            else:  # AND mode
-                return all(results) if results else False
-        
-        return False


    def __getattr__(self, name):
@@ -1515,9 +1443,6 @@ class CrawlerRunConfig():
            # Link Extraction Parameters
            link_preview_config=kwargs.get("link_preview_config"),
            url=kwargs.get("url"),
-            # URL Matching Parameters
-            url_matcher=kwargs.get("url_matcher"),
-            match_mode=kwargs.get("match_mode", MatchMode.OR),
            # Experimental Parameters 
            experimental=kwargs.get("experimental"),
        )
@@ -1615,8 +1540,6 @@ class CrawlerRunConfig():
            "deep_crawl_strategy": self.deep_crawl_strategy,
            "link_preview_config": self.link_preview_config.to_dict() if self.link_preview_config else None,
            "url": self.url,
-            "url_matcher": self.url_matcher,
-            "match_mode": self.match_mode,
            "experimental": self.experimental,
        }

--- a/crawl4ai/async_crawler_strategy.back.py
+++ b/crawl4ai/async_crawler_strategy.back.py
--- a/crawl4ai/async_crawler_strategy.py
+++ b/crawl4ai/async_crawler_strategy.py
@@ -12,6 +12,20 @@ from playwright.async_api import TimeoutError as PlaywrightTimeoutError
 from io import BytesIO
 from PIL import Image, ImageDraw, ImageFont
 import hashlib
+
+# Backward compatible stealth import
+try:
+    # Try new tf-playwright-stealth API (Stealth class)
+    from playwright_stealth import Stealth
+    STEALTH_NEW_API = True
+except ImportError:
+    try:
+        # Try old playwright-stealth API (stealth_async function)
+        from playwright_stealth import stealth_async
+        STEALTH_NEW_API = False
+    except ImportError:
+        # No stealth available
+        STEALTH_NEW_API = None
 import uuid
 from .js_snippet import load_js_script
 from .models import AsyncCrawlResponse
@@ -21,7 +35,6 @@ from .async_logger import AsyncLogger
 from .ssl_certificate import SSLCertificate
 from .user_agent_generator import ValidUAGenerator
 from .browser_manager import BrowserManager
-from .browser_adapter import BrowserAdapter, PlaywrightAdapter, UndetectedAdapter

 import aiofiles
 import aiohttp
@@ -32,6 +45,107 @@ from types import MappingProxyType
 import contextlib
 from functools import partial

+
+# Add StealthConfig class for backward compatibility and new features
+class StealthConfig:
+    """
+    Configuration class for stealth settings that works with tf-playwright-stealth.
+    This maintains backward compatibility while supporting all tf-playwright-stealth features.
+    """
+    def __init__(
+        self,
+        # Common settings
+        enabled: bool = True,
+        
+        # Core tf-playwright-stealth parameters (matching the actual library)
+        chrome_app: bool = True,
+        chrome_csi: bool = True,
+        chrome_load_times: bool = True,
+        chrome_runtime: bool = False,  # Note: library default is False
+        hairline: bool = True,
+        iframe_content_window: bool = True,
+        media_codecs: bool = True,
+        navigator_hardware_concurrency: bool = True,
+        navigator_languages: bool = True,
+        navigator_permissions: bool = True,
+        navigator_platform: bool = True,
+        navigator_plugins: bool = True,
+        navigator_user_agent: bool = True,
+        navigator_vendor: bool = True,
+        navigator_webdriver: bool = True,
+        sec_ch_ua: bool = True,
+        webgl_vendor: bool = True,
+        
+        # Override parameters
+        navigator_languages_override: tuple = ("en-US", "en"),
+        navigator_platform_override: str = "Win32",
+        navigator_user_agent_override: str = None,
+        navigator_vendor_override: str = None,
+        sec_ch_ua_override: str = None,
+        webgl_renderer_override: str = None,
+        webgl_vendor_override: str = None,
+        
+        # Advanced parameters
+        init_scripts_only: bool = False,
+        script_logging: bool = False,
+        
+        # Legacy parameters for backward compatibility
+        webdriver: bool = None,  # This will be mapped to navigator_webdriver
+        user_agent_override: bool = None,  # This will be mapped to navigator_user_agent
+        window_outerdimensions: bool = None,  # This parameter doesn't exist in tf-playwright-stealth
+    ):
+        self.enabled = enabled
+        
+        # Handle legacy parameter mapping for backward compatibility
+        if webdriver is not None:
+            navigator_webdriver = webdriver
+        if user_agent_override is not None:
+            navigator_user_agent = user_agent_override
+        
+        # Store all stealth options for the Stealth class - filter out None values
+        self.stealth_options = {
+            k: v for k, v in {
+                'chrome_app': chrome_app,
+                'chrome_csi': chrome_csi,
+                'chrome_load_times': chrome_load_times,
+                'chrome_runtime': chrome_runtime,
+                'hairline': hairline,
+                'iframe_content_window': iframe_content_window,
+                'media_codecs': media_codecs,
+                'navigator_hardware_concurrency': navigator_hardware_concurrency,
+                'navigator_languages': navigator_languages,
+                'navigator_permissions': navigator_permissions,
+                'navigator_platform': navigator_platform,
+                'navigator_plugins': navigator_plugins,
+                'navigator_user_agent': navigator_user_agent,
+                'navigator_vendor': navigator_vendor,
+                'navigator_webdriver': navigator_webdriver,
+                'sec_ch_ua': sec_ch_ua,
+                'webgl_vendor': webgl_vendor,
+                'navigator_languages_override': navigator_languages_override,
+                'navigator_platform_override': navigator_platform_override,
+                'navigator_user_agent_override': navigator_user_agent_override,
+                'navigator_vendor_override': navigator_vendor_override,
+                'sec_ch_ua_override': sec_ch_ua_override,
+                'webgl_renderer_override': webgl_renderer_override,
+                'webgl_vendor_override': webgl_vendor_override,
+                'init_scripts_only': init_scripts_only,
+                'script_logging': script_logging,
+            }.items() if v is not None
+        }
+    
+    @classmethod
+    def from_dict(cls, config_dict: dict) -> 'StealthConfig':
+        """Create StealthConfig from dictionary for easy configuration"""
+        return cls(**config_dict)
+    
+    def to_dict(self) -> dict:
+        """Convert to dictionary for serialization"""
+        return {
+            'enabled': self.enabled,
+            **self.stealth_options
+        }
+
 class AsyncCrawlerStrategy(ABC):
    """
    Abstract base class for crawler strategies.
@@ -40,7 +154,7 @@ class AsyncCrawlerStrategy(ABC):

    @abstractmethod
    async def crawl(self, url: str, **kwargs) -> AsyncCrawlResponse:
-        pass  # 4 + 3
+        pass # 4 + 3

 class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
    """
@@ -72,7 +186,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
    """

    def __init__(
-        self, browser_config: BrowserConfig = None, logger: AsyncLogger = None, browser_adapter: BrowserAdapter = None, **kwargs
+        self, browser_config: BrowserConfig = None, logger: AsyncLogger = None, **kwargs
    ):
        """
        Initialize the AsyncPlaywrightCrawlerStrategy with a browser configuration.
@@ -81,16 +195,11 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            browser_config (BrowserConfig): Configuration object containing browser settings.
                                          If None, will be created from kwargs for backwards compatibility.
            logger: Logger instance for recording events and errors.
-            browser_adapter (BrowserAdapter): Browser adapter for handling browser-specific operations.
-                                           If None, defaults to PlaywrightAdapter.
            **kwargs: Additional arguments for backwards compatibility and extending functionality.
        """
        # Initialize browser config, either from provided object or kwargs
        self.browser_config = browser_config or BrowserConfig.from_kwargs(kwargs)
        self.logger = logger
-        
-        # Initialize browser adapter
-        self.adapter = browser_adapter or PlaywrightAdapter()

        # Initialize session management
        self._downloaded_files = []
@@ -110,9 +219,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):

        # Initialize browser manager with config
        self.browser_manager = BrowserManager(
-            browser_config=self.browser_config, 
-            logger=self.logger,
-            use_undetected=isinstance(self.adapter, UndetectedAdapter)
+            browser_config=self.browser_config, logger=self.logger
        )

    async def __aenter__(self):
@@ -228,6 +335,79 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        """
        self.headers = headers

+    async def _apply_stealth(self, page: Page, stealth_config: Optional[StealthConfig] = None):
+        """
+        Apply stealth measures to the page with backward compatibility and enhanced configuration.
+        
+        This method automatically applies stealth measures and now supports configuration
+        through StealthConfig while maintaining backward compatibility.
+        
+        Currently supports:
+        - tf-playwright-stealth (Stealth class with extensive configuration)
+        - Old playwright-stealth v1.x (stealth_async function) - legacy support
+        
+        Args:
+            page (Page): The Playwright page object
+            stealth_config (Optional[StealthConfig]): Configuration for stealth settings
+        """
+        if STEALTH_NEW_API is None:
+            # No stealth library available - silently continue
+            if self.logger and hasattr(self.logger, 'debug'):
+                self.logger.debug(
+                    message="playwright-stealth not available, skipping stealth measures",
+                    tag="STEALTH"
+                )
+            return
+        
+        # Use default config if none provided
+        if stealth_config is None:
+            stealth_config = StealthConfig()
+        
+        # Skip if stealth is disabled
+        if not stealth_config.enabled:
+            if self.logger and hasattr(self.logger, 'debug'):
+                self.logger.debug(
+                    message="Stealth measures disabled in configuration",
+                    tag="STEALTH"
+                )
+            return
+        
+        try:
+            if STEALTH_NEW_API:
+                # Use tf-playwright-stealth API with configuration support
+                # Filter out any invalid parameters that might cause issues
+                valid_options = {}
+                for key, value in stealth_config.stealth_options.items():
+                    # Accept boolean parameters and specific string/tuple parameters
+                    if isinstance(value, (bool, str, tuple)):
+                        valid_options[key] = value
+                
+                stealth = Stealth(**valid_options)
+                await stealth.apply_stealth_async(page)
+                
+                config_info = f"with {len(valid_options)} options"
+            else:
+                # Use old API (v1.x) - configuration options are limited
+                await stealth_async(page)
+                config_info = "default (v1.x legacy)"
+                
+            # Only log if logger is available and in debug mode
+            if self.logger and hasattr(self.logger, 'debug'):
+                api_version = "tf-playwright-stealth" if STEALTH_NEW_API else "v1.x"
+                self.logger.debug(
+                    message="Applied stealth measures using {version} {config}",
+                    tag="STEALTH",
+                    params={"version": api_version, "config": config_info}
+                )
+        except Exception as e:
+            # Silently continue if stealth fails - don't break the crawling process
+            if self.logger:
+                self.logger.warning(
+                    message="Stealth measures failed, continuing without stealth: {error}",
+                    tag="STEALTH",
+                    params={"error": str(e)}
+                )
+
    async def smart_wait(self, page: Page, wait_for: str, timeout: float = 30000):
        """
        Wait for a condition in a smart way. This functions works as below:
@@ -330,7 +510,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        """

        try:
-            result = await self.adapter.evaluate(page, wrapper_js)
+            result = await page.evaluate(wrapper_js)
            return result
        except Exception as e:
            if "Error evaluating condition" in str(e):
@@ -375,7 +555,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):

                    # Replace the iframe with a div containing the extracted content
                    _iframe = iframe_content.replace("`", "\\`")
-                    await self.adapter.evaluate(page,
+                    await page.evaluate(
                        f"""
                        () => {{
                            const iframe = document.getElementById('iframe-{i}');
@@ -540,6 +720,24 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        # Get page for session
        page, context = await self.browser_manager.get_page(crawlerRunConfig=config)

+        # Apply stealth measures automatically (backward compatible) with optional config
+        # Check multiple possible locations for stealth config for flexibility
+        stealth_config = None
+        if hasattr(config, 'stealth_config') and config.stealth_config:
+            stealth_config = config.stealth_config
+        elif hasattr(config, 'stealth') and config.stealth:
+            # Alternative attribute name for backward compatibility
+            stealth_config = config.stealth if isinstance(config.stealth, StealthConfig) else StealthConfig.from_dict(config.stealth)
+        elif config.magic:
+            # Enable more aggressive stealth in magic mode
+            stealth_config = StealthConfig(
+                navigator_webdriver=False,  # More aggressive stealth
+                webdriver=False,
+                chrome_app=False
+            )
+        
+        await self._apply_stealth(page, stealth_config)
+
        # await page.goto(URL)

        # Add default cookie
@@ -636,16 +834,91 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            page.on("requestfailed", handle_request_failed_capture)

        # Console Message Capturing
-        handle_console = None
-        handle_error = None
        if config.capture_console_messages:
-            # Set up console capture using adapter
-            handle_console = await self.adapter.setup_console_capture(page, captured_console)
-            handle_error = await self.adapter.setup_error_capture(page, captured_console)
+            def handle_console_capture(msg):
+                try:
+                    message_type = "unknown"
+                    try:
+                        message_type = msg.type
+                    except:
+                        pass
+                        
+                    message_text = "unknown"
+                    try:
+                        message_text = msg.text
+                    except:
+                        pass
+                        
+                    # Basic console message with minimal content
+                    entry = {
+                        "type": message_type,
+                        "text": message_text,
+                        "timestamp": time.time()
+                    }
+                    
+                    captured_console.append(entry)
+                    
+                except Exception as e:
+                    if self.logger:
+                        self.logger.warning(f"Error capturing console message: {e}", tag="CAPTURE")
+                    # Still add something to the list even on error
+                    captured_console.append({
+                        "type": "console_capture_error", 
+                        "error": str(e), 
+                        "timestamp": time.time()
+                    })
+
+            def handle_pageerror_capture(err):
+                try:
+                    error_message = "Unknown error"
+                    try:
+                        error_message = err.message
+                    except:
+                        pass
+                        
+                    error_stack = ""
+                    try:
+                        error_stack = err.stack
+                    except:
+                        pass
+                        
+                    captured_console.append({
+                        "type": "error",
+                        "text": error_message,
+                        "stack": error_stack,
+                        "timestamp": time.time()
+                    })
+                except Exception as e:
+                    if self.logger:
+                        self.logger.warning(f"Error capturing page error: {e}", tag="CAPTURE")
+                    captured_console.append({
+                        "type": "pageerror_capture_error", 
+                        "error": str(e), 
+                        "timestamp": time.time()
+                    })
+
+            # Add event listeners directly
+            page.on("console", handle_console_capture)
+            page.on("pageerror", handle_pageerror_capture)

        # Set up console logging if requested
-        # Note: For undetected browsers, console logging won't work directly
-        # but captured messages can still be logged after retrieval
+        if config.log_console:
+            def log_consol(
+                msg, console_log_type="debug"
+            ):  # Corrected the parameter syntax
+                if console_log_type == "error":
+                    self.logger.error(
+                        message=f"Console error: {msg}",  # Use f-string for variable interpolation
+                        tag="CONSOLE"
+                    )
+                elif console_log_type == "debug":
+                    self.logger.debug(
+                        message=f"Console: {msg}",  # Use f-string for variable interpolation
+                        tag="CONSOLE"
+                    )
+
+            page.on("console", log_consol)
+            page.on("pageerror", lambda e: log_consol(e, "error"))

        try:
            # Get SSL certificate information if requested and URL is HTTPS
@@ -757,7 +1030,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            except Error:
                visibility_info = await self.check_visibility(page)

-                if self.browser_config.verbose:
+                if self.browser_config.config.verbose:
                    self.logger.debug(
                        message="Body visibility info: {info}",
                        tag="DEBUG",
@@ -866,7 +1139,6 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
                        tag="VIEWPORT",
                        params={"error": str(e)},
                    )
-
            # Handle full page scanning
            if config.scan_full_page:
                # await self._handle_full_page_scan(page, config.scroll_delay)
@@ -931,7 +1203,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
                        await page.wait_for_load_state("domcontentloaded", timeout=5)
                    except PlaywrightTimeoutError:
                        pass
-                    await self.adapter.evaluate(page, update_image_dimensions_js)
+                    await page.evaluate(update_image_dimensions_js)
                except Exception as e:
                    self.logger.error(
                        message="Error updating image dimensions: {error}",
@@ -960,7 +1232,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
                    
                    for selector in selectors:
                        try:
-                            content = await self.adapter.evaluate(page,
+                            content = await page.evaluate(
                                f"""Array.from(document.querySelectorAll("{selector}"))
                                    .map(el => el.outerHTML)
                                    .join('')"""
@@ -1018,11 +1290,6 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
                await asyncio.sleep(delay)
                return await page.content()

-            # For undetected browsers, retrieve console messages before returning
-            if config.capture_console_messages and hasattr(self.adapter, 'retrieve_console_messages'):
-                final_messages = await self.adapter.retrieve_console_messages(page)
-                captured_console.extend(final_messages)
-
            # Return complete response
            return AsyncCrawlResponse(
                html=html,
@@ -1061,13 +1328,8 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
                    page.remove_listener("response", handle_response_capture)
                    page.remove_listener("requestfailed", handle_request_failed_capture)
                if config.capture_console_messages:
-                    # Retrieve any final console messages for undetected browsers
-                    if hasattr(self.adapter, 'retrieve_console_messages'):
-                        final_messages = await self.adapter.retrieve_console_messages(page)
-                        captured_console.extend(final_messages)
-                    
-                    # Clean up console capture
-                    await self.adapter.cleanup_console_capture(page, handle_console, handle_error)
+                    page.remove_listener("console", handle_console_capture)
+                    page.remove_listener("pageerror", handle_pageerror_capture)
                
                # Close the page
                await page.close()
@@ -1297,7 +1559,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            """
            
            # Execute virtual scroll capture
-            result = await self.adapter.evaluate(page, virtual_scroll_js, config.to_dict())
+            result = await page.evaluate(virtual_scroll_js, config.to_dict())
            
            if result.get("replaced", False):
                self.logger.success(
@@ -1381,7 +1643,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        remove_overlays_js = load_js_script("remove_overlay_elements")

        try:
-            await self.adapter.evaluate(page,
+            await page.evaluate(
                f"""
                (() => {{
                    try {{
@@ -1780,13 +2042,11 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
                        #     }}
                        # }})();
                        # """
-                        # )
-                        
                        # """ NEW VERSION:
                        # When {script} contains statements (e.g., const link = …; link.click();), 
                        # this forms invalid JavaScript, causing Playwright execution error: SyntaxError: Unexpected token 'const'.
                        # """
-                        result = await self.adapter.evaluate(page,
+                        result = await page.evaluate(
                            f"""
                        (async () => {{
                            try {{
@@ -1908,7 +2168,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            for script in scripts:
                try:
                    # Execute the script and wait for network idle
-                    result = await self.adapter.evaluate(page,
+                    result = await page.evaluate(
                        f"""
                        (() => {{
                            return new Promise((resolve) => {{
@@ -1992,7 +2252,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        Returns:
            Boolean indicating visibility
        """
-        return await self.adapter.evaluate(page,
+        return await page.evaluate(
            """
            () => {
                const element = document.body;
@@ -2033,7 +2293,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            Dict containing scroll status and position information
        """
        try:
-            result = await self.adapter.evaluate(page,
+            result = await page.evaluate(
                f"""() => {{
                    try {{
                        const startX = window.scrollX;
@@ -2090,7 +2350,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
        Returns:
            Dict containing width and height of the page
        """
-        return await self.adapter.evaluate(page,
+        return await page.evaluate(
            """
            () => {
                const {scrollWidth, scrollHeight} = document.documentElement;
@@ -2110,7 +2370,7 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            bool: True if page needs scrolling
        """
        try:
-            need_scroll = await self.adapter.evaluate(page,
+            need_scroll = await page.evaluate(
                """
            () => {
                const scrollHeight = document.documentElement.scrollHeight;
@@ -2129,3 +2389,265 @@ class AsyncPlaywrightCrawlerStrategy(AsyncCrawlerStrategy):
            return True  # Default to scrolling if check fails


+####################################################################################################
+# HTTP Crawler Strategy
+####################################################################################################
+
+class HTTPCrawlerError(Exception):
+    """Base error class for HTTP crawler specific exceptions"""
+    pass
+
+
+class ConnectionTimeoutError(HTTPCrawlerError):
+    """Raised when connection timeout occurs"""
+    pass
+
+
+class HTTPStatusError(HTTPCrawlerError):
+    """Raised for unexpected status codes"""
+    def __init__(self, status_code: int, message: str):
+        self.status_code = status_code
+        super().__init__(f"HTTP {status_code}: {message}")
+
+
+class AsyncHTTPCrawlerStrategy(AsyncCrawlerStrategy):
+    """
+    Fast, lightweight HTTP-only crawler strategy optimized for memory efficiency.
+    """
+    
+    __slots__ = ('logger', 'max_connections', 'dns_cache_ttl', 'chunk_size', '_session', 'hooks', 'browser_config')
+
+    DEFAULT_TIMEOUT: Final[int] = 30
+    DEFAULT_CHUNK_SIZE: Final[int] = 64 * 1024  
+    DEFAULT_MAX_CONNECTIONS: Final[int] = min(32, (os.cpu_count() or 1) * 4)
+    DEFAULT_DNS_CACHE_TTL: Final[int] = 300
+    VALID_SCHEMES: Final = frozenset({'http', 'https', 'file', 'raw'})
+
+    _BASE_HEADERS: Final = MappingProxyType({
+        'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+        'Accept-Language': 'en-US,en;q=0.5',
+        'Accept-Encoding': 'gzip, deflate, br',
+        'Connection': 'keep-alive',
+        'Upgrade-Insecure-Requests': '1',
+        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
+    })
+    
+    def __init__(
+        self, 
+        browser_config: Optional[HTTPCrawlerConfig] = None,
+        logger: Optional[AsyncLogger] = None,
+        max_connections: int = DEFAULT_MAX_CONNECTIONS,
+        dns_cache_ttl: int = DEFAULT_DNS_CACHE_TTL,
+        chunk_size: int = DEFAULT_CHUNK_SIZE
+    ):
+        """Initialize the HTTP crawler with config"""
+        self.browser_config = browser_config or HTTPCrawlerConfig()
+        self.logger = logger
+        self.max_connections = max_connections
+        self.dns_cache_ttl = dns_cache_ttl
+        self.chunk_size = chunk_size
+        self._session: Optional[aiohttp.ClientSession] = None
+        
+        self.hooks = {
+            k: partial(self._execute_hook, k) 
+            for k in ('before_request', 'after_request', 'on_error')
+        }
+
+        # Set default hooks
+        self.set_hook('before_request', lambda *args, **kwargs: None)
+        self.set_hook('after_request', lambda *args, **kwargs: None)
+        self.set_hook('on_error', lambda *args, **kwargs: None)
+                      
+
+    async def __aenter__(self) -> AsyncHTTPCrawlerStrategy:
+        await self.start()
+        return self
+        
+    async def __aexit__(self, exc_type, exc_val, exc_tb) -> None:
+        await self.close()
+
+    @contextlib.asynccontextmanager
+    async def _session_context(self):
+        try:
+            if not self._session:
+                await self.start()
+            yield self._session
+        finally:
+            pass
+
+    def set_hook(self, hook_type: str, hook_func: Callable) -> None:
+        if hook_type in self.hooks:
+            self.hooks[hook_type] = partial(self._execute_hook, hook_type, hook_func)
+        else:
+            raise ValueError(f"Invalid hook type: {hook_type}")
+
+    async def _execute_hook(
+        self, 
+        hook_type: str, 
+        hook_func: Callable,
+        *args: Any, 
+        **kwargs: Any
+    ) -> Any:
+        if asyncio.iscoroutinefunction(hook_func):
+            return await hook_func(*args, **kwargs)
+        return hook_func(*args, **kwargs)
+
+    async def start(self) -> None:
+        if not self._session:
+            connector = aiohttp.TCPConnector(
+                limit=self.max_connections,
+                ttl_dns_cache=self.dns_cache_ttl,
+                use_dns_cache=True,
+                force_close=False
+            )
+            self._session = aiohttp.ClientSession(
+                headers=dict(self._BASE_HEADERS),
+                connector=connector,
+                timeout=ClientTimeout(total=self.DEFAULT_TIMEOUT)
+            )
+
+    async def close(self) -> None:
+        if self._session and not self._session.closed:
+            try:
+                await asyncio.wait_for(self._session.close(), timeout=5.0)
+            except asyncio.TimeoutError:
+                if self.logger:
+                    self.logger.warning(
+                        message="Session cleanup timed out",
+                        tag="CLEANUP"
+                    )
+            finally:
+                self._session = None
+
+    async def _stream_file(self, path: str) -> AsyncGenerator[memoryview, None]:
+        async with aiofiles.open(path, mode='rb') as f:
+            while chunk := await f.read(self.chunk_size):
+                yield memoryview(chunk)
+
+    async def _handle_file(self, path: str) -> AsyncCrawlResponse:
+        if not os.path.exists(path):
+            raise FileNotFoundError(f"Local file not found: {path}")
+            
+        chunks = []
+        async for chunk in self._stream_file(path):
+            chunks.append(chunk.tobytes().decode('utf-8', errors='replace'))
+            
+        return AsyncCrawlResponse(
+            html=''.join(chunks),
+            response_headers={},
+            status_code=200
+        )
+
+    async def _handle_raw(self, content: str) -> AsyncCrawlResponse:
+        return AsyncCrawlResponse(
+            html=content,
+            response_headers={},
+            status_code=200
+        )
+
+
+    async def _handle_http(
+        self, 
+        url: str, 
+        config: CrawlerRunConfig
+    ) -> AsyncCrawlResponse:
+        async with self._session_context() as session:
+            timeout = ClientTimeout(
+                total=config.page_timeout or self.DEFAULT_TIMEOUT,
+                connect=10,
+                sock_read=30
+            )
+            
+            headers = dict(self._BASE_HEADERS)
+            if self.browser_config.headers:
+                headers.update(self.browser_config.headers)
+
+            request_kwargs = {
+                'timeout': timeout,
+                'allow_redirects': self.browser_config.follow_redirects,
+                'ssl': self.browser_config.verify_ssl,
+                'headers': headers
+            }
+
+            if self.browser_config.method == "POST":
+                if self.browser_config.data:
+                    request_kwargs['data'] = self.browser_config.data
+                if self.browser_config.json:
+                    request_kwargs['json'] = self.browser_config.json
+
+            await self.hooks['before_request'](url, request_kwargs)
+
+            try:
+                async with session.request(self.browser_config.method, url, **request_kwargs) as response:
+                    content = memoryview(await response.read())
+                    
+                    if not (200 <= response.status < 300):
+                        raise HTTPStatusError(
+                            response.status,
+                            f"Unexpected status code for {url}"
+                        )
+                    
+                    encoding = response.charset
+                    if not encoding:
+                        encoding = chardet.detect(content.tobytes())['encoding'] or 'utf-8'                    
+                    
+                    result = AsyncCrawlResponse(
+                        html=content.tobytes().decode(encoding, errors='replace'),
+                        response_headers=dict(response.headers),
+                        status_code=response.status,
+                        redirected_url=str(response.url)
+                    )
+                    
+                    await self.hooks['after_request'](result)
+                    return result
+
+            except aiohttp.ServerTimeoutError as e:
+                await self.hooks['on_error'](e)
+                raise ConnectionTimeoutError(f"Request timed out: {str(e)}")
+                
+            except aiohttp.ClientConnectorError as e:
+                await self.hooks['on_error'](e)
+                raise ConnectionError(f"Connection failed: {str(e)}")
+                
+            except aiohttp.ClientError as e:
+                await self.hooks['on_error'](e)
+                raise HTTPCrawlerError(f"HTTP client error: {str(e)}")
+            
+            except asyncio.exceptions.TimeoutError as e:
+                await self.hooks['on_error'](e)
+                raise ConnectionTimeoutError(f"Request timed out: {str(e)}")
+            
+            except Exception as e:
+                await self.hooks['on_error'](e)
+                raise HTTPCrawlerError(f"HTTP request failed: {str(e)}")
+
+    async def crawl(
+        self, 
+        url: str, 
+        config: Optional[CrawlerRunConfig] = None, 
+        **kwargs
+    ) -> AsyncCrawlResponse:
+        config = config or CrawlerRunConfig.from_kwargs(kwargs)
+        
+        parsed = urlparse(url)
+        scheme = parsed.scheme.rstrip('/')
+        
+        if scheme not in self.VALID_SCHEMES:
+            raise ValueError(f"Unsupported URL scheme: {scheme}")
+            
+        try:
+            if scheme == 'file':
+                return await self._handle_file(parsed.path)
+            elif scheme == 'raw':
+                return await self._handle_raw(parsed.path)
+            else:  # http or https
+                return await self._handle_http(url, config)
+                
+        except Exception as e:
+            if self.logger:
+                self.logger.error(
+                    message="Crawl failed: {error}",
+                    tag="CRAWL",
+                    params={"error": str(e), "url": url}
+                )
+            raise
--- a/crawl4ai/async_dispatcher.py
+++ b/crawl4ai/async_dispatcher.py
@@ -1,4 +1,4 @@
-from typing import Dict, Optional, List, Tuple, Union
+from typing import Dict, Optional, List, Tuple
 from .async_configs import CrawlerRunConfig
 from .models import (
    CrawlResult,
@@ -22,8 +22,6 @@ from urllib.parse import urlparse
 import random
 from abc import ABC, abstractmethod

-from .memory_utils import get_true_memory_usage_percent
-

 class RateLimiter:
    def __init__(
@@ -98,37 +96,11 @@ class BaseDispatcher(ABC):
        self.rate_limiter = rate_limiter
        self.monitor = monitor

-    def select_config(self, url: str, configs: Union[CrawlerRunConfig, List[CrawlerRunConfig]]) -> Optional[CrawlerRunConfig]:
-        """Select the appropriate config for a given URL.
-        
-        Args:
-            url: The URL to match against
-            configs: Single config or list of configs to choose from
-            
-        Returns:
-            The matching config, or None if no match found
-        """
-        # Single config - return as is
-        if isinstance(configs, CrawlerRunConfig):
-            return configs
-        
-        # Empty list - return None
-        if not configs:
-            return None
-        
-        # Find first matching config
-        for config in configs:
-            if config.is_match(url):
-                return config
-        
-        # No match found - return None to indicate URL should be skipped
-        return None
-
    @abstractmethod
    async def crawl_url(
        self,
        url: str,
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
        task_id: str,
        monitor: Optional[CrawlerMonitor] = None,
    ) -> CrawlerTaskResult:
@@ -139,7 +111,7 @@ class BaseDispatcher(ABC):
        self,
        urls: List[str],
        crawler: AsyncWebCrawler,  # noqa: F821
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
        monitor: Optional[CrawlerMonitor] = None,
    ) -> List[CrawlerTaskResult]:
        pass
@@ -175,7 +147,7 @@ class MemoryAdaptiveDispatcher(BaseDispatcher):
    async def _memory_monitor_task(self):
        """Background task to continuously monitor memory usage and update state"""
        while True:
-            self.current_memory_percent = get_true_memory_usage_percent()
+            self.current_memory_percent = psutil.virtual_memory().percent

            # Enter memory pressure mode if we cross the threshold
            if self.current_memory_percent >= self.memory_threshold_percent:
@@ -228,7 +200,7 @@ class MemoryAdaptiveDispatcher(BaseDispatcher):
    async def crawl_url(
        self,
        url: str,
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
        task_id: str,
        retry_count: int = 0,
    ) -> CrawlerTaskResult:
@@ -236,37 +208,6 @@ class MemoryAdaptiveDispatcher(BaseDispatcher):
        error_message = ""
        memory_usage = peak_memory = 0.0
        
-        # Select appropriate config for this URL
-        selected_config = self.select_config(url, config)
-        
-        # If no config matches, return failed result
-        if selected_config is None:
-            error_message = f"No matching configuration found for URL: {url}"
-            if self.monitor:
-                self.monitor.update_task(
-                    task_id, 
-                    status=CrawlStatus.FAILED,
-                    error_message=error_message
-                )
-            
-            return CrawlerTaskResult(
-                task_id=task_id,
-                url=url,
-                result=CrawlResult(
-                    url=url, 
-                    html="", 
-                    metadata={"status": "no_config_match"}, 
-                    success=False, 
-                    error_message=error_message
-                ),
-                memory_usage=0,
-                peak_memory=0,
-                start_time=start_time,
-                end_time=time.time(),
-                error_message=error_message,
-                retry_count=retry_count
-            )
-        
        # Get starting memory for accurate measurement
        process = psutil.Process()
        start_memory = process.memory_info().rss / (1024 * 1024)
@@ -316,8 +257,8 @@ class MemoryAdaptiveDispatcher(BaseDispatcher):
                    retry_count=retry_count + 1
                )
            
-            # Execute the crawl with selected config
-            result = await self.crawler.arun(url, config=selected_config, session_id=task_id)
+            # Execute the crawl
+            result = await self.crawler.arun(url, config=config, session_id=task_id)
            
            # Measure memory usage
            end_memory = process.memory_info().rss / (1024 * 1024)
@@ -375,7 +316,7 @@ class MemoryAdaptiveDispatcher(BaseDispatcher):
        self,
        urls: List[str],
        crawler: AsyncWebCrawler,
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
    ) -> List[CrawlerTaskResult]:
        self.crawler = crawler
        
@@ -529,7 +470,7 @@ class MemoryAdaptiveDispatcher(BaseDispatcher):
        self,
        urls: List[str],
        crawler: AsyncWebCrawler,
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
    ) -> AsyncGenerator[CrawlerTaskResult, None]:
        self.crawler = crawler
        
@@ -631,7 +572,7 @@ class SemaphoreDispatcher(BaseDispatcher):
    async def crawl_url(
        self,
        url: str,
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
        task_id: str,
        semaphore: asyncio.Semaphore = None,
    ) -> CrawlerTaskResult:
@@ -639,36 +580,6 @@ class SemaphoreDispatcher(BaseDispatcher):
        error_message = ""
        memory_usage = peak_memory = 0.0

-        # Select appropriate config for this URL
-        selected_config = self.select_config(url, config)
-        
-        # If no config matches, return failed result
-        if selected_config is None:
-            error_message = f"No matching configuration found for URL: {url}"
-            if self.monitor:
-                self.monitor.update_task(
-                    task_id, 
-                    status=CrawlStatus.FAILED,
-                    error_message=error_message
-                )
-            
-            return CrawlerTaskResult(
-                task_id=task_id,
-                url=url,
-                result=CrawlResult(
-                    url=url, 
-                    html="", 
-                    metadata={"status": "no_config_match"}, 
-                    success=False, 
-                    error_message=error_message
-                ),
-                memory_usage=0,
-                peak_memory=0,
-                start_time=start_time,
-                end_time=time.time(),
-                error_message=error_message
-            )
-
        try:
            if self.monitor:
                self.monitor.update_task(
@@ -681,7 +592,7 @@ class SemaphoreDispatcher(BaseDispatcher):
            async with semaphore:
                process = psutil.Process()
                start_memory = process.memory_info().rss / (1024 * 1024)
-                result = await self.crawler.arun(url, config=selected_config, session_id=task_id)
+                result = await self.crawler.arun(url, config=config, session_id=task_id)
                end_memory = process.memory_info().rss / (1024 * 1024)

                memory_usage = peak_memory = end_memory - start_memory
@@ -743,7 +654,7 @@ class SemaphoreDispatcher(BaseDispatcher):
        self,
        crawler: AsyncWebCrawler,  # noqa: F821
        urls: List[str],
-        config: Union[CrawlerRunConfig, List[CrawlerRunConfig]],
+        config: CrawlerRunConfig,
    ) -> List[CrawlerTaskResult]:
        self.crawler = crawler
        if self.monitor:
--- a/crawl4ai/async_url_seeder.py
+++ b/crawl4ai/async_url_seeder.py
@@ -829,7 +829,7 @@ class AsyncUrlSeeder:

    async def _iter_sitemap(self, url: str):
        try:
-            r = await self.client.get(url, timeout=15, follow_redirects=True)
+            r = await self.client.get(url, timeout=15)
            r.raise_for_status()
        except httpx.HTTPStatusError as e:
            self._log("warning", "Failed to fetch sitemap {url}: HTTP {status_code}",
--- a/crawl4ai/async_webcrawler.py
+++ b/crawl4ai/async_webcrawler.py
@@ -502,12 +502,9 @@ class AsyncWebCrawler:
            metadata = result.get("metadata", {})
        else:
            cleaned_html = sanitize_input_encode(result.cleaned_html)
-            # media = result.media.model_dump()
-            # tables = media.pop("tables", [])
-            # links = result.links.model_dump()
-            media = result.media.model_dump() if hasattr(result.media, 'model_dump') else result.media
-            tables = media.pop("tables", []) if isinstance(media, dict) else []
-            links = result.links.model_dump() if hasattr(result.links, 'model_dump') else result.links
+            media = result.media.model_dump()
+            tables = media.pop("tables", [])
+            links = result.links.model_dump()
            metadata = result.metadata

        fit_html = preprocess_html_for_schema(html_content=html, text_threshold= 500, max_size= 300_000)
@@ -653,7 +650,7 @@ class AsyncWebCrawler:
    async def arun_many(
        self,
        urls: List[str],
-        config: Optional[Union[CrawlerRunConfig, List[CrawlerRunConfig]]] = None,
+        config: Optional[CrawlerRunConfig] = None,
        dispatcher: Optional[BaseDispatcher] = None,
        # Legacy parameters maintained for backwards compatibility
        # word_count_threshold=MIN_WORD_THRESHOLD,
@@ -674,9 +671,7 @@ class AsyncWebCrawler:

        Args:
        urls: List of URLs to crawl
-        config: Configuration object(s) controlling crawl behavior. Can be:
-            - Single CrawlerRunConfig: Used for all URLs
-            - List[CrawlerRunConfig]: Configs with url_matcher for URL-specific settings
+        config: Configuration object controlling crawl behavior for all URLs
        dispatcher: The dispatcher strategy instance to use. Defaults to MemoryAdaptiveDispatcher
        [other parameters maintained for backwards compatibility]

@@ -741,11 +736,7 @@ class AsyncWebCrawler:
                or task_result.result
            )

-        # Handle stream setting - use first config's stream setting if config is a list
-        if isinstance(config, list):
-            stream = config[0].stream if config else False
-        else:
-            stream = config.stream
+        stream = config.stream

        if stream:

--- a/crawl4ai/browser_adapter.py
+++ b/crawl4ai/browser_adapter.py
@@ -1,293 +0,0 @@
-# browser_adapter.py
-"""
-Browser adapter for Crawl4AI to support both Playwright and undetected browsers
-with minimal changes to existing codebase.
-"""
-
-from abc import ABC, abstractmethod
-from typing import List, Dict, Any, Optional, Callable
-import time
-import json
-
-# Import both, but use conditionally
-try:
-    from playwright.async_api import Page
-except ImportError:
-    Page = Any
-
-try:
-    from patchright.async_api import Page as UndetectedPage
-except ImportError:
-    UndetectedPage = Any
-
-
-class BrowserAdapter(ABC):
-    """Abstract adapter for browser-specific operations"""
-    
-    @abstractmethod
-    async def evaluate(self, page: Page, expression: str, arg: Any = None) -> Any:
-        """Execute JavaScript in the page"""
-        pass
-    
-    @abstractmethod
-    async def setup_console_capture(self, page: Page, captured_console: List[Dict]) -> Optional[Callable]:
-        """Setup console message capturing, returns handler function if needed"""
-        pass
-    
-    @abstractmethod
-    async def setup_error_capture(self, page: Page, captured_console: List[Dict]) -> Optional[Callable]:
-        """Setup error capturing, returns handler function if needed"""
-        pass
-    
-    @abstractmethod
-    async def retrieve_console_messages(self, page: Page) -> List[Dict]:
-        """Retrieve captured console messages (for undetected browsers)"""
-        pass
-    
-    @abstractmethod
-    async def cleanup_console_capture(self, page: Page, handle_console: Optional[Callable], handle_error: Optional[Callable]):
-        """Clean up console event listeners"""
-        pass
-    
-    @abstractmethod
-    def get_imports(self) -> tuple:
-        """Get the appropriate imports for this adapter"""
-        pass
-
-
-class PlaywrightAdapter(BrowserAdapter):
-    """Adapter for standard Playwright"""
-    
-    async def evaluate(self, page: Page, expression: str, arg: Any = None) -> Any:
-        """Standard Playwright evaluate"""
-        if arg is not None:
-            return await page.evaluate(expression, arg)
-        return await page.evaluate(expression)
-    
-    async def setup_console_capture(self, page: Page, captured_console: List[Dict]) -> Optional[Callable]:
-        """Setup console capture using Playwright's event system"""
-        def handle_console_capture(msg):
-            try:
-                message_type = "unknown"
-                try:
-                    message_type = msg.type
-                except:
-                    pass
-                    
-                message_text = "unknown"
-                try:
-                    message_text = msg.text
-                except:
-                    pass
-                    
-                entry = {
-                    "type": message_type,
-                    "text": message_text,
-                    "timestamp": time.time()
-                }
-                
-                captured_console.append(entry)
-                
-            except Exception as e:
-                captured_console.append({
-                    "type": "console_capture_error", 
-                    "error": str(e), 
-                    "timestamp": time.time()
-                })
-        
-        page.on("console", handle_console_capture)
-        return handle_console_capture
-    
-    async def setup_error_capture(self, page: Page, captured_console: List[Dict]) -> Optional[Callable]:
-        """Setup error capture using Playwright's event system"""
-        def handle_pageerror_capture(err):
-            try:
-                error_message = "Unknown error"
-                try:
-                    error_message = err.message
-                except:
-                    pass
-                    
-                error_stack = ""
-                try:
-                    error_stack = err.stack
-                except:
-                    pass
-                    
-                captured_console.append({
-                    "type": "error",
-                    "text": error_message,
-                    "stack": error_stack,
-                    "timestamp": time.time()
-                })
-            except Exception as e:
-                captured_console.append({
-                    "type": "pageerror_capture_error", 
-                    "error": str(e), 
-                    "timestamp": time.time()
-                })
-        
-        page.on("pageerror", handle_pageerror_capture)
-        return handle_pageerror_capture
-    
-    async def retrieve_console_messages(self, page: Page) -> List[Dict]:
-        """Not needed for Playwright - messages are captured via events"""
-        return []
-    
-    async def cleanup_console_capture(self, page: Page, handle_console: Optional[Callable], handle_error: Optional[Callable]):
-        """Remove event listeners"""
-        if handle_console:
-            page.remove_listener("console", handle_console)
-        if handle_error:
-            page.remove_listener("pageerror", handle_error)
-    
-    def get_imports(self) -> tuple:
-        """Return Playwright imports"""
-        from playwright.async_api import Page, Error
-        from playwright.async_api import TimeoutError as PlaywrightTimeoutError
-        return Page, Error, PlaywrightTimeoutError
-
-
-class UndetectedAdapter(BrowserAdapter):
-    """Adapter for undetected browser automation with stealth features"""
-    
-    def __init__(self):
-        self._console_script_injected = {}
-    
-    async def evaluate(self, page: UndetectedPage, expression: str, arg: Any = None) -> Any:
-        """Undetected browser evaluate with isolated context"""
-        # For most evaluations, use isolated context for stealth
-        # Only use non-isolated when we need to access our injected console capture
-        isolated = not (
-            "__console" in expression or 
-            "__captured" in expression or
-            "__error" in expression or
-            "window.__" in expression
-        )
-        
-        if arg is not None:
-            return await page.evaluate(expression, arg, isolated_context=isolated)
-        return await page.evaluate(expression, isolated_context=isolated)
-    
-    async def setup_console_capture(self, page: UndetectedPage, captured_console: List[Dict]) -> Optional[Callable]:
-        """Setup console capture using JavaScript injection for undetected browsers"""
-        if not self._console_script_injected.get(page, False):
-            await page.add_init_script("""
-                // Initialize console capture
-                window.__capturedConsole = [];
-                window.__capturedErrors = [];
-                
-                // Store original console methods
-                const originalConsole = {};
-                ['log', 'info', 'warn', 'error', 'debug'].forEach(method => {
-                    originalConsole[method] = console[method];
-                    console[method] = function(...args) {
-                        try {
-                            window.__capturedConsole.push({
-                                type: method,
-                                text: args.map(arg => {
-                                    try {
-                                        if (typeof arg === 'object') {
-                                            return JSON.stringify(arg);
-                                        }
-                                        return String(arg);
-                                    } catch (e) {
-                                        return '[Object]';
-                                    }
-                                }).join(' '),
-                                timestamp: Date.now()
-                            });
-                        } catch (e) {
-                            // Fail silently to avoid detection
-                        }
-                        
-                        // Call original method
-                        originalConsole[method].apply(console, args);
-                    };
-                });
-            """)
-            self._console_script_injected[page] = True
-        
-        return None  # No handler function needed for undetected browser
-    
-    async def setup_error_capture(self, page: UndetectedPage, captured_console: List[Dict]) -> Optional[Callable]:
-        """Setup error capture using JavaScript injection for undetected browsers"""
-        if not self._console_script_injected.get(page, False):
-            await page.add_init_script("""
-                // Capture errors
-                window.addEventListener('error', (event) => {
-                    try {
-                        window.__capturedErrors.push({
-                            type: 'error',
-                            text: event.message,
-                            stack: event.error ? event.error.stack : '',
-                            filename: event.filename,
-                            lineno: event.lineno,
-                            colno: event.colno,
-                            timestamp: Date.now()
-                        });
-                    } catch (e) {
-                        // Fail silently
-                    }
-                });
-                
-                // Capture unhandled promise rejections
-                window.addEventListener('unhandledrejection', (event) => {
-                    try {
-                        window.__capturedErrors.push({
-                            type: 'unhandledrejection',
-                            text: event.reason ? String(event.reason) : 'Unhandled Promise Rejection',
-                            stack: event.reason && event.reason.stack ? event.reason.stack : '',
-                            timestamp: Date.now()
-                        });
-                    } catch (e) {
-                        // Fail silently
-                    }
-                });
-            """)
-            self._console_script_injected[page] = True
-        
-        return None  # No handler function needed for undetected browser
-    
-    async def retrieve_console_messages(self, page: UndetectedPage) -> List[Dict]:
-        """Retrieve captured console messages and errors from the page"""
-        messages = []
-        
-        try:
-            # Get console messages
-            console_messages = await page.evaluate(
-                "() => { const msgs = window.__capturedConsole || []; window.__capturedConsole = []; return msgs; }",
-                isolated_context=False
-            )
-            messages.extend(console_messages)
-            
-            # Get errors
-            errors = await page.evaluate(
-                "() => { const errs = window.__capturedErrors || []; window.__capturedErrors = []; return errs; }",
-                isolated_context=False
-            )
-            messages.extend(errors)
-            
-            # Convert timestamps from JS to Python format
-            for msg in messages:
-                if 'timestamp' in msg and isinstance(msg['timestamp'], (int, float)):
-                    msg['timestamp'] = msg['timestamp'] / 1000.0  # Convert from ms to seconds
-                    
-        except Exception:
-            # If retrieval fails, return empty list
-            pass
-        
-        return messages
-    
-    async def cleanup_console_capture(self, page: UndetectedPage, handle_console: Optional[Callable], handle_error: Optional[Callable]):
-        """Clean up for undetected browser - retrieve final messages"""
-        # For undetected browser, we don't have event listeners to remove
-        # but we should retrieve any final messages
-        final_messages = await self.retrieve_console_messages(page)
-        return final_messages
-    
-    def get_imports(self) -> tuple:
-        """Return undetected browser imports"""
-        from patchright.async_api import Page, Error
-        from patchright.async_api import TimeoutError as PlaywrightTimeoutError
-        return Page, Error, PlaywrightTimeoutError
--- a/crawl4ai/browser_manager.py
+++ b/crawl4ai/browser_manager.py
@@ -16,7 +16,6 @@ from .config import DOWNLOAD_PAGE_TIMEOUT
 from .async_configs import BrowserConfig, CrawlerRunConfig
 from .utils import get_chromium_path

-
 BROWSER_DISABLE_OPTIONS = [
    "--disable-background-networking",
    "--disable-background-timer-throttling",
@@ -573,26 +572,21 @@ class BrowserManager:
    _playwright_instance = None
    
    @classmethod
-    async def get_playwright(cls, use_undetected: bool = False):
-        if use_undetected:
-            from patchright.async_api import async_playwright
-        else:
-            from playwright.async_api import async_playwright
+    async def get_playwright(cls):
+        from playwright.async_api import async_playwright
        cls._playwright_instance = await async_playwright().start()
        return cls._playwright_instance    

-    def __init__(self, browser_config: BrowserConfig, logger=None, use_undetected: bool = False):
+    def __init__(self, browser_config: BrowserConfig, logger=None):
        """
        Initialize the BrowserManager with a browser configuration.

        Args:
            browser_config (BrowserConfig): Configuration object containing all browser settings
            logger: Logger instance for recording events and errors
-            use_undetected (bool): Whether to use undetected browser (Patchright)
        """
        self.config: BrowserConfig = browser_config
        self.logger = logger
-        self.use_undetected = use_undetected

        # Browser state
        self.browser = None
@@ -606,11 +600,7 @@ class BrowserManager:

        # Keep track of contexts by a "config signature," so each unique config reuses a single context
        self.contexts_by_config = {}
-        self._contexts_lock = asyncio.Lock()
-        
-        # Stealth-related attributes
-        self._stealth_instance = None
-        self._stealth_cm = None 
+        self._contexts_lock = asyncio.Lock() 

        # Initialize ManagedBrowser if needed
        if self.config.use_managed_browser:
@@ -639,21 +629,9 @@ class BrowserManager:
        if self.playwright is not None:
            await self.close()
            
-        if self.use_undetected:
-            from patchright.async_api import async_playwright
-        else:
-            from playwright.async_api import async_playwright
+        from playwright.async_api import async_playwright

-        # Initialize playwright with or without stealth
-        if self.config.enable_stealth and not self.use_undetected:
-            # Import stealth only when needed
-            from playwright_stealth import Stealth
-            # Use the recommended stealth wrapper approach
-            self._stealth_instance = Stealth()
-            self._stealth_cm = self._stealth_instance.use_async(async_playwright())
-            self.playwright = await self._stealth_cm.__aenter__()
-        else:
-            self.playwright = await async_playwright().start()
+        self.playwright = await async_playwright().start()

        if self.config.cdp_url or self.config.use_managed_browser:
            self.config.use_managed_browser = True
@@ -1115,19 +1093,5 @@ class BrowserManager:
            self.managed_browser = None

        if self.playwright:
-            # Handle stealth context manager cleanup if it exists
-            if hasattr(self, '_stealth_cm') and self._stealth_cm is not None:
-                try:
-                    await self._stealth_cm.__aexit__(None, None, None)
-                except Exception as e:
-                    if self.logger:
-                        self.logger.error(
-                            message="Error closing stealth context: {error}",
-                            tag="ERROR", 
-                            params={"error": str(e)}
-                        )
-                self._stealth_cm = None
-                self._stealth_instance = None
-            else:
-                await self.playwright.stop()
+            await self.playwright.stop()
            self.playwright = None
--- a/crawl4ai/cli.py
+++ b/crawl4ai/cli.py
@@ -27,10 +27,7 @@ from crawl4ai import (
    PruningContentFilter,
    BrowserProfiler,
    DefaultMarkdownGenerator,
-    LLMConfig,
-    BFSDeepCrawlStrategy,
-    DFSDeepCrawlStrategy,
-    BestFirstCrawlingStrategy,
+    LLMConfig
 )
 from crawl4ai.config import USER_SETTINGS
 from litellm import completion
@@ -1017,11 +1014,9 @@ def cdp_cmd(user_data_dir: Optional[str], port: int, browser_type: str, headless
@click.option("--question", "-q", help="Ask a question about the crawled content")
@click.option("--verbose", "-v", is_flag=True)
@click.option("--profile", "-p", help="Use a specific browser profile (by name)")
-@click.option("--deep-crawl", type=click.Choice(["bfs", "dfs", "best-first"]), help="Enable deep crawling with specified strategy (bfs, dfs, or best-first)")
-@click.option("--max-pages", type=int, default=10, help="Maximum number of pages to crawl in deep crawl mode")
 def crawl_cmd(url: str, browser_config: str, crawler_config: str, filter_config: str, 
           extraction_config: str, json_extract: str, schema: str, browser: Dict, crawler: Dict,
-           output: str, output_file: str, bypass_cache: bool, question: str, verbose: bool, profile: str, deep_crawl: str, max_pages: int):
+           output: str, output_file: str, bypass_cache: bool, question: str, verbose: bool, profile: str):
    """Crawl a website and extract content
    
    Simple Usage:
@@ -1161,27 +1156,6 @@ Always return valid, properly formatted JSON."""

        crawler_cfg.scraping_strategy = LXMLWebScrapingStrategy()    

-        # Handle deep crawling configuration
-        if deep_crawl:
-            if deep_crawl == "bfs":
-                crawler_cfg.deep_crawl_strategy = BFSDeepCrawlStrategy(
-                    max_depth=3,
-                    max_pages=max_pages
-                )
-            elif deep_crawl == "dfs":
-                crawler_cfg.deep_crawl_strategy = DFSDeepCrawlStrategy(
-                    max_depth=3,
-                    max_pages=max_pages
-                )
-            elif deep_crawl == "best-first":
-                crawler_cfg.deep_crawl_strategy = BestFirstCrawlingStrategy(
-                    max_depth=3,
-                    max_pages=max_pages
-                )
-            
-            if verbose:
-                console.print(f"[green]Deep crawling enabled:[/green] {deep_crawl} strategy, max {max_pages} pages")
-
        config = get_global_config()
        
        browser_cfg.verbose = config.get("VERBOSE", False)
@@ -1196,60 +1170,39 @@ Always return valid, properly formatted JSON."""
            verbose
        )

-        # Handle deep crawl results (list) vs single result
-        if isinstance(result, list):
-            if len(result) == 0:
-                click.echo("No results found during deep crawling")
-                return
-            # Use the first result for question answering and output
-            main_result = result[0]
-            all_results = result
-        else:
-            # Single result from regular crawling
-            main_result = result
-            all_results = [result]
-
        # Handle question
        if question:
            provider, token = setup_llm_config()
-            markdown = main_result.markdown.raw_markdown
+            markdown = result.markdown.raw_markdown
            anyio.run(stream_llm_response, url, markdown, question, provider, token)
            return
        
        # Handle output
        if not output_file:
            if output == "all":
-                if isinstance(result, list):
-                    output_data = [r.model_dump() for r in all_results]
-                    click.echo(json.dumps(output_data, indent=2))
-                else:
-                    click.echo(json.dumps(main_result.model_dump(), indent=2))
+                click.echo(json.dumps(result.model_dump(), indent=2))
            elif output == "json":
-                print(main_result.extracted_content)
-                extracted_items = json.loads(main_result.extracted_content)
+                print(result.extracted_content)
+                extracted_items = json.loads(result.extracted_content)
                click.echo(json.dumps(extracted_items, indent=2))
                
            elif output in ["markdown", "md"]:
-                click.echo(main_result.markdown.raw_markdown)
+                click.echo(result.markdown.raw_markdown)
            elif output in ["markdown-fit", "md-fit"]:
-                click.echo(main_result.markdown.fit_markdown)
+                click.echo(result.markdown.fit_markdown)
        else:
            if output == "all":
                with open(output_file, "w") as f:
-                    if isinstance(result, list):
-                        output_data = [r.model_dump() for r in all_results]
-                        f.write(json.dumps(output_data, indent=2))
-                    else:
-                        f.write(json.dumps(main_result.model_dump(), indent=2))
+                    f.write(json.dumps(result.model_dump(), indent=2))
            elif output == "json":
                with open(output_file, "w") as f:
-                    f.write(main_result.extracted_content)
+                    f.write(result.extracted_content)
            elif output in ["markdown", "md"]:
                with open(output_file, "w") as f:
-                    f.write(main_result.markdown.raw_markdown)
+                    f.write(result.markdown.raw_markdown)
            elif output in ["markdown-fit", "md-fit"]:
                with open(output_file, "w") as f:
-                    f.write(main_result.markdown.fit_markdown)
+                    f.write(result.markdown.fit_markdown)
            
    except Exception as e:
        raise click.ClickException(str(e))
@@ -1401,11 +1354,9 @@ def profiles_cmd():
@click.option("--question", "-q", help="Ask a question about the crawled content")
@click.option("--verbose", "-v", is_flag=True)
@click.option("--profile", "-p", help="Use a specific browser profile (by name)")
-@click.option("--deep-crawl", type=click.Choice(["bfs", "dfs", "best-first"]), help="Enable deep crawling with specified strategy")
-@click.option("--max-pages", type=int, default=10, help="Maximum number of pages to crawl in deep crawl mode")
 def default(url: str, example: bool, browser_config: str, crawler_config: str, filter_config: str, 
        extraction_config: str, json_extract: str, schema: str, browser: Dict, crawler: Dict,
-        output: str, bypass_cache: bool, question: str, verbose: bool, profile: str, deep_crawl: str, max_pages: int):
+        output: str, bypass_cache: bool, question: str, verbose: bool, profile: str):
    """Crawl4AI CLI - Web content extraction tool

    Simple Usage:
@@ -1455,9 +1406,7 @@ def default(url: str, example: bool, browser_config: str, crawler_config: str, f
        bypass_cache=bypass_cache,
        question=question,
        verbose=verbose,
-        profile=profile,
-        deep_crawl=deep_crawl,
-        max_pages=max_pages
+        profile=profile
    )

 def main():
--- a/crawl4ai/content_scraping_strategy.py
+++ b/crawl4ai/content_scraping_strategy.py
@@ -98,20 +98,20 @@ class ContentScrapingStrategy(ABC):
        pass


-class LXMLWebScrapingStrategy(ContentScrapingStrategy):
+class WebScrapingStrategy(ContentScrapingStrategy):
    """
-    LXML-based implementation for fast web content scraping.
-    
-    This is the primary scraping strategy in Crawl4AI, providing high-performance
-    HTML parsing and content extraction using the lxml library.
-    
-    Note: WebScrapingStrategy is now an alias for this class to maintain
-    backward compatibility.
+    Class for web content scraping. Perhaps the most important class.
+
+    How it works:
+    1. Extract content from HTML using BeautifulSoup.
+    2. Clean the extracted content using a content cleaning strategy.
+    3. Filter the cleaned content using a content filtering strategy.
+    4. Generate markdown content from the filtered content.
+    5. Return the markdown content.
    """
+
    def __init__(self, logger=None):
        self.logger = logger
-        self.DIMENSION_REGEX = re.compile(r"(\d+)(\D*)")
-        self.BASE64_PATTERN = re.compile(r'data:image/[^;]+;base64,([^"]+)')

    def _log(self, level, message, tag="SCRAPE", **kwargs):
        """Helper method to safely use logger."""
@@ -132,7 +132,7 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):
            ScrapingResult: A structured result containing the scraped content.
        """
        actual_url = kwargs.get("redirected_url", url)
-        raw_result = self._scrap(actual_url, html, **kwargs)
+        raw_result = self._scrap(actual_url, html, is_async=False, **kwargs)
        if raw_result is None:
            return ScrapingResult(
                cleaned_html="",
@@ -196,9 +196,376 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):
        Returns:
            ScrapingResult: A structured result containing the scraped content.
        """
-        return await asyncio.to_thread(self.scrap, url, html, **kwargs)
+        return await asyncio.to_thread(self._scrap, url, html, **kwargs)

-    def process_element(self, url, element: lhtml.HtmlElement, **kwargs) -> Dict[str, Any]:
+    def is_data_table(self, table: Tag, **kwargs) -> bool:
+        """
+        Determine if a table element is a data table (not a layout table).
+
+        Args:
+            table (Tag): BeautifulSoup Tag representing a table element
+            **kwargs: Additional keyword arguments including table_score_threshold
+
+        Returns:
+            bool: True if the table is a data table, False otherwise
+        """
+        score = 0
+        
+        # Check for thead and tbody
+        has_thead = len(table.select('thead')) > 0
+        has_tbody = len(table.select('tbody')) > 0
+        if has_thead:
+            score += 2
+        if has_tbody:
+            score += 1
+            
+        # Check for th elements
+        th_count = len(table.select('th'))
+        if th_count > 0:
+            score += 2
+            if has_thead or len(table.select('tr:first-child th')) > 0:
+                score += 1
+                
+        # Check for nested tables
+        if len(table.select('table')) > 0:
+            score -= 3
+            
+        # Role attribute check
+        role = table.get('role', '').lower()
+        if role in {'presentation', 'none'}:
+            score -= 3
+            
+        # Column consistency
+        rows = table.select('tr')
+        if not rows:
+            return False
+            
+        col_counts = [len(row.select('td, th')) for row in rows]
+        avg_cols = sum(col_counts) / len(col_counts)
+        variance = sum((c - avg_cols)**2 for c in col_counts) / len(col_counts)
+        if variance < 1:
+            score += 2
+            
+        # Caption and summary
+        if table.select('caption'):
+            score += 2
+        if table.has_attr('summary') and table['summary']:
+            score += 1
+            
+        # Text density
+        total_text = sum(len(cell.get_text().strip()) for row in rows for cell in row.select('td, th'))
+        total_tags = sum(1 for _ in table.descendants if isinstance(_, Tag))
+        text_ratio = total_text / (total_tags + 1e-5)
+        if text_ratio > 20:
+            score += 3
+        elif text_ratio > 10:
+            score += 2
+            
+        # Data attributes
+        data_attrs = sum(1 for attr in table.attrs if attr.startswith('data-'))
+        score += data_attrs * 0.5
+        
+        # Size check
+        if avg_cols >= 2 and len(rows) >= 2:
+            score += 2
+            
+        threshold = kwargs.get('table_score_threshold', 7)
+        return score >= threshold
+    
+    def extract_table_data(self, table: Tag) -> dict:
+        """
+        Extract structured data from a table element.
+        
+        Args:
+            table (Tag): BeautifulSoup Tag representing a table element
+            
+        Returns:
+            dict: Dictionary containing table data (headers, rows, caption, summary)
+        """
+        caption_elem = table.select_one('caption')
+        caption = caption_elem.get_text().strip() if caption_elem else ""
+        summary = table.get('summary', '').strip()
+        
+        # Extract headers with colspan handling
+        headers = []
+        thead_rows = table.select('thead tr')
+        if thead_rows:
+            header_cells = thead_rows[0].select('th')
+            for cell in header_cells:
+                text = cell.get_text().strip()
+                colspan = int(cell.get('colspan', 1))
+                headers.extend([text] * colspan)
+        else:
+            first_row = table.select('tr:first-child')
+            if first_row:
+                for cell in first_row[0].select('th, td'):
+                    text = cell.get_text().strip()
+                    colspan = int(cell.get('colspan', 1))
+                    headers.extend([text] * colspan)
+        
+        # Extract rows with colspan handling
+        rows = []
+        all_rows = table.select('tr')
+        thead = table.select_one('thead')
+        tbody_rows = []
+
+        if thead:
+            thead_rows = thead.select('tr')
+            tbody_rows = [row for row in all_rows if row not in thead_rows]
+        else:
+            if all_rows and all_rows[0].select('th'):
+                tbody_rows = all_rows[1:]
+            else:
+                tbody_rows = all_rows
+                
+        for row in tbody_rows:        
+        # for row in table.select('tr:not(:has(ancestor::thead))'):
+            row_data = []
+            for cell in row.select('td'):
+                text = cell.get_text().strip()
+                colspan = int(cell.get('colspan', 1))
+                row_data.extend([text] * colspan)
+            if row_data:
+                rows.append(row_data)
+                
+        # Align rows with headers
+        max_columns = len(headers) if headers else (max(len(row) for row in rows) if rows else 0)
+        aligned_rows = []
+        for row in rows:
+            aligned = row[:max_columns] + [''] * (max_columns - len(row))
+            aligned_rows.append(aligned)
+            
+        if not headers:
+            headers = [f"Column {i+1}" for i in range(max_columns)]
+            
+        return {
+            "headers": headers,
+            "rows": aligned_rows,
+            "caption": caption,
+            "summary": summary,
+        }
+    
+    def flatten_nested_elements(self, node):
+        """
+        Flatten nested elements in a HTML tree.
+
+        Args:
+            node (Tag): The root node of the HTML tree.
+
+        Returns:
+            Tag: The flattened HTML tree.
+        """
+        if isinstance(node, NavigableString):
+            return node
+        if (
+            len(node.contents) == 1
+            and isinstance(node.contents[0], Tag)
+            and node.contents[0].name == node.name
+        ):
+            return self.flatten_nested_elements(node.contents[0])
+        node.contents = [self.flatten_nested_elements(child) for child in node.contents]
+        return node
+
+    def find_closest_parent_with_useful_text(self, tag, **kwargs):
+        """
+        Find the closest parent with useful text.
+
+        Args:
+            tag (Tag): The starting tag to search from.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            Tag: The closest parent with useful text, or None if not found.
+        """
+        image_description_min_word_threshold = kwargs.get(
+            "image_description_min_word_threshold", IMAGE_DESCRIPTION_MIN_WORD_THRESHOLD
+        )
+        current_tag = tag
+        while current_tag:
+            current_tag = current_tag.parent
+            # Get the text content of the parent tag
+            if current_tag:
+                text_content = current_tag.get_text(separator=" ", strip=True)
+                # Check if the text content has at least word_count_threshold
+                if len(text_content.split()) >= image_description_min_word_threshold:
+                    return text_content
+        return None
+
+    def remove_unwanted_attributes(
+        self, element, important_attrs, keep_data_attributes=False
+    ):
+        """
+        Remove unwanted attributes from an HTML element.
+
+        Args:
+            element (Tag): The HTML element to remove attributes from.
+            important_attrs (list): List of important attributes to keep.
+            keep_data_attributes (bool): Whether to keep data attributes.
+
+        Returns:
+            None
+        """
+        attrs_to_remove = []
+        for attr in element.attrs:
+            if attr not in important_attrs:
+                if keep_data_attributes:
+                    if not attr.startswith("data-"):
+                        attrs_to_remove.append(attr)
+                else:
+                    attrs_to_remove.append(attr)
+
+        for attr in attrs_to_remove:
+            del element[attr]
+
+    def process_image(self, img, url, index, total_images, **kwargs):
+        """
+        Process an image element.
+
+        How it works:
+        1. Check if the image has valid display and inside undesired html elements.
+        2. Score an image for it's usefulness.
+        3. Extract image file metadata to extract size and extension.
+        4. Generate a dictionary with the processed image information.
+        5. Return the processed image information.
+
+        Args:
+            img (Tag): The image element to process.
+            url (str): The URL of the page containing the image.
+            index (int): The index of the image in the list of images.
+            total_images (int): The total number of images in the list.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            dict: A dictionary containing the processed image information.
+        """
+        # parse_srcset = lambda s: [{'url': u.strip().split()[0], 'width': u.strip().split()[-1].rstrip('w')
+        #                 if ' ' in u else None}
+        #                 for u in [f"http{p}" for p in s.split("http") if p]]
+
+        # Constants for checks
+        classes_to_check = frozenset(["button", "icon", "logo"])
+        tags_to_check = frozenset(["button", "input"])
+        image_formats = frozenset(["jpg", "jpeg", "png", "webp", "avif", "gif"])
+
+        # Pre-fetch commonly used attributes
+        style = img.get("style", "")
+        alt = img.get("alt", "")
+        src = img.get("src", "")
+        data_src = img.get("data-src", "")
+        srcset = img.get("srcset", "")
+        data_srcset = img.get("data-srcset", "")
+        width = img.get("width")
+        height = img.get("height")
+        parent = img.parent
+        parent_classes = parent.get("class", [])
+
+        # Quick validation checks
+        if (
+            "display:none" in style
+            or parent.name in tags_to_check
+            or any(c in cls for c in parent_classes for cls in classes_to_check)
+            or any(c in src for c in classes_to_check)
+            or any(c in alt for c in classes_to_check)
+        ):
+            return None
+
+        # Quick score calculation
+        score = 0
+        if width and width.isdigit():
+            width_val = int(width)
+            score += 1 if width_val > 150 else 0
+        if height and height.isdigit():
+            height_val = int(height)
+            score += 1 if height_val > 150 else 0
+        if alt:
+            score += 1
+        score += index / total_images < 0.5
+
+        # image_format = ''
+        # if "data:image/" in src:
+        #     image_format = src.split(',')[0].split(';')[0].split('/')[1].split(';')[0]
+        # else:
+        #     image_format = os.path.splitext(src)[1].lower().strip('.').split('?')[0]
+
+        # if image_format in ('jpg', 'png', 'webp', 'avif'):
+        #     score += 1
+
+        # Check for image format in all possible sources
+        def has_image_format(url):
+            return any(fmt in url.lower() for fmt in image_formats)
+
+        # Score for having proper image sources
+        if any(has_image_format(url) for url in [src, data_src, srcset, data_srcset]):
+            score += 1
+        if srcset or data_srcset:
+            score += 1
+        if img.find_parent("picture"):
+            score += 1
+
+        # Detect format from any available source
+        detected_format = None
+        for url in [src, data_src, srcset, data_srcset]:
+            if url:
+                format_matches = [fmt for fmt in image_formats if fmt in url.lower()]
+                if format_matches:
+                    detected_format = format_matches[0]
+                    break
+
+        if score <= kwargs.get("image_score_threshold", IMAGE_SCORE_THRESHOLD):
+            return None
+
+        # Use set for deduplication
+        unique_urls = set()
+        image_variants = []
+
+        # Generate a unique group ID for this set of variants
+        group_id = index
+
+        # Base image info template
+        base_info = {
+            "alt": alt,
+            "desc": self.find_closest_parent_with_useful_text(img, **kwargs),
+            "score": score,
+            "type": "image",
+            "group_id": group_id,  # Group ID for this set of variants
+            "format": detected_format,
+        }
+
+        # Inline function for adding variants
+        def add_variant(src, width=None):
+            if src and not src.startswith("data:") and src not in unique_urls:
+                unique_urls.add(src)
+                image_variants.append({**base_info, "src": src, "width": width})
+
+        # Process all sources
+        add_variant(src)
+        add_variant(data_src)
+
+        # Handle srcset and data-srcset in one pass
+        for attr in ("srcset", "data-srcset"):
+            if value := img.get(attr):
+                for source in parse_srcset(value):
+                    add_variant(source["url"], source["width"])
+
+        # Quick picture element check
+        if picture := img.find_parent("picture"):
+            for source in picture.find_all("source"):
+                if srcset := source.get("srcset"):
+                    for src in parse_srcset(srcset):
+                        add_variant(src["url"], src["width"])
+
+        # Framework-specific attributes in one pass
+        for attr, value in img.attrs.items():
+            if (
+                attr.startswith("data-")
+                and ("src" in attr or "srcset" in attr)
+                and "http" in value
+            ):
+                add_variant(value)
+
+        return image_variants if image_variants else None
+
+    def process_element(self, url, element: PageElement, **kwargs) -> Dict[str, Any]:
        """
        Process an HTML element.

@@ -210,7 +577,7 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):

        Args:
            url (str): The URL of the page containing the element.
-            element (lhtml.HtmlElement): The HTML element to process.
+            element (Tag): The HTML element to process.
            **kwargs: Additional keyword arguments.

        Returns:
@@ -228,6 +595,514 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):
            "external_links_dict": external_links_dict,
        }

+    def _process_element(
+        self,
+        url,
+        element: PageElement,
+        media: Dict[str, Any],
+        internal_links_dict: Dict[str, Any],
+        external_links_dict: Dict[str, Any],
+        **kwargs,
+    ) -> bool:
+        """
+        Process an HTML element.
+        """
+        try:
+            if isinstance(element, NavigableString):
+                if isinstance(element, Comment):
+                    element.extract()
+                return False
+
+            # if element.name == 'img':
+            #     process_image(element, url, 0, 1)
+            #     return True
+            base_domain = kwargs.get("base_domain", get_base_domain(url))
+
+            if element.name in ["script", "style", "link", "meta", "noscript"]:
+                element.decompose()
+                return False
+
+            keep_element = False
+            # Special case for table elements - always preserve structure
+            if element.name in ["tr", "td", "th"]:
+                keep_element = True
+
+            exclude_domains = kwargs.get("exclude_domains", [])
+            # exclude_social_media_domains = kwargs.get('exclude_social_media_domains', set(SOCIAL_MEDIA_DOMAINS))
+            # exclude_social_media_domains = SOCIAL_MEDIA_DOMAINS + kwargs.get('exclude_social_media_domains', [])
+            # exclude_social_media_domains = list(set(exclude_social_media_domains))
+
+            try:
+                if element.name == "a" and element.get("href"):
+                    href = element.get("href", "").strip()
+                    if not href:  # Skip empty hrefs
+                        return False
+
+                    # url_base = url.split("/")[2]
+
+                    # Normalize the URL
+                    try:
+                        normalized_href = normalize_url(href, url)
+                    except ValueError:
+                        # logging.warning(f"Invalid URL format: {href}, Error: {str(e)}")
+                        return False
+
+                    link_data = {
+                        "href": normalized_href,
+                        "text": element.get_text().strip(),
+                        "title": element.get("title", "").strip(),
+                        "base_domain": base_domain,
+                    }
+
+                    is_external = is_external_url(normalized_href, base_domain)
+
+                    keep_element = True
+
+                    # Handle external link exclusions
+                    if is_external:
+                        link_base_domain = get_base_domain(normalized_href)
+                        link_data["base_domain"] = link_base_domain
+                        if kwargs.get("exclude_external_links", False):
+                            element.decompose()
+                            return False
+                        # elif kwargs.get('exclude_social_media_links', False):
+                        #     if link_base_domain in exclude_social_media_domains:
+                        #         element.decompose()
+                        #         return False
+                        # if any(domain in normalized_href.lower() for domain in exclude_social_media_domains):
+                        #     element.decompose()
+                        #     return False
+                        elif exclude_domains:
+                            if link_base_domain in exclude_domains:
+                                element.decompose()
+                                return False
+                            # if any(domain in normalized_href.lower() for domain in kwargs.get('exclude_domains', [])):
+                            #     element.decompose()
+                            #     return False
+
+                    if is_external:
+                        if normalized_href not in external_links_dict:
+                            external_links_dict[normalized_href] = link_data
+                    else:
+                        if kwargs.get("exclude_internal_links", False):
+                            element.decompose()
+                            return False
+                        if normalized_href not in internal_links_dict:
+                            internal_links_dict[normalized_href] = link_data
+
+            except Exception as e:
+                raise Exception(f"Error processing links: {str(e)}")
+
+            try:
+                if element.name == "img":
+                    potential_sources = [
+                        "src",
+                        "data-src",
+                        "srcset" "data-lazy-src",
+                        "data-original",
+                    ]
+                    src = element.get("src", "")
+                    while not src and potential_sources:
+                        src = element.get(potential_sources.pop(0), "")
+                    if not src:
+                        element.decompose()
+                        return False
+
+                    # If it is srcset pick up the first image
+                    if "srcset" in element.attrs:
+                        src = element.attrs["srcset"].split(",")[0].split(" ")[0]
+
+                    # If image src is internal, then skip
+                    if not is_external_url(src, base_domain):
+                        return True
+
+                    image_src_base_domain = get_base_domain(src)
+
+                    # Check flag if we should remove external images
+                    if kwargs.get("exclude_external_images", False):
+                        # Handle relative URLs (which are always from the same domain)
+                        if not src.startswith('http') and not src.startswith('//'):
+                            return True  # Keep relative URLs
+                        
+                        # For absolute URLs, compare the base domains using the existing function
+                        src_base_domain = get_base_domain(src)
+                        url_base_domain = get_base_domain(url)
+                        
+                        # If the domains don't match and both are valid, the image is external
+                        if src_base_domain and url_base_domain and src_base_domain != url_base_domain:
+                            element.decompose()
+                            return False
+
+                    # if kwargs.get('exclude_social_media_links', False):
+                    #     if image_src_base_domain in exclude_social_media_domains:
+                    #         element.decompose()
+                    #         return False
+                    # src_url_base = src.split('/')[2]
+                    # url_base = url.split('/')[2]
+                    # if any(domain in src for domain in exclude_social_media_domains):
+                    #     element.decompose()
+                    #     return False
+
+                    # Handle exclude domains
+                    if exclude_domains:
+                        if image_src_base_domain in exclude_domains:
+                            element.decompose()
+                            return False
+                        # if any(domain in src for domain in kwargs.get('exclude_domains', [])):
+                        #     element.decompose()
+                        #     return False
+
+                    return True  # Always keep image elements
+            except Exception:
+                raise "Error processing images"
+
+            # Check if flag to remove all forms is set
+            if kwargs.get("remove_forms", False) and element.name == "form":
+                element.decompose()
+                return False
+
+            if element.name in ["video", "audio"]:
+                media[f"{element.name}s"].append(
+                    {
+                        "src": element.get("src"),
+                        "alt": element.get("alt"),
+                        "type": element.name,
+                        "description": self.find_closest_parent_with_useful_text(
+                            element, **kwargs
+                        ),
+                    }
+                )
+                source_tags = element.find_all("source")
+                for source_tag in source_tags:
+                    media[f"{element.name}s"].append(
+                        {
+                            "src": source_tag.get("src"),
+                            "alt": element.get("alt"),
+                            "type": element.name,
+                            "description": self.find_closest_parent_with_useful_text(
+                                element, **kwargs
+                            ),
+                        }
+                    )
+                return True  # Always keep video and audio elements
+
+            if element.name in ONLY_TEXT_ELIGIBLE_TAGS:
+                if kwargs.get("only_text", False):
+                    element.replace_with(element.get_text())
+
+            try:
+                self.remove_unwanted_attributes(
+                    element, IMPORTANT_ATTRS + kwargs.get("keep_attrs", []) , kwargs.get("keep_data_attributes", False)
+                )
+            except Exception as e:
+                # print('Error removing unwanted attributes:', str(e))
+                self._log(
+                    "error",
+                    message="Error removing unwanted attributes: {error}",
+                    tag="SCRAPE",
+                    params={"error": str(e)},
+                )
+            # Process children
+            for child in list(element.children):
+                if isinstance(child, NavigableString) and not isinstance(
+                    child, Comment
+                ):
+                    if len(child.strip()) > 0:
+                        keep_element = True
+                else:
+                    if self._process_element(
+                        url,
+                        child,
+                        media,
+                        internal_links_dict,
+                        external_links_dict,
+                        **kwargs,
+                    ):
+                        keep_element = True
+
+            # Check word count
+            word_count_threshold = kwargs.get(
+                "word_count_threshold", MIN_WORD_THRESHOLD
+            )
+            if not keep_element:
+                word_count = len(element.get_text(strip=True).split())
+                keep_element = word_count >= word_count_threshold
+
+            if not keep_element:
+                element.decompose()
+
+            return keep_element
+        except Exception as e:
+            # print('Error processing element:', str(e))
+            self._log(
+                "error",
+                message="Error processing element: {error}",
+                tag="SCRAPE",
+                params={"error": str(e)},
+            )
+            return False
+
+    def _scrap(
+        self,
+        url: str,
+        html: str,
+        word_count_threshold: int = MIN_WORD_THRESHOLD,
+        css_selector: str = None,
+        target_elements: List[str] = None,
+        **kwargs,
+    ) -> Dict[str, Any]:
+        """
+        Extract content from HTML using BeautifulSoup.
+
+        Args:
+            url (str): The URL of the page to scrape.
+            html (str): The HTML content of the page to scrape.
+            word_count_threshold (int): The minimum word count threshold for content extraction.
+            css_selector (str): The CSS selector to use for content extraction.
+            **kwargs: Additional keyword arguments.
+
+        Returns:
+            dict: A dictionary containing the extracted content.
+        """
+        success = True
+        if not html:
+            return None
+
+        parser_type = kwargs.get("parser", "lxml")
+        soup = BeautifulSoup(html, parser_type)
+        body = soup.body
+        if body is None:
+            raise Exception("'<body>' tag is not found in fetched html. Consider adding wait_for=\"css:body\" to wait for body tag to be loaded into DOM.")
+        base_domain = get_base_domain(url)
+        
+        # Early removal of all images if exclude_all_images is set
+        # This happens before any processing to minimize memory usage
+        if kwargs.get("exclude_all_images", False):
+            for img in body.find_all('img'):
+                img.decompose()
+
+        try:
+            meta = extract_metadata("", soup)
+        except Exception as e:
+            self._log(
+                "error",
+                message="Error extracting metadata: {error}",
+                tag="SCRAPE",
+                params={"error": str(e)},
+            )
+            meta = {}
+
+        # Handle tag-based removal first - faster than CSS selection
+        excluded_tags = set(kwargs.get("excluded_tags", []) or [])
+        if excluded_tags:
+            for element in body.find_all(lambda tag: tag.name in excluded_tags):
+                element.extract()
+
+        # Handle CSS selector-based removal
+        excluded_selector = kwargs.get("excluded_selector", "")
+        if excluded_selector:
+            is_single_selector = (
+                "," not in excluded_selector and " " not in excluded_selector
+            )
+            if is_single_selector:
+                while element := body.select_one(excluded_selector):
+                    element.extract()
+            else:
+                for element in body.select(excluded_selector):
+                    element.extract()
+
+        content_element = None
+        if target_elements:
+            try:
+                for_content_targeted_element = []
+                for target_element in target_elements:
+                    for_content_targeted_element.extend(body.select(target_element))
+                content_element = soup.new_tag("div")
+                for el in for_content_targeted_element:
+                    content_element.append(copy.deepcopy(el))
+            except Exception as e:
+                self._log("error", f"Error with target element detection: {str(e)}", "SCRAPE")
+                return None
+        else:
+            content_element = body     
+
+        kwargs["exclude_social_media_domains"] = set(
+            kwargs.get("exclude_social_media_domains", []) + SOCIAL_MEDIA_DOMAINS
+        )
+        kwargs["exclude_domains"] = set(kwargs.get("exclude_domains", []))
+        if kwargs.get("exclude_social_media_links", False):
+            kwargs["exclude_domains"] = kwargs["exclude_domains"].union(
+                kwargs["exclude_social_media_domains"]
+            )
+
+        result_obj = self.process_element(
+            url,
+            body,
+            word_count_threshold=word_count_threshold,
+            base_domain=base_domain,
+            **kwargs,
+        )
+
+        links = {"internal": [], "external": []}
+        media = result_obj["media"]
+        internal_links_dict = result_obj["internal_links_dict"]
+        external_links_dict = result_obj["external_links_dict"]
+
+        # Update the links dictionary with unique links
+        links["internal"] = list(internal_links_dict.values())
+        links["external"] = list(external_links_dict.values())
+        
+        # Extract head content for links if configured
+        link_preview_config = kwargs.get("link_preview_config")
+        if link_preview_config is not None:
+            try:
+                import asyncio
+                from .link_preview import LinkPreview
+                from .models import Links, Link
+                
+                verbose = link_preview_config.verbose
+                
+                if verbose:
+                    self._log("info", "Starting link head extraction for {internal} internal and {external} external links",
+                              params={"internal": len(links["internal"]), "external": len(links["external"])}, tag="LINK_EXTRACT")
+                
+                # Convert dict links to Link objects
+                internal_links = [Link(**link_data) for link_data in links["internal"]]
+                external_links = [Link(**link_data) for link_data in links["external"]]
+                links_obj = Links(internal=internal_links, external=external_links)
+                
+                # Create a config object for LinkPreview  
+                class TempCrawlerRunConfig:
+                    def __init__(self, link_config, score_links):
+                        self.link_preview_config = link_config
+                        self.score_links = score_links
+                
+                config = TempCrawlerRunConfig(link_preview_config, kwargs.get("score_links", False))
+                
+                # Extract head content (run async operation in sync context)
+                async def extract_links():
+                    async with LinkPreview(self.logger) as extractor:
+                        return await extractor.extract_link_heads(links_obj, config)
+                
+                # Run the async operation
+                try:
+                    # Check if we're already in an async context
+                    loop = asyncio.get_running_loop()
+                    # If we're in an async context, we need to run in a thread
+                    import concurrent.futures
+                    with concurrent.futures.ThreadPoolExecutor() as executor:
+                        future = executor.submit(asyncio.run, extract_links())
+                        updated_links = future.result()
+                except RuntimeError:
+                    # No running loop, we can use asyncio.run directly
+                    updated_links = asyncio.run(extract_links())
+                
+                # Convert back to dict format
+                links["internal"] = [link.dict() for link in updated_links.internal]
+                links["external"] = [link.dict() for link in updated_links.external]
+                
+                if verbose:
+                    successful_internal = len([l for l in updated_links.internal if l.head_extraction_status == "valid"])
+                    successful_external = len([l for l in updated_links.external if l.head_extraction_status == "valid"])
+                    self._log("info", "Link head extraction completed: {internal_success}/{internal_total} internal, {external_success}/{external_total} external",
+                              params={
+                                  "internal_success": successful_internal,
+                                  "internal_total": len(updated_links.internal),
+                                  "external_success": successful_external,
+                                  "external_total": len(updated_links.external)
+                              }, tag="LINK_EXTRACT")
+                else:
+                    self._log("info", "Link head extraction completed successfully", tag="LINK_EXTRACT")
+                
+            except Exception as e:
+                self._log("error", f"Link head extraction failed: {str(e)}", tag="LINK_EXTRACT")
+                # Continue with original links if extraction fails
+
+        # # Process images using ThreadPoolExecutor
+        imgs = body.find_all("img")
+
+        media["images"] = [
+            img
+            for result in (
+                self.process_image(img, url, i, len(imgs), **kwargs)
+                for i, img in enumerate(imgs)
+            )
+            if result is not None
+            for img in result
+        ]
+        
+        # Process tables if not excluded
+        excluded_tags = set(kwargs.get("excluded_tags", []) or [])
+        if 'table' not in excluded_tags:
+            tables = body.find_all('table')
+            for table in tables:
+                if self.is_data_table(table, **kwargs):
+                    table_data = self.extract_table_data(table)
+                    media["tables"].append(table_data)
+
+        body = self.flatten_nested_elements(body)
+        base64_pattern = re.compile(r'data:image/[^;]+;base64,([^"]+)')
+        for img in imgs:
+            src = img.get("src", "")
+            if base64_pattern.match(src):
+                # Replace base64 data with empty string
+                img["src"] = base64_pattern.sub("", src)
+
+        str_body = ""
+        try:
+            str_body = content_element.encode_contents().decode("utf-8")
+        except Exception:
+            # Reset body to the original HTML
+            success = False
+            body = BeautifulSoup(html, "html.parser")
+
+            # Create a new div with a special ID
+            error_div = body.new_tag("div", id="crawl4ai_error_message")
+            error_div.string = """
+            Crawl4AI Error: This page is not fully supported.
+            
+            Possible reasons:
+            1. The page may have restrictions that prevent crawling.
+            2. The page might not be fully loaded.
+            
+            Suggestions:
+            - Try calling the crawl function with these parameters:
+            magic=True,
+            - Set headless=False to visualize what's happening on the page.
+            
+            If the issue persists, please check the page's structure and any potential anti-crawling measures.
+            """
+
+            # Append the error div to the body
+            body.append(error_div)
+            str_body = body.encode_contents().decode("utf-8")
+
+            print(
+                "[LOG] 😧 Error: After processing the crawled HTML and removing irrelevant tags, nothing was left in the page. Check the markdown for further details."
+            )
+            self._log(
+                "error",
+                message="After processing the crawled HTML and removing irrelevant tags, nothing was left in the page. Check the markdown for further details.",
+                tag="SCRAPE",
+            )
+
+        cleaned_html = str_body.replace("\n\n", "\n").replace("  ", " ")
+
+        return {
+            "cleaned_html": cleaned_html,
+            "success": success,
+            "media": media,
+            "links": links,
+            "metadata": meta,
+        }
+
+
+class LXMLWebScrapingStrategy(WebScrapingStrategy):
+    def __init__(self, logger=None):
+        super().__init__(logger)
+        self.DIMENSION_REGEX = re.compile(r"(\d+)(\D*)")
+        self.BASE64_PATTERN = re.compile(r'data:image/[^;]+;base64,([^"]+)')
+
    def _process_element(
        self,
        url: str,
@@ -270,10 +1145,10 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):
                        link_data["intrinsic_score"] = intrinsic_score
                    except Exception:
                        # Fail gracefully - assign default score
-                        link_data["intrinsic_score"] = 0
+                        link_data["intrinsic_score"] = float('inf')
                else:
                    # No scoring enabled - assign infinity (all links equal priority)
-                    link_data["intrinsic_score"] = 0
+                    link_data["intrinsic_score"] = float('inf')

                is_external = is_external_url(normalized_href, base_domain)
                if is_external:
@@ -987,7 +1862,3 @@ class LXMLWebScrapingStrategy(ContentScrapingStrategy):
                "links": {"internal": [], "external": []},
                "metadata": {},
            }
-
-
-# Backward compatibility alias
-WebScrapingStrategy = LXMLWebScrapingStrategy
--- a/crawl4ai/install.py
+++ b/crawl4ai/install.py
@@ -119,32 +119,6 @@ def install_playwright():
        logger.warning(
            f"Please run '{sys.executable} -m playwright install --with-deps' manually after the installation."
        )
-    
-    # Install Patchright browsers for undetected browser support
-    logger.info("Installing Patchright browsers for undetected mode...", tag="INIT")
-    try:
-        subprocess.check_call(
-            [
-                sys.executable,
-                "-m",
-                "patchright",
-                "install",
-                "--with-deps",
-                "--force",
-                "chromium",
-            ]
-        )
-        logger.success(
-            "Patchright installation completed successfully.", tag="COMPLETE"
-        )
-    except subprocess.CalledProcessError:
-        logger.warning(
-            f"Please run '{sys.executable} -m patchright install --with-deps' manually after the installation."
-        )
-    except Exception:
-        logger.warning(
-            f"Please run '{sys.executable} -m patchright install --with-deps' manually after the installation."
-        )


 def run_migration():
--- a/crawl4ai/legacy/web_crawler.py
+++ b/crawl4ai/legacy/web_crawler.py
@@ -11,7 +11,7 @@ from .extraction_strategy import *
 from .crawler_strategy import *
 from typing import List
 from concurrent.futures import ThreadPoolExecutor
-from ..content_scraping_strategy import LXMLWebScrapingStrategy as WebScrapingStrategy
+from .content_scraping_strategy import WebScrapingStrategy
 from .config import *
 import warnings
 import json
--- a/crawl4ai/memory_utils.py
+++ b/crawl4ai/memory_utils.py
@@ -1,79 +0,0 @@
-import psutil
-import platform
-import subprocess
-from typing import Tuple
-
-
-def get_true_available_memory_gb() -> float:
-    """Get truly available memory including inactive pages (cross-platform)"""
-    vm = psutil.virtual_memory()
-
-    if platform.system() == 'Darwin':  # macOS
-        # On macOS, we need to include inactive memory too
-        try:
-            # Use vm_stat to get accurate values
-            result = subprocess.run(['vm_stat'], capture_output=True, text=True)
-            lines = result.stdout.split('\n')
-
-            page_size = 16384  # macOS page size
-            pages = {}
-
-            for line in lines:
-                if 'Pages free:' in line:
-                    pages['free'] = int(line.split()[-1].rstrip('.'))
-                elif 'Pages inactive:' in line:
-                    pages['inactive'] = int(line.split()[-1].rstrip('.'))
-                elif 'Pages speculative:' in line:
-                    pages['speculative'] = int(line.split()[-1].rstrip('.'))
-                elif 'Pages purgeable:' in line:
-                    pages['purgeable'] = int(line.split()[-1].rstrip('.'))
-
-            # Calculate total available (free + inactive + speculative + purgeable)
-            total_available_pages = (
-                pages.get('free', 0) + 
-                pages.get('inactive', 0) + 
-                pages.get('speculative', 0) + 
-                pages.get('purgeable', 0)
-            )
-            available_gb = (total_available_pages * page_size) / (1024**3)
-
-            return available_gb
-        except:
-            # Fallback to psutil
-            return vm.available / (1024**3)
-    else:
-        # For Windows and Linux, psutil.available is accurate
-        return vm.available / (1024**3)
-
-
-def get_true_memory_usage_percent() -> float:
-    """
-    Get memory usage percentage that accounts for platform differences.
-    
-    Returns:
-        float: Memory usage percentage (0-100)
-    """
-    vm = psutil.virtual_memory()
-    total_gb = vm.total / (1024**3)
-    available_gb = get_true_available_memory_gb()
-    
-    # Calculate used percentage based on truly available memory
-    used_percent = 100.0 * (total_gb - available_gb) / total_gb
-    
-    # Ensure it's within valid range
-    return max(0.0, min(100.0, used_percent))
-
-
-def get_memory_stats() -> Tuple[float, float, float]:
-    """
-    Get comprehensive memory statistics.
-    
-    Returns:
-        Tuple[float, float, float]: (used_percent, available_gb, total_gb)
-    """
-    vm = psutil.virtual_memory()
-    total_gb = vm.total / (1024**3)
-    available_gb = get_true_available_memory_gb()
-    used_percent = get_true_memory_usage_percent()
-    
-    return used_percent, available_gb, total_gb
--- a/crawl4ai/prompts.py
+++ b/crawl4ai/prompts.py
@@ -1056,7 +1056,7 @@ Your output must:
 </output_requirements>
 """

-GENERATE_SCRIPT_PROMPT = r"""You are a world-class browser automation specialist. Your sole purpose is to convert a natural language objective and a snippet of HTML into the most **efficient, robust, and simple** script possible to prepare a web page for data extraction.
+GENERATE_SCRIPT_PROMPT = """You are a world-class browser automation specialist. Your sole purpose is to convert a natural language objective and a snippet of HTML into the most **efficient, robust, and simple** script possible to prepare a web page for data extraction.

 Your scripts run **before the crawl** to handle dynamic content, user interactions, and other obstacles. You are a master of two tools: raw **JavaScript** and the high-level **Crawl4ai Script (c4a)**.

--- a/crawl4ai/types.py
+++ b/crawl4ai/types.py
@@ -23,9 +23,8 @@ SeedingConfig = Union['SeedingConfigType']

 # Content scraping types
 ContentScrapingStrategy = Union['ContentScrapingStrategyType']
+WebScrapingStrategy = Union['WebScrapingStrategyType']
 LXMLWebScrapingStrategy = Union['LXMLWebScrapingStrategyType']
-# Backward compatibility alias
-WebScrapingStrategy = Union['LXMLWebScrapingStrategyType']

 # Proxy types
 ProxyRotationStrategy = Union['ProxyRotationStrategyType']
@@ -115,6 +114,7 @@ if TYPE_CHECKING:
    # Content scraping imports
    from .content_scraping_strategy import (
        ContentScrapingStrategy as ContentScrapingStrategyType,
+        WebScrapingStrategy as WebScrapingStrategyType,
        LXMLWebScrapingStrategy as LXMLWebScrapingStrategyType,
    )
    
--- a/crawl4ai/utils.py
+++ b/crawl4ai/utils.py
@@ -1517,29 +1517,8 @@ def extract_metadata_using_lxml(html, doc=None):
    head = head[0]

    # Title - using XPath
-    # title = head.xpath(".//title/text()")
-    # metadata["title"] = title[0].strip() if title else None
-
-    # === Title Extraction - New Approach ===
-    # Attempt to extract <title> using XPath
    title = head.xpath(".//title/text()")
-    title = title[0] if title else None
-
-    # Fallback: Use .find() in case XPath fails due to malformed HTML
-    if not title:
-        title_el = doc.find(".//title")
-        title = title_el.text if title_el is not None else None
-
-    # Final fallback: Use OpenGraph or Twitter title if <title> is missing or empty
-    if not title:
-        title_candidates = (
-            doc.xpath("//meta[@property='og:title']/@content") or
-            doc.xpath("//meta[@name='twitter:title']/@content")
-        )
-        title = title_candidates[0] if title_candidates else None
-
-    # Strip and assign title
-    metadata["title"] = title.strip() if title else None
+    metadata["title"] = title[0].strip() if title else None

    # Meta description - using XPath with multiple attribute conditions
    description = head.xpath('.//meta[@name="description"]/@content')
@@ -3363,13 +3342,7 @@ async def get_text_embeddings(
    # Default: use sentence-transformers
    else:
        # Lazy load to avoid importing heavy libraries unless needed
-        try:
-            from sentence_transformers import SentenceTransformer
-        except ImportError:
-            raise ImportError(
-                "sentence-transformers is required for local embeddings. "
-                "Install it with: pip install 'crawl4ai[transformer]' or pip install sentence-transformers"
-            )
+        from sentence_transformers import SentenceTransformer
        
        # Cache the model in function attribute to avoid reloading
        if not hasattr(get_text_embeddings, '_models'):
--- a/deploy/docker/.llm.env.example
+++ b/deploy/docker/.llm.env.example
@@ -5,9 +5,4 @@ ANTHROPIC_API_KEY=your_anthropic_key_here
 GROQ_API_KEY=your_groq_key_here
 TOGETHER_API_KEY=your_together_key_here
 MISTRAL_API_KEY=your_mistral_key_here
-GEMINI_API_TOKEN=your_gemini_key_here
-
-# Optional: Override the default LLM provider
-# Examples: "openai/gpt-4", "anthropic/claude-3-opus", "deepseek/chat", etc.
-# If not set, uses the provider specified in config.yml (default: openai/gpt-4o-mini)
-# LLM_PROVIDER=anthropic/claude-3-opus
+GEMINI_API_TOKEN=your_gemini_key_here
--- a/deploy/docker/README.md
+++ b/deploy/docker/README.md
@@ -154,29 +154,6 @@ cp deploy/docker/.llm.env.example .llm.env
 # Now edit .llm.env and add your API keys
 ```

-**Flexible LLM Provider Configuration:**
-
-The Docker setup now supports flexible LLM provider configuration through three methods:
-
-1. **Environment Variable** (Highest Priority): Set `LLM_PROVIDER` to override the default
-   ```bash
-   export LLM_PROVIDER="anthropic/claude-3-opus"
-   # Or in your .llm.env file:
-   # LLM_PROVIDER=anthropic/claude-3-opus
-   ```
-
-2. **API Request Parameter**: Specify provider per request
-   ```json
-   {
-     "url": "https://example.com",
-     "provider": "groq/mixtral-8x7b"
-   }
-   ```
-
-3. **Config File Default**: Falls back to `config.yml` (default: `openai/gpt-4o-mini`)
-
-The system automatically selects the appropriate API key based on the provider.
-
 #### 3. Build and Run with Compose

 The `docker-compose.yml` file in the project root provides a simplified approach that automatically handles architecture detection using buildx.
@@ -691,7 +668,7 @@ app:

 # Default LLM Configuration
 llm:
-  provider: "openai/gpt-4o-mini"  # Can be overridden by LLM_PROVIDER env var
+  provider: "openai/gpt-4o-mini"
  api_key_env: "OPENAI_API_KEY"
  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored

--- a/deploy/docker/api.py
+++ b/deploy/docker/api.py
@@ -5,7 +5,6 @@ from typing import List, Tuple, Dict
 from functools import partial
 from uuid import uuid4
 from datetime import datetime
-from base64 import b64encode

 import logging
 from typing import Optional, AsyncGenerator
@@ -40,9 +39,7 @@ from utils import (
    get_base_url,
    is_task_id,
    should_cleanup_task,
-    decode_redis_hash,
-    get_llm_api_key,
-    validate_llm_provider
+    decode_redis_hash
 )

 import psutil, time
@@ -91,12 +88,10 @@ async def handle_llm_qa(

    Answer:"""

-        # api_token=os.environ.get(config["llm"].get("api_key_env", ""))
-
        response = perform_completion_with_backoff(
            provider=config["llm"]["provider"],
            prompt_with_variables=prompt,
-            api_token=get_llm_api_key(config)
+            api_token=os.environ.get(config["llm"].get("api_key_env", ""))
        )

        return response.choices[0].message.content
@@ -114,23 +109,19 @@ async def process_llm_extraction(
    url: str,
    instruction: str,
    schema: Optional[str] = None,
-    cache: str = "0",
-    provider: Optional[str] = None
+    cache: str = "0"
 ) -> None:
    """Process LLM extraction in background."""
    try:
-        # Validate provider
-        is_valid, error_msg = validate_llm_provider(config, provider)
-        if not is_valid:
-            await redis.hset(f"task:{task_id}", mapping={
-                "status": TaskStatus.FAILED,
-                "error": error_msg
-            })
-            return
-        api_key = get_llm_api_key(config, provider)
+        # If config['llm'] has api_key then ignore the api_key_env
+        api_key = ""
+        if "api_key" in config["llm"]:
+            api_key = config["llm"]["api_key"]
+        else:
+            api_key = os.environ.get(config["llm"].get("api_key_env", None), "")
        llm_strategy = LLMExtractionStrategy(
            llm_config=LLMConfig(
-                provider=provider or config["llm"]["provider"],
+                provider=config["llm"]["provider"],
                api_token=api_key
            ),
            instruction=instruction,
@@ -177,19 +168,10 @@ async def handle_markdown_request(
    filter_type: FilterType,
    query: Optional[str] = None,
    cache: str = "0",
-    config: Optional[dict] = None,
-    provider: Optional[str] = None
+    config: Optional[dict] = None
 ) -> str:
    """Handle markdown generation requests."""
    try:
-        # Validate provider if using LLM filter
-        if filter_type == FilterType.LLM:
-            is_valid, error_msg = validate_llm_provider(config, provider)
-            if not is_valid:
-                raise HTTPException(
-                    status_code=status.HTTP_400_BAD_REQUEST,
-                    detail=error_msg
-                )
        decoded_url = unquote(url)
        if not decoded_url.startswith(('http://', 'https://')):
            decoded_url = 'https://' + decoded_url
@@ -202,8 +184,8 @@ async def handle_markdown_request(
                FilterType.BM25: BM25ContentFilter(user_query=query or ""),
                FilterType.LLM: LLMContentFilter(
                    llm_config=LLMConfig(
-                        provider=provider or config["llm"]["provider"],
-                        api_token=get_llm_api_key(config, provider),
+                        provider=config["llm"]["provider"],
+                        api_token=os.environ.get(config["llm"].get("api_key_env", None), ""),
                    ),
                    instruction=query or "Extract main content"
                )
@@ -247,8 +229,7 @@ async def handle_llm_request(
    query: Optional[str] = None,
    schema: Optional[str] = None,
    cache: str = "0",
-    config: Optional[dict] = None,
-    provider: Optional[str] = None
+    config: Optional[dict] = None
 ) -> JSONResponse:
    """Handle LLM extraction requests."""
    base_url = get_base_url(request)
@@ -278,8 +259,7 @@ async def handle_llm_request(
            schema,
            cache,
            base_url,
-            config,
-            provider
+            config
        )

    except Exception as e:
@@ -323,8 +303,7 @@ async def create_new_task(
    schema: Optional[str],
    cache: str,
    base_url: str,
-    config: dict,
-    provider: Optional[str] = None
+    config: dict
 ) -> JSONResponse:
    """Create and initialize a new task."""
    decoded_url = unquote(input_path)
@@ -348,8 +327,7 @@ async def create_new_task(
        decoded_url,
        query,
        schema,
-        cache,
-        provider
+        cache
    )

    return JSONResponse({
@@ -393,9 +371,6 @@ async def stream_results(crawler: AsyncWebCrawler, results_gen: AsyncGenerator)
                server_memory_mb = _get_memory_mb()
                result_dict = result.model_dump()
                result_dict['server_memory_mb'] = server_memory_mb
-                # If PDF exists, encode it to base64
-                if result_dict.get('pdf') is not None:
-                    result_dict['pdf'] = b64encode(result_dict['pdf']).decode('utf-8')
                logger.info(f"Streaming result for {result_dict.get('url', 'unknown')}")
                data = json.dumps(result_dict, default=datetime_handler) + "\n"
                yield data.encode('utf-8')
@@ -468,19 +443,10 @@ async def handle_crawl_request(
            mem_delta_mb = end_mem_mb - start_mem_mb # <--- Calculate delta
            peak_mem_mb = max(peak_mem_mb if peak_mem_mb else 0, end_mem_mb) # <--- Get peak memory
        logger.info(f"Memory usage: Start: {start_mem_mb} MB, End: {end_mem_mb} MB, Delta: {mem_delta_mb} MB, Peak: {peak_mem_mb} MB")
-
-        # Process results to handle PDF bytes
-        processed_results = []
-        for result in results:
-            result_dict = result.model_dump()
-            # If PDF exists, encode it to base64
-            if result_dict.get('pdf') is not None:
-                result_dict['pdf'] = b64encode(result_dict['pdf']).decode('utf-8')
-            processed_results.append(result_dict)
-            
+                              
        return {
            "success": True,
-            "results": processed_results,
+            "results": [result.model_dump() for result in results],
            "server_processing_time_s": end_time - start_time,
            "server_memory_delta_mb": mem_delta_mb,
            "server_peak_memory_mb": peak_mem_mb
--- a/deploy/docker/job.py
+++ b/deploy/docker/job.py
@@ -36,7 +36,6 @@ class LlmJobPayload(BaseModel):
    q:      str
    schema: Optional[str] = None
    cache:  bool = False
-    provider: Optional[str] = None


 class CrawlJobPayload(BaseModel):
@@ -62,7 +61,6 @@ async def llm_job_enqueue(
        schema=payload.schema,
        cache=payload.cache,
        config=_config,
-        provider=payload.provider,
    )


--- a/deploy/docker/schemas.py
+++ b/deploy/docker/schemas.py
@@ -15,7 +15,6 @@ class MarkdownRequest(BaseModel):
    f:   FilterType             = Field(FilterType.FIT, description="Content‑filter strategy: fit, raw, bm25, or llm")
    q:   Optional[str] = Field(None,  description="Query string used by BM25/LLM filters")
    c:   Optional[str] = Field("0",   description="Cache‑bust / revision counter")
-    provider: Optional[str] = Field(None, description="LLM provider override (e.g., 'anthropic/claude-3-opus')")


 class RawCode(BaseModel):
--- a/deploy/docker/server.py
+++ b/deploy/docker/server.py
@@ -241,7 +241,7 @@ async def get_markdown(
        raise HTTPException(
            400, "URL must be absolute and start with http/https")
    markdown = await handle_markdown_request(
-        body.url, body.f, body.q, body.c, config, body.provider
+        body.url, body.f, body.q, body.c, config
    )
    return JSONResponse({
        "url": body.url,
--- a/deploy/docker/utils.py
+++ b/deploy/docker/utils.py
@@ -1,7 +1,6 @@
 import dns.resolver
 import logging
 import yaml
-import os
 from datetime import datetime
 from enum import Enum
 from pathlib import Path
@@ -20,24 +19,10 @@ class FilterType(str, Enum):
    LLM = "llm"

 def load_config() -> Dict:
-    """Load and return application configuration with environment variable overrides."""
+    """Load and return application configuration."""
    config_path = Path(__file__).parent / "config.yml"
    with open(config_path, "r") as config_file:
-        config = yaml.safe_load(config_file)
-    
-    # Override LLM provider from environment if set
-    llm_provider = os.environ.get("LLM_PROVIDER")
-    if llm_provider:
-        config["llm"]["provider"] = llm_provider
-        logging.info(f"LLM provider overridden from environment: {llm_provider}")
-    
-    # Also support direct API key from environment if the provider-specific key isn't set
-    llm_api_key = os.environ.get("LLM_API_KEY")
-    if llm_api_key and "api_key" not in config["llm"]:
-        config["llm"]["api_key"] = llm_api_key
-        logging.info("LLM API key loaded from LLM_API_KEY environment variable")
-    
-    return config
+        return yaml.safe_load(config_file)

 def setup_logging(config: Dict) -> None:
    """Configure application logging."""
@@ -71,52 +56,6 @@ def decode_redis_hash(hash_data: Dict[bytes, bytes]) -> Dict[str, str]:



-def get_llm_api_key(config: Dict, provider: Optional[str] = None) -> str:
-    """Get the appropriate API key based on the LLM provider.
-    
-    Args:
-        config: The application configuration dictionary
-        provider: Optional provider override (e.g., "openai/gpt-4")
-    
-    Returns:
-        The API key for the provider, or empty string if not found
-    """
-        
-    # Use provided provider or fall back to config
-    if not provider:
-        provider = config["llm"]["provider"]
-    
-    # Check if direct API key is configured
-    if "api_key" in config["llm"]:
-        return config["llm"]["api_key"]
-    
-    # Fall back to the configured api_key_env if no match
-    return os.environ.get(config["llm"].get("api_key_env", ""), "")
-
-
-def validate_llm_provider(config: Dict, provider: Optional[str] = None) -> tuple[bool, str]:
-    """Validate that the LLM provider has an associated API key.
-    
-    Args:
-        config: The application configuration dictionary
-        provider: Optional provider override (e.g., "openai/gpt-4")
-    
-    Returns:
-        Tuple of (is_valid, error_message)
-    """
-    # Use provided provider or fall back to config
-    if not provider:
-        provider = config["llm"]["provider"]
-    
-    # Get the API key for this provider
-    api_key = get_llm_api_key(config, provider)
-    
-    if not api_key:
-        return False, f"No API key found for provider '{provider}'. Please set the appropriate environment variable."
-    
-    return True, ""
-
-
 def verify_email_domain(email: str) -> bool:
    try:
        domain = email.split('@')[1]
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -14,7 +14,6 @@ x-base-config: &base-config
    - TOGETHER_API_KEY=${TOGETHER_API_KEY:-}
    - MISTRAL_API_KEY=${MISTRAL_API_KEY:-}
    - GEMINI_API_TOKEN=${GEMINI_API_TOKEN:-}
-    - LLM_PROVIDER=${LLM_PROVIDER:-}  # Optional: Override default provider (e.g., "anthropic/claude-3-opus")
  volumes:
    - /dev/shm:/dev/shm  # Chromium performance
  deploy:
--- a/docs/blog/release-v0.7.0.md
+++ b/docs/blog/release-v0.7.0.md
@@ -10,8 +10,9 @@ Today I'm releasing Crawl4AI v0.7.0—the Adaptive Intelligence Update. This rel

 - **Adaptive Crawling**: Your crawler now learns and adapts to website patterns
 - **Virtual Scroll Support**: Complete content extraction from infinite scroll pages
- **Link Preview with Intelligent Scoring**: Intelligent link analysis and prioritization
+- **Link Preview with 3-Layer Scoring**: Intelligent link analysis and prioritization
 - **Async URL Seeder**: Discover thousands of URLs in seconds with intelligent filtering
+- **PDF Parsing**: Extract data from PDF documents
 - **Performance Optimizations**: Significant speed and memory improvements

 ## 🧠 Adaptive Crawling: Intelligence Through Pattern Learning
@@ -29,41 +30,44 @@ The Adaptive Crawler maintains a persistent state for each domain, tracking:
 - Extraction confidence scores

 ```python
-from crawl4ai import AsyncWebCrawler, AdaptiveCrawler, AdaptiveConfig
-import asyncio
+from crawl4ai import AdaptiveCrawler, AdaptiveConfig, CrawlState

-async def main():
-    
-    # Configure adaptive crawler
-    config = AdaptiveConfig(
-        strategy="statistical",  # or "embedding" for semantic understanding
-        max_pages=10,
-        confidence_threshold=0.7,  # Stop at 70% confidence
-        top_k_links=3,  # Follow top 3 links per page
-        min_gain_threshold=0.05  # Need 5% information gain to continue
+# Initialize with custom learning parameters
+config = AdaptiveConfig(
+    confidence_threshold=0.7,    # Min confidence to use learned patterns
+    max_history=100,            # Remember last 100 crawls per domain
+    learning_rate=0.2,          # How quickly to adapt to changes
+    patterns_per_page=3,        # Patterns to learn per page type
+    extraction_strategy='css'   # 'css' or 'xpath'
+)
+
+adaptive_crawler = AdaptiveCrawler(config)
+
+# First crawl - crawler learns the structure
+async with AsyncWebCrawler() as crawler:
+    result = await crawler.arun(
+        "https://news.example.com/article/12345",
+        config=CrawlerRunConfig(
+            adaptive_config=config,
+            extraction_hints={  # Optional hints to speed up learning
+                "title": "article h1",
+                "content": "article .body-content"
+            }
+        )
    )
    
-    async with AsyncWebCrawler(verbose=False) as crawler:
-        adaptive = AdaptiveCrawler(crawler, config)
-        
-        print("Starting adaptive crawl about Python decorators...")
-        result = await adaptive.digest(
-            start_url="https://docs.python.org/3/glossary.html",
-            query="python decorators functions wrapping"
-        )
-        
-        print(f"\n✅ Crawling Complete!")
-        print(f"• Confidence Level: {adaptive.confidence:.0%}")
-        print(f"• Pages Crawled: {len(result.crawled_urls)}")
-        print(f"• Knowledge Base: {len(adaptive.state.knowledge_base)} documents")
-        
-        # Get most relevant content
-        relevant = adaptive.get_relevant_content(top_k=3)
-        print(f"\nMost Relevant Pages:")
-        for i, page in enumerate(relevant, 1):
-            print(f"{i}. {page['url']} (relevance: {page['score']:.2%})")
+    # Crawler identifies and stores patterns
+    if result.success:
+        state = adaptive_crawler.get_state("news.example.com")
+        print(f"Learned {len(state.patterns)} patterns")
+        print(f"Confidence: {state.avg_confidence:.2%}")

-asyncio.run(main())
+# Subsequent crawls - uses learned patterns
+result2 = await crawler.arun(
+    "https://news.example.com/article/67890",
+    config=CrawlerRunConfig(adaptive_config=config)
+)
+# Automatically extracts using learned patterns!
 ```

 **Expected Real-World Impact:**
@@ -88,7 +92,9 @@ twitter_config = VirtualScrollConfig(
    container_selector="[data-testid='primaryColumn']",
    scroll_count=20,                    # Number of scrolls
    scroll_by="container_height",       # Smart scrolling by container size
-    wait_after_scroll=1.0              # Let content load
+    wait_after_scroll=1.0,             # Let content load
+    capture_method="incremental",       # Capture new content on each scroll
+    deduplicate=True                   # Remove duplicate elements
 )

 # For e-commerce product grids (Instagram style)
@@ -96,7 +102,8 @@ grid_config = VirtualScrollConfig(
    container_selector="main .product-grid",
    scroll_count=30,
    scroll_by=800,                     # Fixed pixel scrolling
-    wait_after_scroll=1.5              # Images need time
+    wait_after_scroll=1.5,             # Images need time
+    stop_on_no_change=True            # Smart stopping
 )

 # For news feeds with lazy loading
@@ -104,7 +111,9 @@ news_config = VirtualScrollConfig(
    container_selector=".article-feed",
    scroll_count=50,
    scroll_by="page_height",           # Viewport-based scrolling
-    wait_after_scroll=0.5              # Wait for content to load
+    wait_after_scroll=0.5,
+    wait_for_selector=".article-card",  # Wait for specific elements
+    timeout=30000                      # Max 30 seconds total
 )

 # Use it in your crawl
@@ -148,63 +157,68 @@ async with AsyncWebCrawler() as crawler:

 **My Solution:** I implemented a three-layer scoring system that analyzes links like a human would—considering their position, context, and relevance to your goals.

-### Intelligent Link Analysis and Scoring
+### The Three-Layer Scoring System

 ```python
-import asyncio
-from crawl4ai import CrawlerRunConfig, CacheMode, AsyncWebCrawler
-from crawl4ai.adaptive_crawler import LinkPreviewConfig
+from crawl4ai import LinkPreviewConfig

-async def main():
-    # Configure intelligent link analysis
-    link_config = LinkPreviewConfig(
-        include_internal=True,
-        include_external=False,
-        max_links=10,
-        concurrency=5,
-        query="python tutorial",  # For contextual scoring
-        score_threshold=0.3,
-        verbose=True
+# Configure intelligent link analysis
+link_config = LinkPreviewConfig(
+    # What to analyze
+    include_internal=True,
+    include_external=True,
+    max_links=100,              # Analyze top 100 links
+    
+    # Relevance scoring
+    query="machine learning tutorials",  # Your interest
+    score_threshold=0.3,        # Minimum relevance score
+    
+    # Performance
+    concurrent_requests=10,     # Parallel processing
+    timeout_per_link=5000,      # 5s per link
+    
+    # Advanced scoring weights
+    scoring_weights={
+        "intrinsic": 0.3,       # Link quality indicators
+        "contextual": 0.5,      # Relevance to query
+        "popularity": 0.2       # Link prominence
+    }
+)
+
+# Use in your crawl
+result = await crawler.arun(
+    "https://tech-blog.example.com",
+    config=CrawlerRunConfig(
+        link_preview_config=link_config,
+        score_links=True
    )
-    # Use in your crawl
-    async with AsyncWebCrawler() as crawler:
-        result = await crawler.arun(
-            "https://www.geeksforgeeks.org/",
-            config=CrawlerRunConfig(
-                link_preview_config=link_config,
-                score_links=True,  # Enable intrinsic scoring
-                cache_mode=CacheMode.BYPASS
-            )
-        )
+)

-        # Access scored and sorted links
-        if result.success and result.links:
-            for link in result.links.get("internal", []):
-                text = link.get('text', 'No text')[:40]
-                print(
-                    text,
-                    f"{link.get('intrinsic_score', 0):.1f}/10" if link.get('intrinsic_score') is not None else "0.0/10",
-                    f"{link.get('contextual_score', 0):.2f}/1" if link.get('contextual_score') is not None else "0.00/1",
-                    f"{link.get('total_score', 0):.3f}" if link.get('total_score') is not None else "0.000"
-                )
-
-asyncio.run(main())
+# Access scored and sorted links
+for link in result.links["internal"][:10]:  # Top 10 internal links
+    print(f"Score: {link['total_score']:.3f}")
+    print(f"  Intrinsic: {link['intrinsic_score']:.1f}/10")  # Position, attributes
+    print(f"  Contextual: {link['contextual_score']:.1f}/1")  # Relevance to query
+    print(f"  URL: {link['href']}")
+    print(f"  Title: {link['head_data']['title']}")
+    print(f"  Description: {link['head_data']['meta']['description'][:100]}...")
 ```

 **Scoring Components:**

-1. **Intrinsic Score**: Based on link quality indicators
+1. **Intrinsic Score (0-10)**: Based on link quality indicators
   - Position on page (navigation, content, footer)
   - Link attributes (rel, title, class names)
   - Anchor text quality and length
   - URL structure and depth

-2. **Contextual Score**: Relevance to your query using BM25 algorithm
+2. **Contextual Score (0-1)**: Relevance to your query
+   - Semantic similarity using embeddings
   - Keyword matching in link text and title
   - Meta description analysis
   - Content preview scoring

-3. **Total Score**: Combined score for final ranking
+3. **Total Score**: Weighted combination for final ranking

 **Expected Real-World Impact:**
 - **Research Efficiency**: Find relevant papers 10x faster by following only high-score links
@@ -221,34 +235,58 @@ asyncio.run(main())
 ### Technical Architecture

 ```python
-import asyncio
 from crawl4ai import AsyncUrlSeeder, SeedingConfig

-async def main():
-    async with AsyncUrlSeeder() as seeder:
-        # Discover Python tutorial URLs
-        config = SeedingConfig(
-            source="sitemap",  # Use sitemap
-            pattern="*python*",  # URL pattern filter
-            extract_head=True,  # Get metadata
-            query="python tutorial",  # For relevance scoring
-            scoring_method="bm25",
-            score_threshold=0.2,
-            max_urls=10
-        )
-        
-        print("Discovering Python async tutorial URLs...")
-        urls = await seeder.urls("https://www.geeksforgeeks.org/", config)
-        
-        print(f"\n✅ Found {len(urls)} relevant URLs:")
-        for i, url_info in enumerate(urls[:5], 1):
-            print(f"\n{i}. {url_info['url']}")
-            if url_info.get('relevance_score'):
-                print(f"   Relevance: {url_info['relevance_score']:.3f}")
-            if url_info.get('head_data', {}).get('title'):
-                print(f"   Title: {url_info['head_data']['title'][:60]}...")
+# Basic discovery - find all product pages
+seeder_config = SeedingConfig(
+    # Discovery sources
+    source="sitemap+cc",        # Sitemap + Common Crawl
+    
+    # Filtering
+    pattern="*/product/*",      # URL pattern matching
+    ignore_patterns=["*/reviews/*", "*/questions/*"],
+    
+    # Validation
+    live_check=True,           # Verify URLs are alive
+    max_urls=5000,             # Stop at 5000 URLs
+    
+    # Performance  
+    concurrency=100,           # Parallel requests
+    hits_per_sec=10           # Rate limiting
+)

-asyncio.run(main())
+seeder = AsyncUrlSeeder(seeder_config)
+urls = await seeder.discover("https://shop.example.com")
+
+# Advanced: Relevance-based discovery
+research_config = SeedingConfig(
+    source="crawl+sitemap",    # Deep crawl + sitemap
+    pattern="*/blog/*",        # Blog posts only
+    
+    # Content relevance
+    extract_head=True,         # Get meta tags
+    query="quantum computing tutorials",
+    scoring_method="bm25",     # Or "semantic" (coming soon)
+    score_threshold=0.4,       # High relevance only
+    
+    # Smart filtering
+    filter_nonsense_urls=True,  # Remove .xml, .txt, etc.
+    min_content_length=500,     # Skip thin content
+    
+    force=True                 # Bypass cache
+)
+
+# Discover with progress tracking
+discovered = []
+async for batch in seeder.discover_iter("https://physics-blog.com", research_config):
+    discovered.extend(batch)
+    print(f"Found {len(discovered)} relevant URLs so far...")
+
+# Results include scores and metadata
+for url_data in discovered[:5]:
+    print(f"URL: {url_data['url']}")
+    print(f"Score: {url_data['score']:.3f}")
+    print(f"Title: {url_data['title']}")
 ```

 **Discovery Methods:**
@@ -271,18 +309,35 @@ This release includes significant performance improvements through optimized res
 ### What We Optimized

 ```python
-# Optimized crawling with v0.7.0 improvements
+# Before v0.7.0 (slow)
 results = []
 for url in urls:
-    result = await crawler.arun(
-        url,
-        config=CrawlerRunConfig(
-            # Performance optimizations
-            wait_until="domcontentloaded",  # Faster than networkidle
-            cache_mode=CacheMode.ENABLED    # Enable caching
-        )
-    )
+    result = await crawler.arun(url)
    results.append(result)
+
+# After v0.7.0 (fast)
+# Automatic batching and connection pooling
+results = await crawler.arun_batch(
+    urls,
+    config=CrawlerRunConfig(
+        # New performance options
+        batch_size=10,              # Process 10 URLs concurrently
+        reuse_browser=True,         # Keep browser warm
+        eager_loading=False,        # Load only what's needed
+        streaming_extraction=True,  # Stream large extractions
+        
+        # Optimized defaults
+        wait_until="domcontentloaded",  # Faster than networkidle
+        exclude_external_resources=True, # Skip third-party assets
+        block_ads=True                  # Ad blocking built-in
+    )
+)
+
+# Memory-efficient streaming for large crawls
+async for result in crawler.arun_stream(large_url_list):
+    # Process results as they complete
+    await process_result(result)
+    # Memory is freed after each iteration
 ```

 **Performance Gains:**
@@ -292,6 +347,24 @@ for url in urls:
 - **Memory Usage**: 60% reduction with streaming processing
 - **Concurrent Crawls**: Handle 5x more parallel requests

+## 📄 PDF Support
+
+PDF extraction is now natively supported in Crawl4AI.
+
+```python
+# Extract data from PDF documents
+result = await crawler.arun(
+    "https://example.com/report.pdf",
+    config=CrawlerRunConfig(
+        pdf_extraction=True,
+        extraction_strategy=JsonCssExtractionStrategy({
+            # Works on converted PDF structure
+            "title": {"selector": "h1", "type": "text"},
+            "sections": {"selector": "h2", "type": "list"}
+        })
+    )
+)
+```

 ## 🔧 Important Changes

--- a/docs/blog/release-v0.7.1.md
+++ b/docs/blog/release-v0.7.1.md
@@ -1,43 +0,0 @@
-# 🛠️ Crawl4AI v0.7.1: Minor Cleanup Update
-
-*July 17, 2025 • 2 min read*
-
---
-
-A small maintenance release that removes unused code and improves documentation.
-
-## 🎯 What's Changed
-
- **Removed unused StealthConfig** from `crawl4ai/browser_manager.py`
- **Updated documentation** with better examples and parameter explanations
- **Fixed virtual scroll configuration** examples in docs
-
-## 🧹 Code Cleanup
-
-Removed unused `StealthConfig` import and configuration that wasn't being used anywhere in the codebase. The project uses its own custom stealth implementation through JavaScript injection instead.
-
-```python
-# Removed unused code:
-from playwright_stealth import StealthConfig
-stealth_config = StealthConfig(...)  # This was never used
-```
-
-## 📖 Documentation Updates
-
- Fixed adaptive crawling parameter examples
- Updated session management documentation
- Corrected virtual scroll configuration examples
-
-## 🚀 Installation
-
-```bash
-pip install crawl4ai==0.7.1
-```
-
-No breaking changes - upgrade directly from v0.7.0.
-
---
-
-Questions? Issues? 
- GitHub: [github.com/unclecode/crawl4ai](https://github.com/unclecode/crawl4ai)
- Discord: [discord.gg/crawl4ai](https://discord.gg/jP8KfhDhyN)
--- a/docs/blog/release-v0.7.3.md
+++ b/docs/blog/release-v0.7.3.md
@@ -1,170 +0,0 @@
-# 🚀 Crawl4AI v0.7.3: The Multi-Config Intelligence Update
-
-*August 6, 2025 • 5 min read*
-
---
-
-Today I'm releasing Crawl4AI v0.7.3—the Multi-Config Intelligence Update. This release brings smarter URL-specific configurations, flexible Docker deployments, important bug fixes, and documentation improvements that make Crawl4AI more robust and production-ready.
-
-## 🎯 What's New at a Glance
-
- **Multi-URL Configurations**: Different crawling strategies for different URL patterns in a single batch
- **Flexible Docker LLM Providers**: Configure LLM providers via environment variables
- **Bug Fixes**: Resolved several critical issues for better stability
- **Documentation Updates**: Clearer examples and improved API documentation
-
-## 🎨 Multi-URL Configurations: One Size Doesn't Fit All
-
-**The Problem:** You're crawling a mix of documentation sites, blogs, and API endpoints. Each needs different handling—caching for docs, fresh content for news, structured extraction for APIs. Previously, you'd run separate crawls or write complex conditional logic.
-
-**My Solution:** I implemented URL-specific configurations that let you define different strategies for different URL patterns in a single crawl batch. First match wins, with optional fallback support.
-
-### Technical Implementation
-
-```python
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, MatchMode
-
-# Define specialized configs for different content types
-configs = [
-    # Documentation sites - aggressive caching, include links
-    CrawlerRunConfig(
-        url_matcher=["*docs*", "*documentation*"],
-        cache_mode="write",
-        markdown_generator_options={"include_links": True}
-    ),
-    
-    # News/blog sites - fresh content, scroll for lazy loading
-    CrawlerRunConfig(
-        url_matcher=lambda url: 'blog' in url or 'news' in url,
-        cache_mode="bypass",
-        js_code="window.scrollTo(0, document.body.scrollHeight/2);"
-    ),
-    
-    # API endpoints - structured extraction
-    CrawlerRunConfig(
-        url_matcher=["*.json", "*api*"],
-        extraction_strategy=LLMExtractionStrategy(
-            provider="openai/gpt-4o-mini",
-            extraction_type="structured"
-        )
-    ),
-    
-    # Default fallback for everything else
-    CrawlerRunConfig()  # No url_matcher = matches everything
-]
-
-# Crawl multiple URLs with appropriate configs
-async with AsyncWebCrawler() as crawler:
-    results = await crawler.arun_many(
-        urls=[
-            "https://docs.python.org/3/",      # → Uses documentation config
-            "https://blog.python.org/",        # → Uses blog config  
-            "https://api.github.com/users",    # → Uses API config
-            "https://example.com/"             # → Uses default config
-        ],
-        config=configs
-    )
-```
-
-**Matching Capabilities:**
- **String Patterns**: Wildcards like `"*.pdf"`, `"*/blog/*"`
- **Function Matchers**: Lambda functions for complex logic
- **Mixed Matchers**: Combine strings and functions with AND/OR logic
- **Fallback Support**: Default config when nothing matches
-
-**Expected Real-World Impact:**
- **Mixed Content Sites**: Handle blogs, docs, and downloads in one crawl
- **Multi-Domain Crawling**: Different strategies per domain without separate runs
- **Reduced Complexity**: No more if/else forests in your extraction code
- **Better Performance**: Each URL gets exactly the processing it needs
-
-## 🐳 Docker: Flexible LLM Provider Configuration
-
-**The Problem:** Hardcoded LLM providers in Docker deployments. Want to switch from OpenAI to Groq? Rebuild and redeploy. Testing different models? Multiple Docker images.
-
-**My Solution:** Configure LLM providers via environment variables. Switch providers without touching code or rebuilding images.
-
-### Deployment Flexibility
-
-```bash
-# Option 1: Direct environment variables
-docker run -d \
-  -e LLM_PROVIDER="groq/llama-3.2-3b-preview" \
-  -e GROQ_API_KEY="your-key" \
-  -p 11235:11235 \
-  unclecode/crawl4ai:latest
-
-# Option 2: Using .llm.env file (recommended for production)
-# Create .llm.env file:
-# LLM_PROVIDER=openai/gpt-4o-mini
-# OPENAI_API_KEY=your-openai-key
-# GROQ_API_KEY=your-groq-key
-
-docker run -d \
-  --env-file .llm.env \
-  -p 11235:11235 \
-  unclecode/crawl4ai:latest
-```
-
-Override per request when needed:
-```python
-# Use default provider from .llm.env
-response = requests.post("http://localhost:11235/crawl", json={
-    "url": "https://example.com",
-    "extraction_strategy": {"type": "llm"}
-})
-
-# Override to use different provider for this specific request
-response = requests.post("http://localhost:11235/crawl", json={
-    "url": "https://complex-page.com",
-    "extraction_strategy": {
-        "type": "llm",
-        "provider": "openai/gpt-4"  # Override default
-    }
-})
-```
-
-**Expected Real-World Impact:**
- **Cost Optimization**: Use cheaper models for simple tasks, premium for complex
- **A/B Testing**: Compare provider performance without deployment changes
- **Fallback Strategies**: Switch providers on-the-fly during outages
- **Development Flexibility**: Test locally with one provider, deploy with another
- **Secure Configuration**: Keep API keys in `.llm.env` file, not in commands
-
-## 🔧 Bug Fixes & Improvements
-
-This release includes several important bug fixes that improve stability and reliability:
-
- **URL Matcher Fallback**: Fixed edge cases in URL pattern matching logic
- **Memory Management**: Resolved memory leaks in long-running crawl sessions
- **Sitemap Processing**: Fixed redirect handling in sitemap fetching
- **Table Extraction**: Improved table detection and extraction accuracy
- **Error Handling**: Better error messages and recovery from network failures
-
-## 📚 Documentation Enhancements
-
-Based on community feedback, we've updated:
- Clearer examples for multi-URL configuration
- Improved CrawlResult documentation with all available fields
- Fixed typos and inconsistencies across documentation
- Added real-world URLs in examples for better understanding
- New comprehensive demo showcasing all v0.7.3 features
-
-## 🙏 Acknowledgments
-
-Thanks to our contributors and the entire community for feedback and bug reports.
-
-## 📚 Resources
-
- [Full Documentation](https://docs.crawl4ai.com)
- [GitHub Repository](https://github.com/unclecode/crawl4ai)
- [Discord Community](https://discord.gg/crawl4ai)
- [Feature Demo](https://github.com/unclecode/crawl4ai/blob/main/docs/releases_review/demo_v0.7.3.py)
-
---
-
-*Crawl4AI continues to evolve with your needs. This release makes it smarter, more flexible, and more stable. Try the new multi-config feature and flexible Docker deployment—they're game changers!*
-
-**Happy Crawling! 🕷️**
-
-*- The Crawl4AI Team*
--- a/docs/examples/c4a_script/api_usage_examples.py
+++ b/docs/examples/c4a_script/api_usage_examples.py
@@ -3,8 +3,8 @@ C4A-Script API Usage Examples
 Shows how to use the new Result-based API in various scenarios
 """

-from crawl4ai.script.c4a_compile import compile, validate, compile_file
-from crawl4ai.script.c4a_result import CompilationResult, ValidationResult
+from c4a_compile import compile, validate, compile_file
+from c4a_result import CompilationResult, ValidationResult
 import json


--- a/docs/examples/c4a_script/c4a_script_hello_world.py
+++ b/docs/examples/c4a_script/c4a_script_hello_world.py
@@ -3,7 +3,7 @@ C4A-Script Hello World
 A concise example showing how to use the C4A-Script compiler
 """

-from crawl4ai.script.c4a_compile import compile
+from c4a_compile import compile

 # Define your C4A-Script
 script = """
--- a/docs/examples/c4a_script/c4a_script_hello_world_error.py
+++ b/docs/examples/c4a_script/c4a_script_hello_world_error.py
@@ -3,7 +3,7 @@ C4A-Script Hello World - Error Example
 Shows how error handling works
 """

-from crawl4ai.script.c4a_compile import compile
+from c4a_compile import compile

 # Define a script with an error (missing THEN)
 script = """
--- a/docs/examples/demo_multi_config_clean.py
+++ b/docs/examples/demo_multi_config_clean.py
@@ -1,303 +0,0 @@
-"""
-🎯 Multi-Config URL Matching Demo
-=================================
-Learn how to use different crawler configurations for different URL patterns
-in a single crawl batch with Crawl4AI's multi-config feature.
-
-Part 1: Understanding URL Matching (Pattern Testing)
-Part 2: Practical Example with Real Crawling
-"""
-
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler, 
-    CrawlerRunConfig,
-    MatchMode
-)
-from crawl4ai.processors.pdf import PDFContentScrapingStrategy
-from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
-from crawl4ai.content_filter_strategy import PruningContentFilter
-from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
-
-
-def print_section(title):
-    """Print a formatted section header"""
-    print(f"\n{'=' * 60}")
-    print(f"{title}")
-    print(f"{'=' * 60}\n")
-
-
-def test_url_matching(config, test_urls, config_name):
-    """Test URL matching for a config and show results"""
-    print(f"Config: {config_name}")
-    print(f"Matcher: {config.url_matcher}")
-    if hasattr(config, 'match_mode'):
-        print(f"Mode: {config.match_mode.value}")
-    print("-" * 40)
-    
-    for url in test_urls:
-        matches = config.is_match(url)
-        symbol = "✓" if matches else "✗"
-        print(f"{symbol} {url}")
-    print()
-
-
-# ==============================================================================
-# PART 1: Understanding URL Matching
-# ==============================================================================
-
-def demo_part1_pattern_matching():
-    """Part 1: Learn how URL matching works without crawling"""
-    
-    print_section("PART 1: Understanding URL Matching")
-    print("Let's explore different ways to match URLs with configs.\n")
-    
-    # Test URLs we'll use throughout
-    test_urls = [
-        "https://example.com/report.pdf",
-        "https://example.com/data.json",
-        "https://example.com/blog/post-1",
-        "https://example.com/article/news",
-        "https://api.example.com/v1/users",
-        "https://example.com/about"
-    ]
-    
-    # 1.1 Simple String Pattern
-    print("1.1 Simple String Pattern Matching")
-    print("-" * 40)
-    
-    pdf_config = CrawlerRunConfig(
-        url_matcher="*.pdf"
-    )
-    
-    test_url_matching(pdf_config, test_urls, "PDF Config")
-    
-    
-    # 1.2 Multiple String Patterns
-    print("1.2 Multiple String Patterns (OR logic)")
-    print("-" * 40)
-    
-    blog_config = CrawlerRunConfig(
-        url_matcher=["*/blog/*", "*/article/*", "*/news/*"],
-        match_mode=MatchMode.OR  # This is default, shown for clarity
-    )
-    
-    test_url_matching(blog_config, test_urls, "Blog/Article Config")
-    
-    
-    # 1.3 Single Function Matcher
-    print("1.3 Function-based Matching")
-    print("-" * 40)
-    
-    api_config = CrawlerRunConfig(
-        url_matcher=lambda url: 'api' in url or url.endswith('.json')
-    )
-    
-    test_url_matching(api_config, test_urls, "API Config")
-    
-    
-    # 1.4 List of Functions
-    print("1.4 Multiple Functions with AND Logic")
-    print("-" * 40)
-    
-    # Must be HTTPS AND contain 'api' AND have version number
-    secure_api_config = CrawlerRunConfig(
-        url_matcher=[
-            lambda url: url.startswith('https://'),
-            lambda url: 'api' in url,
-            lambda url: '/v' in url  # Version indicator
-        ],
-        match_mode=MatchMode.AND
-    )
-    
-    test_url_matching(secure_api_config, test_urls, "Secure API Config")
-    
-    
-    # 1.5 Mixed: String and Function Together
-    print("1.5 Mixed Patterns: String + Function")
-    print("-" * 40)
-    
-    # Match JSON files OR any API endpoint
-    json_or_api_config = CrawlerRunConfig(
-        url_matcher=[
-            "*.json",  # String pattern
-            lambda url: 'api' in url  # Function
-        ],
-        match_mode=MatchMode.OR
-    )
-    
-    test_url_matching(json_or_api_config, test_urls, "JSON or API Config")
-    
-    
-    # 1.6 Complex: Multiple Strings + Multiple Functions
-    print("1.6 Complex Matcher: Mixed Types with AND Logic")
-    print("-" * 40)
-    
-    # Must be: HTTPS AND (.com domain) AND (blog OR article) AND NOT a PDF
-    complex_config = CrawlerRunConfig(
-        url_matcher=[
-            lambda url: url.startswith('https://'),  # Function: HTTPS check
-            "*.com/*",  # String: .com domain
-            lambda url: any(pattern in url for pattern in ['/blog/', '/article/']),  # Function: Blog OR article
-            lambda url: not url.endswith('.pdf')  # Function: Not PDF
-        ],
-        match_mode=MatchMode.AND
-    )
-    
-    test_url_matching(complex_config, test_urls, "Complex Mixed Config")
-    
-    print("\n✅ Key Takeaway: First matching config wins when passed to arun_many()!")
-
-
-# ==============================================================================
-# PART 2: Practical Multi-URL Crawling
-# ==============================================================================
-
-async def demo_part2_practical_crawling():
-    """Part 2: Real-world example with different content types"""
-    
-    print_section("PART 2: Practical Multi-URL Crawling")
-    print("Now let's see multi-config in action with real URLs.\n")
-    
-    # Create specialized configs for different content types
-    configs = [
-        # Config 1: PDF documents - only match files ending with .pdf
-        CrawlerRunConfig(
-            url_matcher="*.pdf",
-            scraping_strategy=PDFContentScrapingStrategy()
-        ),
-        
-        # Config 2: Blog/article pages with content filtering
-        CrawlerRunConfig(
-            url_matcher=["*/blog/*", "*/article/*", "*python.org*"],
-            markdown_generator=DefaultMarkdownGenerator(
-                content_filter=PruningContentFilter(threshold=0.48)
-            )
-        ),
-        
-        # Config 3: Dynamic pages requiring JavaScript
-        CrawlerRunConfig(
-            url_matcher=lambda url: 'github.com' in url,
-            js_code="window.scrollTo(0, 500);"  # Scroll to load content
-        ),
-        
-        # Config 4: Mixed matcher - API endpoints (string OR function)
-        CrawlerRunConfig(
-            url_matcher=[
-                "*.json",  # String pattern for JSON files
-                lambda url: 'api' in url or 'httpbin.org' in url  # Function for API endpoints
-            ],
-            match_mode=MatchMode.OR,
-        ),
-        
-        # Config 5: Complex matcher - Secure documentation sites
-        CrawlerRunConfig(
-            url_matcher=[
-                lambda url: url.startswith('https://'),  # Must be HTTPS
-                "*.org/*",  # String: .org domain
-                lambda url: any(doc in url for doc in ['docs', 'documentation', 'reference']),  # Has docs
-                lambda url: not url.endswith(('.pdf', '.json'))  # Not PDF or JSON
-            ],
-            match_mode=MatchMode.AND,
-            # wait_for="css:.content, css:article"  # Wait for content to load
-        ),
-        
-        # Default config for everything else
-        # CrawlerRunConfig()  # No url_matcher means it matches everything (use it as fallback)
-    ]
-    
-    # URLs to crawl - each will use a different config
-    urls = [
-        "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",  # → PDF config
-        "https://blog.python.org/",  # → Blog config with content filter
-        "https://github.com/microsoft/playwright",  # → JS config
-        "https://httpbin.org/json",  # → Mixed matcher config (API)
-        "https://docs.python.org/3/reference/",  # → Complex matcher config
-        "https://www.w3schools.com/",  # → Default config, if you uncomment the default config line above, if not you will see `Error: No matching configuration`
-    ]
-    
-    print("URLs to crawl:")
-    for i, url in enumerate(urls, 1):
-        print(f"{i}. {url}")
-    
-    print("\nCrawling with appropriate config for each URL...\n")
-    
-    async with AsyncWebCrawler() as crawler:
-        results = await crawler.arun_many(
-            urls=urls,
-            config=configs
-        )
-        
-        # Display results
-        print("Results:")
-        print("-" * 60)
-        
-        for result in results:
-            if result.success:
-                # Determine which config was used
-                config_type = "Default"
-                if result.url.endswith('.pdf'):
-                    config_type = "PDF Strategy"
-                elif any(pattern in result.url for pattern in ['blog', 'python.org']) and 'docs' not in result.url:
-                    config_type = "Blog + Content Filter"
-                elif 'github.com' in result.url:
-                    config_type = "JavaScript Enabled"
-                elif 'httpbin.org' in result.url or result.url.endswith('.json'):
-                    config_type = "Mixed Matcher (API)"
-                elif 'docs.python.org' in result.url:
-                    config_type = "Complex Matcher (Secure Docs)"
-                
-                print(f"\n✓ {result.url}")
-                print(f"  Config used: {config_type}")
-                print(f"  Content size: {len(result.markdown)} chars")
-                
-                # Show if we have fit_markdown (from content filter)
-                if hasattr(result.markdown, 'fit_markdown') and result.markdown.fit_markdown:
-                    print(f"  Fit markdown size: {len(result.markdown.fit_markdown)} chars")
-                    reduction = (1 - len(result.markdown.fit_markdown) / len(result.markdown)) * 100
-                    print(f"  Content reduced by: {reduction:.1f}%")
-                
-                # Show extracted data if using extraction strategy
-                if hasattr(result, 'extracted_content') and result.extracted_content:
-                    print(f"  Extracted data: {str(result.extracted_content)[:100]}...")
-            else:
-                print(f"\n✗ {result.url}")
-                print(f"  Error: {result.error_message}")
-    
-    print("\n" + "=" * 60)
-    print("✅ Multi-config crawling complete!")
-    print("\nBenefits demonstrated:")
-    print("- PDFs handled with specialized scraper")
-    print("- Blog content filtered for relevance") 
-    print("- JavaScript executed only where needed")
-    print("- Mixed matchers (string + function) for flexible matching")
-    print("- Complex matchers for precise URL targeting")
-    print("- Each URL got optimal configuration automatically!")
-
-
-async def main():
-    """Run both parts of the demo"""
-    
-    print("""
-🎯 Multi-Config URL Matching Demo
-=================================
-Learn how Crawl4AI can use different configurations
-for different URLs in a single batch.
-    """)
-    
-    # Part 1: Pattern matching
-    demo_part1_pattern_matching()
-    
-    print("\nPress Enter to continue to Part 2...")
-    try:
-        input()
-    except EOFError:
-        # Running in non-interactive mode, skip input
-        pass
-    
-    # Part 2: Practical crawling
-    await demo_part2_practical_crawling()
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/hello_world_undetected.py
+++ b/docs/examples/hello_world_undetected.py
@@ -1,57 +0,0 @@
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler,
-    BrowserConfig,
-    CrawlerRunConfig,
-    DefaultMarkdownGenerator,
-    PruningContentFilter,
-    CrawlResult,
-    UndetectedAdapter
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-
-async def main():
-    # Create browser config
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True,
-    )
-    
-    # Create the undetected adapter
-    undetected_adapter = UndetectedAdapter()
-    
-    # Create the crawler strategy with the undetected adapter
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=undetected_adapter
-    )
-    
-    # Create the crawler with our custom strategy
-    async with AsyncWebCrawler(
-        crawler_strategy=crawler_strategy,
-        config=browser_config
-    ) as crawler:
-        # Configure the crawl
-        crawler_config = CrawlerRunConfig(
-            markdown_generator=DefaultMarkdownGenerator(
-                content_filter=PruningContentFilter()
-            ),
-            capture_console_messages=True,  # Enable console capture to test adapter
-        )
-        
-        # Test on a site that typically detects bots
-        print("Testing undetected adapter...")
-        result: CrawlResult = await crawler.arun(
-            url="https://www.helloworld.org", 
-            config=crawler_config
-        )
-        
-        print(f"Status: {result.status_code}")
-        print(f"Success: {result.success}")
-        print(f"Console messages captured: {len(result.console_messages or [])}")
-        print(f"Markdown content (first 500 chars):\n{result.markdown.raw_markdown[:500]}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/link_head_extraction_example.py
+++ b/docs/examples/link_head_extraction_example.py
@@ -18,7 +18,7 @@ Usage:

 import asyncio
 from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
-from crawl4ai import LinkPreviewConfig
+from crawl4ai.async_configs import LinkPreviewConfig


 async def basic_link_head_extraction():
--- a/docs/examples/scraping_strategies_performance.py
+++ b/docs/examples/scraping_strategies_performance.py
@@ -1,6 +1,5 @@
 import time, re
-from crawl4ai.content_scraping_strategy import LXMLWebScrapingStrategy
-# WebScrapingStrategy is now an alias for LXMLWebScrapingStrategy
+from crawl4ai.content_scraping_strategy import WebScrapingStrategy,  LXMLWebScrapingStrategy
 import time
 import functools
 from collections import defaultdict
@@ -58,7 +57,7 @@ methods_to_profile = [


 # Apply decorators to both strategies
-for strategy, name in [(LXMLWebScrapingStrategy, "LXML")]:
+for strategy, name in [(WebScrapingStrategy, "Original"), (LXMLWebScrapingStrategy, "LXML")]:
    for method in methods_to_profile:
        apply_decorators(strategy, method, name)

@@ -86,7 +85,7 @@ def generate_large_html(n_elements=1000):

 def test_scraping():
    # Initialize both scrapers
-    original_scraper = LXMLWebScrapingStrategy()
+    original_scraper = WebScrapingStrategy()
    selected_scraper = LXMLWebScrapingStrategy()
    
    # Generate test HTML
--- a/docs/examples/simple_anti_bot_examples.py
+++ b/docs/examples/simple_anti_bot_examples.py
@@ -1,59 +0,0 @@
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, UndetectedAdapter
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-# Example 1: Stealth Mode
-async def stealth_mode_example():
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=False
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun("https://example.com")
-        return result.html[:500]
-
-# Example 2: Undetected Browser
-async def undetected_browser_example():
-    browser_config = BrowserConfig(
-        headless=False
-    )
-    
-    adapter = UndetectedAdapter()
-    strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=adapter
-    )
-    
-    async with AsyncWebCrawler(
-        crawler_strategy=strategy,
-        config=browser_config
-    ) as crawler:
-        result = await crawler.arun("https://example.com")
-        return result.html[:500]
-
-# Example 3: Both Combined
-async def combined_example():
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=False
-    )
-    
-    adapter = UndetectedAdapter()
-    strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=adapter
-    )
-    
-    async with AsyncWebCrawler(
-        crawler_strategy=strategy,
-        config=browser_config
-    ) as crawler:
-        result = await crawler.arun("https://example.com")
-        return result.html[:500]
-
-# Run examples
-if __name__ == "__main__":
-    asyncio.run(stealth_mode_example())
-    asyncio.run(undetected_browser_example())
-    asyncio.run(combined_example())
--- a/docs/examples/stealth_mode_example.py
+++ b/docs/examples/stealth_mode_example.py
@@ -1,522 +0,0 @@
-"""
-Stealth Mode Example with Crawl4AI
-
-This example demonstrates how to use the stealth mode feature to bypass basic bot detection.
-The stealth mode uses playwright-stealth to modify browser fingerprints and behaviors
-that are commonly used to detect automated browsers.
-
-Key features demonstrated:
-1. Comparing crawling with and without stealth mode
-2. Testing against bot detection sites
-3. Accessing sites that block automated browsers
-4. Best practices for stealth crawling
-"""
-
-import asyncio
-import json
-from typing import Dict, Any
-from colorama import Fore, Style, init
-
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
-from crawl4ai.async_logger import AsyncLogger
-
-# Initialize colorama for colored output
-init()
-
-# Create a logger for better output
-logger = AsyncLogger(verbose=True)
-
-
-async def test_bot_detection(use_stealth: bool = False) -> Dict[str, Any]:
-    """Test against a bot detection service"""
-    
-    logger.info(
-        f"Testing bot detection with stealth={'ON' if use_stealth else 'OFF'}",
-        tag="STEALTH"
-    )
-    
-    # Configure browser with or without stealth
-    browser_config = BrowserConfig(
-        headless=False,  # Use False to see the browser in action
-        enable_stealth=use_stealth,
-        viewport_width=1280,
-        viewport_height=800
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        # JavaScript to extract bot detection results
-        detection_script = """
-        // Comprehensive bot detection checks
-        (() => {
-        const detectionResults = {
-            // Basic WebDriver detection
-            webdriver: navigator.webdriver,
-            
-            // Chrome specific
-            chrome: !!window.chrome,
-            chromeRuntime: !!window.chrome?.runtime,
-            
-            // Automation indicators
-            automationControlled: navigator.webdriver,
-            
-            // Permissions API
-            permissionsPresent: !!navigator.permissions?.query,
-            
-            // Plugins
-            pluginsLength: navigator.plugins.length,
-            pluginsArray: Array.from(navigator.plugins).map(p => p.name),
-            
-            // Languages
-            languages: navigator.languages,
-            language: navigator.language,
-            
-            // User agent
-            userAgent: navigator.userAgent,
-            
-            // Screen and window properties
-            screen: {
-                width: screen.width,
-                height: screen.height,
-                availWidth: screen.availWidth,
-                availHeight: screen.availHeight,
-                colorDepth: screen.colorDepth,
-                pixelDepth: screen.pixelDepth
-            },
-            
-            // WebGL vendor
-            webglVendor: (() => {
-                try {
-                    const canvas = document.createElement('canvas');
-                    const gl = canvas.getContext('webgl') || canvas.getContext('experimental-webgl');
-                    const ext = gl.getExtension('WEBGL_debug_renderer_info');
-                    return gl.getParameter(ext.UNMASKED_VENDOR_WEBGL);
-                } catch (e) {
-                    return 'Error';
-                }
-            })(),
-            
-            // Platform
-            platform: navigator.platform,
-            
-            // Hardware concurrency
-            hardwareConcurrency: navigator.hardwareConcurrency,
-            
-            // Device memory
-            deviceMemory: navigator.deviceMemory,
-            
-            // Connection
-            connection: navigator.connection?.effectiveType
-        };
-        
-        // Log results for console capture
-        console.log('DETECTION_RESULTS:', JSON.stringify(detectionResults, null, 2));
-        
-        // Return results
-        return detectionResults;
-        })();
-        """
-        
-        # Crawl bot detection test page
-        config = CrawlerRunConfig(
-            js_code=detection_script,
-            capture_console_messages=True,
-            wait_until="networkidle",
-            delay_before_return_html=2.0  # Give time for all checks to complete
-        )
-        
-        result = await crawler.arun(
-            url="https://bot.sannysoft.com",
-            config=config
-        )
-        
-        if result.success:
-            # Extract detection results from console
-            detection_data = None
-            for msg in result.console_messages or []:
-                if "DETECTION_RESULTS:" in msg.get("text", ""):
-                    try:
-                        json_str = msg["text"].replace("DETECTION_RESULTS:", "").strip()
-                        detection_data = json.loads(json_str)
-                    except:
-                        pass
-            
-            # Also try to get from JavaScript execution result
-            if not detection_data and result.js_execution_result:
-                detection_data = result.js_execution_result
-            
-            return {
-                "success": True,
-                "url": result.url,
-                "detection_data": detection_data,
-                "page_title": result.metadata.get("title", ""),
-                "stealth_enabled": use_stealth
-            }
-        else:
-            return {
-                "success": False,
-                "error": result.error_message,
-                "stealth_enabled": use_stealth
-            }
-
-
-async def test_cloudflare_site(use_stealth: bool = False) -> Dict[str, Any]:
-    """Test accessing a Cloudflare-protected site"""
-    
-    logger.info(
-        f"Testing Cloudflare site with stealth={'ON' if use_stealth else 'OFF'}",
-        tag="STEALTH"
-    )
-    
-    browser_config = BrowserConfig(
-        headless=True,  # Cloudflare detection works better in headless mode with stealth
-        enable_stealth=use_stealth,
-        viewport_width=1920,
-        viewport_height=1080
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        config = CrawlerRunConfig(
-            wait_until="networkidle",
-            page_timeout=30000,  # 30 seconds
-            delay_before_return_html=3.0
-        )
-        
-        # Test on a site that often shows Cloudflare challenges
-        result = await crawler.arun(
-            url="https://nowsecure.nl",
-            config=config
-        )
-        
-        # Check if we hit Cloudflare challenge
-        cloudflare_detected = False
-        if result.html:
-            cloudflare_indicators = [
-                "Checking your browser",
-                "Just a moment",
-                "cf-browser-verification",
-                "cf-challenge",
-                "ray ID"
-            ]
-            cloudflare_detected = any(indicator in result.html for indicator in cloudflare_indicators)
-        
-        return {
-            "success": result.success,
-            "url": result.url,
-            "cloudflare_challenge": cloudflare_detected,
-            "status_code": result.status_code,
-            "page_title": result.metadata.get("title", "") if result.metadata else "",
-            "stealth_enabled": use_stealth,
-            "html_snippet": result.html[:500] if result.html else ""
-        }
-
-
-async def test_anti_bot_site(use_stealth: bool = False) -> Dict[str, Any]:
-    """Test against sites with anti-bot measures"""
-    
-    logger.info(
-        f"Testing anti-bot site with stealth={'ON' if use_stealth else 'OFF'}",
-        tag="STEALTH"
-    )
-    
-    browser_config = BrowserConfig(
-        headless=False,
-        enable_stealth=use_stealth,
-        # Additional browser arguments that help with stealth
-        extra_args=[
-            "--disable-blink-features=AutomationControlled",
-            "--disable-features=site-per-process"
-        ] if not use_stealth else []  # These are automatically applied with stealth
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        # Some sites check for specific behaviors
-        behavior_script = """
-        (async () => {
-            // Simulate human-like behavior
-            const sleep = ms => new Promise(resolve => setTimeout(resolve, ms));
-            
-            // Random mouse movement
-            const moveX = Math.random() * 100;
-            const moveY = Math.random() * 100;
-            
-            // Simulate reading time
-            await sleep(1000 + Math.random() * 2000);
-            
-            // Scroll slightly
-            window.scrollBy(0, 100 + Math.random() * 200);
-            
-            console.log('Human behavior simulation complete');
-            return true;
-        })()
-        """
-        
-        config = CrawlerRunConfig(
-            js_code=behavior_script,
-            wait_until="networkidle",
-            delay_before_return_html=5.0,  # Longer delay to appear more human
-            capture_console_messages=True
-        )
-        
-        # Test on a site that implements anti-bot measures
-        result = await crawler.arun(
-            url="https://www.g2.com/",
-            config=config
-        )
-        
-        # Check for common anti-bot blocks
-        blocked_indicators = [
-            "Access Denied",
-            "403 Forbidden", 
-            "Security Check",
-            "Verify you are human",
-            "captcha",
-            "challenge"
-        ]
-        
-        blocked = False
-        if result.html:
-            blocked = any(indicator.lower() in result.html.lower() for indicator in blocked_indicators)
-        
-        return {
-            "success": result.success and not blocked,
-            "url": result.url,
-            "blocked": blocked,
-            "status_code": result.status_code,
-            "page_title": result.metadata.get("title", "") if result.metadata else "",
-            "stealth_enabled": use_stealth
-        }
-
-
-async def compare_results():
-    """Run all tests with and without stealth mode and compare results"""
-    
-    print(f"\n{Fore.CYAN}{'='*60}{Style.RESET_ALL}")
-    print(f"{Fore.CYAN}Crawl4AI Stealth Mode Comparison{Style.RESET_ALL}")
-    print(f"{Fore.CYAN}{'='*60}{Style.RESET_ALL}\n")
-    
-    # Test 1: Bot Detection
-    print(f"{Fore.YELLOW}1. Bot Detection Test (bot.sannysoft.com){Style.RESET_ALL}")
-    print("-" * 40)
-    
-    # Without stealth
-    regular_detection = await test_bot_detection(use_stealth=False)
-    if regular_detection["success"] and regular_detection["detection_data"]:
-        print(f"{Fore.RED}Without Stealth:{Style.RESET_ALL}")
-        data = regular_detection["detection_data"]
-        print(f"  • WebDriver detected: {data.get('webdriver', 'Unknown')}")
-        print(f"  • Chrome: {data.get('chrome', 'Unknown')}")
-        print(f"  • Languages: {data.get('languages', 'Unknown')}")
-        print(f"  • Plugins: {data.get('pluginsLength', 'Unknown')}")
-        print(f"  • User Agent: {data.get('userAgent', 'Unknown')[:60]}...")
-    
-    # With stealth
-    stealth_detection = await test_bot_detection(use_stealth=True)
-    if stealth_detection["success"] and stealth_detection["detection_data"]:
-        print(f"\n{Fore.GREEN}With Stealth:{Style.RESET_ALL}")
-        data = stealth_detection["detection_data"]
-        print(f"  • WebDriver detected: {data.get('webdriver', 'Unknown')}")
-        print(f"  • Chrome: {data.get('chrome', 'Unknown')}")
-        print(f"  • Languages: {data.get('languages', 'Unknown')}")
-        print(f"  • Plugins: {data.get('pluginsLength', 'Unknown')}")
-        print(f"  • User Agent: {data.get('userAgent', 'Unknown')[:60]}...")
-    
-    # Test 2: Cloudflare Site
-    print(f"\n\n{Fore.YELLOW}2. Cloudflare Protected Site Test{Style.RESET_ALL}")
-    print("-" * 40)
-    
-    # Without stealth
-    regular_cf = await test_cloudflare_site(use_stealth=False)
-    print(f"{Fore.RED}Without Stealth:{Style.RESET_ALL}")
-    print(f"  • Success: {regular_cf['success']}")
-    print(f"  • Cloudflare Challenge: {regular_cf['cloudflare_challenge']}")
-    print(f"  • Status Code: {regular_cf['status_code']}")
-    print(f"  • Page Title: {regular_cf['page_title']}")
-    
-    # With stealth
-    stealth_cf = await test_cloudflare_site(use_stealth=True)
-    print(f"\n{Fore.GREEN}With Stealth:{Style.RESET_ALL}")
-    print(f"  • Success: {stealth_cf['success']}")
-    print(f"  • Cloudflare Challenge: {stealth_cf['cloudflare_challenge']}")
-    print(f"  • Status Code: {stealth_cf['status_code']}")
-    print(f"  • Page Title: {stealth_cf['page_title']}")
-    
-    # Test 3: Anti-bot Site
-    print(f"\n\n{Fore.YELLOW}3. Anti-Bot Site Test{Style.RESET_ALL}")
-    print("-" * 40)
-    
-    # Without stealth
-    regular_antibot = await test_anti_bot_site(use_stealth=False)
-    print(f"{Fore.RED}Without Stealth:{Style.RESET_ALL}")
-    print(f"  • Success: {regular_antibot['success']}")
-    print(f"  • Blocked: {regular_antibot['blocked']}")
-    print(f"  • Status Code: {regular_antibot['status_code']}")
-    print(f"  • Page Title: {regular_antibot['page_title']}")
-    
-    # With stealth
-    stealth_antibot = await test_anti_bot_site(use_stealth=True)
-    print(f"\n{Fore.GREEN}With Stealth:{Style.RESET_ALL}")
-    print(f"  • Success: {stealth_antibot['success']}")
-    print(f"  • Blocked: {stealth_antibot['blocked']}")
-    print(f"  • Status Code: {stealth_antibot['status_code']}")
-    print(f"  • Page Title: {stealth_antibot['page_title']}")
-    
-    # Summary
-    print(f"\n{Fore.CYAN}{'='*60}{Style.RESET_ALL}")
-    print(f"{Fore.CYAN}Summary:{Style.RESET_ALL}")
-    print(f"{Fore.CYAN}{'='*60}{Style.RESET_ALL}")
-    print(f"\nStealth mode helps bypass basic bot detection by:")
-    print(f"  • Hiding webdriver property")
-    print(f"  • Modifying browser fingerprints")
-    print(f"  • Adjusting navigator properties")
-    print(f"  • Emulating real browser plugin behavior")
-    print(f"\n{Fore.YELLOW}Note:{Style.RESET_ALL} Stealth mode is not a silver bullet.")
-    print(f"Advanced anti-bot systems may still detect automation.")
-    print(f"Always respect robots.txt and website terms of service.")
-
-
-async def stealth_best_practices():
-    """Demonstrate best practices for using stealth mode"""
-    
-    print(f"\n\n{Fore.CYAN}{'='*60}{Style.RESET_ALL}")
-    print(f"{Fore.CYAN}Stealth Mode Best Practices{Style.RESET_ALL}")
-    print(f"{Fore.CYAN}{'='*60}{Style.RESET_ALL}\n")
-    
-    # Best Practice 1: Combine with realistic behavior
-    print(f"{Fore.YELLOW}1. Combine with Realistic Behavior:{Style.RESET_ALL}")
-    
-    browser_config = BrowserConfig(
-        headless=False,
-        enable_stealth=True,
-        viewport_width=1920,
-        viewport_height=1080
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        # Simulate human-like behavior
-        human_behavior_script = """
-        (async () => {
-            // Wait random time between actions
-            const randomWait = () => Math.random() * 2000 + 1000;
-            
-            // Simulate reading
-            await new Promise(resolve => setTimeout(resolve, randomWait()));
-            
-            // Smooth scroll
-            const smoothScroll = async () => {
-                const totalHeight = document.body.scrollHeight;
-                const viewHeight = window.innerHeight;
-                let currentPosition = 0;
-                
-                while (currentPosition < totalHeight - viewHeight) {
-                    const scrollAmount = Math.random() * 300 + 100;
-                    window.scrollBy({
-                        top: scrollAmount,
-                        behavior: 'smooth'
-                    });
-                    currentPosition += scrollAmount;
-                    await new Promise(resolve => setTimeout(resolve, randomWait()));
-                }
-            };
-            
-            await smoothScroll();
-            console.log('Human-like behavior simulation completed');
-            return true;
-        })()
-        """
-        
-        config = CrawlerRunConfig(
-            js_code=human_behavior_script,
-            wait_until="networkidle",
-            delay_before_return_html=3.0,
-            capture_console_messages=True
-        )
-        
-        result = await crawler.arun(
-            url="https://example.com",
-            config=config
-        )
-        
-        print(f"  ✓ Simulated human-like scrolling and reading patterns")
-        print(f"  ✓ Added random delays between actions")
-        print(f"  ✓ Result: {result.success}")
-    
-    # Best Practice 2: Use appropriate viewport and user agent
-    print(f"\n{Fore.YELLOW}2. Use Realistic Viewport and User Agent:{Style.RESET_ALL}")
-    
-    # Get a realistic user agent
-    from crawl4ai.user_agent_generator import UserAgentGenerator
-    ua_generator = UserAgentGenerator()
-    
-    browser_config = BrowserConfig(
-        headless=True,
-        enable_stealth=True,
-        viewport_width=1920,
-        viewport_height=1080,
-        user_agent=ua_generator.generate(device_type="desktop", browser_type="chrome")
-    )
-    
-    print(f"  ✓ Using realistic viewport: 1920x1080")
-    print(f"  ✓ Using current Chrome user agent")
-    print(f"  ✓ Stealth mode will ensure consistency")
-    
-    # Best Practice 3: Manage request rate
-    print(f"\n{Fore.YELLOW}3. Manage Request Rate:{Style.RESET_ALL}")
-    print(f"  ✓ Add delays between requests")
-    print(f"  ✓ Randomize timing patterns")
-    print(f"  ✓ Respect robots.txt")
-    
-    # Best Practice 4: Session management
-    print(f"\n{Fore.YELLOW}4. Use Session Management:{Style.RESET_ALL}")
-    
-    browser_config = BrowserConfig(
-        headless=False,
-        enable_stealth=True
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        # Create a session for multiple requests
-        session_id = "stealth_session_1"
-        
-        config = CrawlerRunConfig(
-            session_id=session_id,
-            wait_until="domcontentloaded"
-        )
-        
-        # First request
-        result1 = await crawler.arun(
-            url="https://example.com",
-            config=config
-        )
-        
-        # Subsequent request reuses the same browser context
-        result2 = await crawler.arun(
-            url="https://example.com/about",
-            config=config
-        )
-        
-        print(f"  ✓ Reused browser session for multiple requests")
-        print(f"  ✓ Maintains cookies and state between requests")
-        print(f"  ✓ More efficient and realistic browsing pattern")
-    
-    print(f"\n{Fore.CYAN}{'='*60}{Style.RESET_ALL}")
-
-
-async def main():
-    """Run all examples"""
-    
-    # Run comparison tests
-    await compare_results()
-    
-    # Show best practices
-    await stealth_best_practices()
-    
-    print(f"\n{Fore.GREEN}Examples completed!{Style.RESET_ALL}")
-    print(f"\n{Fore.YELLOW}Remember:{Style.RESET_ALL}")
-    print(f"• Stealth mode helps with basic bot detection")
-    print(f"• Always respect website terms of service")
-    print(f"• Consider rate limiting and ethical scraping practices")
-    print(f"• For advanced protection, consider additional measures")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/stealth_mode_quick_start.py
+++ b/docs/examples/stealth_mode_quick_start.py
@@ -1,215 +0,0 @@
-"""
-Quick Start: Using Stealth Mode in Crawl4AI
-
-This example shows practical use cases for the stealth mode feature.
-Stealth mode helps bypass basic bot detection mechanisms.
-"""
-
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
-
-
-async def example_1_basic_stealth():
-    """Example 1: Basic stealth mode usage"""
-    print("\n=== Example 1: Basic Stealth Mode ===")
-    
-    # Enable stealth mode in browser config
-    browser_config = BrowserConfig(
-        enable_stealth=True,  # This is the key parameter
-        headless=True
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(url="https://example.com")
-        print(f"✓ Crawled {result.url} successfully")
-        print(f"✓ Title: {result.metadata.get('title', 'N/A')}")
-
-
-async def example_2_stealth_with_screenshot():
-    """Example 2: Stealth mode with screenshot to show detection results"""
-    print("\n=== Example 2: Stealth Mode Visual Verification ===")
-    
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=False  # Set to False to see the browser
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        config = CrawlerRunConfig(
-            screenshot=True,
-            wait_until="networkidle"
-        )
-        
-        result = await crawler.arun(
-            url="https://bot.sannysoft.com",
-            config=config
-        )
-        
-        if result.success:
-            print(f"✓ Successfully crawled bot detection site")
-            print(f"✓ With stealth enabled, many detection tests should show as passed")
-            
-            if result.screenshot:
-                # Save screenshot for verification
-                import base64
-                with open("stealth_detection_results.png", "wb") as f:
-                    f.write(base64.b64decode(result.screenshot))
-                print(f"✓ Screenshot saved as 'stealth_detection_results.png'")
-                print(f"  Check the screenshot to see detection results!")
-
-
-async def example_3_stealth_for_protected_sites():
-    """Example 3: Using stealth for sites with bot protection"""
-    print("\n=== Example 3: Stealth for Protected Sites ===")
-    
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=True,
-        viewport_width=1920,
-        viewport_height=1080
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        # Add human-like behavior
-        config = CrawlerRunConfig(
-            wait_until="networkidle",
-            delay_before_return_html=2.0,  # Wait 2 seconds
-            js_code="""
-            // Simulate human-like scrolling
-            window.scrollTo({
-                top: document.body.scrollHeight / 2,
-                behavior: 'smooth'
-            });
-            """
-        )
-        
-        # Try accessing a site that might have bot protection
-        result = await crawler.arun(
-            url="https://www.g2.com/products/slack/reviews",
-            config=config
-        )
-        
-        if result.success:
-            print(f"✓ Successfully accessed protected site")
-            print(f"✓ Retrieved {len(result.html)} characters of HTML")
-        else:
-            print(f"✗ Failed to access site: {result.error_message}")
-
-
-async def example_4_stealth_with_sessions():
-    """Example 4: Stealth mode with session management"""
-    print("\n=== Example 4: Stealth + Session Management ===")
-    
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=False
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        session_id = "my_stealth_session"
-        
-        # First request - establish session
-        config = CrawlerRunConfig(
-            session_id=session_id,
-            wait_until="domcontentloaded"
-        )
-        
-        result1 = await crawler.arun(
-            url="https://news.ycombinator.com",
-            config=config
-        )
-        print(f"✓ First request completed: {result1.url}")
-        
-        # Second request - reuse session
-        await asyncio.sleep(2)  # Brief delay between requests
-        
-        result2 = await crawler.arun(
-            url="https://news.ycombinator.com/best",
-            config=config
-        )
-        print(f"✓ Second request completed: {result2.url}")
-        print(f"✓ Session reused, maintaining cookies and state")
-
-
-async def example_5_stealth_comparison():
-    """Example 5: Compare results with and without stealth using screenshots"""
-    print("\n=== Example 5: Stealth Mode Comparison ===")
-    
-    test_url = "https://bot.sannysoft.com"
-    
-    # First test WITHOUT stealth
-    print("\nWithout stealth:")
-    regular_config = BrowserConfig(
-        enable_stealth=False,
-        headless=True
-    )
-    
-    async with AsyncWebCrawler(config=regular_config) as crawler:
-        config = CrawlerRunConfig(
-            screenshot=True,
-            wait_until="networkidle"
-        )
-        result = await crawler.arun(url=test_url, config=config)
-        
-        if result.success and result.screenshot:
-            import base64
-            with open("comparison_without_stealth.png", "wb") as f:
-                f.write(base64.b64decode(result.screenshot))
-            print(f"  ✓ Screenshot saved: comparison_without_stealth.png")
-            print(f"  Many tests will show as FAILED (red)")
-    
-    # Then test WITH stealth
-    print("\nWith stealth:")
-    stealth_config = BrowserConfig(
-        enable_stealth=True,
-        headless=True
-    )
-    
-    async with AsyncWebCrawler(config=stealth_config) as crawler:
-        config = CrawlerRunConfig(
-            screenshot=True,
-            wait_until="networkidle"
-        )
-        result = await crawler.arun(url=test_url, config=config)
-        
-        if result.success and result.screenshot:
-            import base64
-            with open("comparison_with_stealth.png", "wb") as f:
-                f.write(base64.b64decode(result.screenshot))
-            print(f"  ✓ Screenshot saved: comparison_with_stealth.png")
-            print(f"  More tests should show as PASSED (green)")
-    
-    print("\nCompare the two screenshots to see the difference!")
-
-
-async def main():
-    """Run all examples"""
-    print("Crawl4AI Stealth Mode Examples")
-    print("==============================")
-    
-    # Run basic example
-    await example_1_basic_stealth()
-    
-    # Run screenshot verification example
-    await example_2_stealth_with_screenshot()
-    
-    # Run protected site example
-    await example_3_stealth_for_protected_sites()
-    
-    # Run session example
-    await example_4_stealth_with_sessions()
-    
-    # Run comparison example
-    await example_5_stealth_comparison()
-    
-    print("\n" + "="*50)
-    print("Tips for using stealth mode effectively:")
-    print("- Use realistic viewport sizes (1920x1080, 1366x768)")
-    print("- Add delays between requests to appear more human")
-    print("- Combine with session management for better results")
-    print("- Remember: stealth mode is for legitimate scraping only")
-    print("="*50)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/stealth_test_simple.py
+++ b/docs/examples/stealth_test_simple.py
@@ -1,62 +0,0 @@
-"""
-Simple test to verify stealth mode is working
-"""
-
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
-
-
-async def test_stealth():
-    """Test stealth mode effectiveness"""
-    
-    # Test WITHOUT stealth
-    print("=== WITHOUT Stealth ===")
-    config1 = BrowserConfig(
-        headless=False,
-        enable_stealth=False
-    )
-    
-    async with AsyncWebCrawler(config=config1) as crawler:
-        result = await crawler.arun(
-            url="https://bot.sannysoft.com",
-            config=CrawlerRunConfig(
-                wait_until="networkidle",
-                screenshot=True
-            )
-        )
-        print(f"Success: {result.success}")
-        # Take screenshot
-        if result.screenshot:
-            with open("without_stealth.png", "wb") as f:
-                import base64
-                f.write(base64.b64decode(result.screenshot))
-            print("Screenshot saved: without_stealth.png")
-    
-    # Test WITH stealth
-    print("\n=== WITH Stealth ===")
-    config2 = BrowserConfig(
-        headless=False,
-        enable_stealth=True
-    )
-    
-    async with AsyncWebCrawler(config=config2) as crawler:
-        result = await crawler.arun(
-            url="https://bot.sannysoft.com",
-            config=CrawlerRunConfig(
-                wait_until="networkidle",
-                screenshot=True
-            )
-        )
-        print(f"Success: {result.success}")
-        # Take screenshot
-        if result.screenshot:
-            with open("with_stealth.png", "wb") as f:
-                import base64
-                f.write(base64.b64decode(result.screenshot))
-            print("Screenshot saved: with_stealth.png")
-    
-    print("\nCheck the screenshots to see the difference in bot detection results!")
-
-
-if __name__ == "__main__":
-    asyncio.run(test_stealth())
--- a/docs/examples/undetectability/undetected_basic_test.py
+++ b/docs/examples/undetectability/undetected_basic_test.py
@@ -1,74 +0,0 @@
-"""
-Basic Undetected Browser Test
-Simple example to test if undetected mode works
-"""
-
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig
-
-async def test_regular_mode():
-    """Test with regular browser"""
-    print("Testing Regular Browser Mode...")
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(url="https://www.example.com")
-        print(f"Regular Mode - Success: {result.success}")
-        print(f"Regular Mode - Status: {result.status_code}")
-        print(f"Regular Mode - Content length: {len(result.markdown.raw_markdown)}")
-        print(f"Regular Mode - First 100 chars: {result.markdown.raw_markdown[:100]}...")
-        return result.success
-
-async def test_undetected_mode():
-    """Test with undetected browser"""
-    print("\nTesting Undetected Browser Mode...")
-    from crawl4ai import UndetectedAdapter
-    from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-    
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True
-    )
-    
-    # Create undetected adapter
-    undetected_adapter = UndetectedAdapter()
-    
-    # Create strategy with undetected adapter
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=undetected_adapter
-    )
-    
-    async with AsyncWebCrawler(
-        crawler_strategy=crawler_strategy,
-        config=browser_config
-    ) as crawler:
-        result = await crawler.arun(url="https://www.example.com")
-        print(f"Undetected Mode - Success: {result.success}")
-        print(f"Undetected Mode - Status: {result.status_code}")
-        print(f"Undetected Mode - Content length: {len(result.markdown.raw_markdown)}")
-        print(f"Undetected Mode - First 100 chars: {result.markdown.raw_markdown[:100]}...")
-        return result.success
-
-async def main():
-    """Run both tests"""
-    print("🤖 Crawl4AI Basic Adapter Test\n")
-    
-    # Test regular mode
-    regular_success = await test_regular_mode()
-    
-    # Test undetected mode
-    undetected_success = await test_undetected_mode()
-    
-    # Summary
-    print("\n" + "="*50)
-    print("Summary:")
-    print(f"Regular Mode: {'✅ Success' if regular_success else '❌ Failed'}")
-    print(f"Undetected Mode: {'✅ Success' if undetected_success else '❌ Failed'}")
-    print("="*50)
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/undetectability/undetected_bot_test.py
+++ b/docs/examples/undetectability/undetected_bot_test.py
@@ -1,155 +0,0 @@
-"""
-Bot Detection Test - Compare Regular vs Undetected
-Tests browser fingerprinting differences at bot.sannysoft.com
-"""
-
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler, 
-    BrowserConfig, 
-    CrawlerRunConfig,
-    UndetectedAdapter,
-    CrawlResult
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-# Bot detection test site
-TEST_URL = "https://bot.sannysoft.com"
-
-def analyze_bot_detection(result: CrawlResult) -> dict:
-    """Analyze bot detection results from the page"""
-    detections = {
-        "webdriver": False,
-        "headless": False, 
-        "automation": False,
-        "user_agent": False,
-        "total_tests": 0,
-        "failed_tests": 0
-    }
-    
-    if not result.success or not result.html:
-        return detections
-    
-    # Look for specific test results in the HTML
-    html_lower = result.html.lower()
-    
-    # Check for common bot indicators
-    if "webdriver" in html_lower and ("fail" in html_lower or "true" in html_lower):
-        detections["webdriver"] = True
-        detections["failed_tests"] += 1
-    
-    if "headless" in html_lower and ("fail" in html_lower or "true" in html_lower):
-        detections["headless"] = True
-        detections["failed_tests"] += 1
-    
-    if "automation" in html_lower and "detected" in html_lower:
-        detections["automation"] = True
-        detections["failed_tests"] += 1
-    
-    # Count total tests (approximate)
-    detections["total_tests"] = html_lower.count("test") + html_lower.count("check")
-    
-    return detections
-
-async def test_browser_mode(adapter_name: str, adapter=None):
-    """Test a browser mode and return results"""
-    print(f"\n{'='*60}")
-    print(f"Testing: {adapter_name}")
-    print(f"{'='*60}")
-    
-    browser_config = BrowserConfig(
-        headless=False,  # Run in headed mode for better results
-        verbose=True,
-        viewport_width=1920,
-        viewport_height=1080,
-    )
-    
-    if adapter:
-        # Use undetected mode
-        crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-            browser_config=browser_config,
-            browser_adapter=adapter
-        )
-        crawler = AsyncWebCrawler(
-            crawler_strategy=crawler_strategy,
-            config=browser_config
-        )
-    else:
-        # Use regular mode
-        crawler = AsyncWebCrawler(config=browser_config)
-    
-    async with crawler:
-        config = CrawlerRunConfig(
-            delay_before_return_html=3.0,  # Let detection scripts run
-            wait_for_images=True,
-            screenshot=True,
-            simulate_user=False,  # Don't simulate for accurate detection
-        )
-        
-        result = await crawler.arun(url=TEST_URL, config=config)
-        
-        print(f"\n✓ Success: {result.success}")
-        print(f"✓ Status Code: {result.status_code}")
-        
-        if result.success:
-            # Analyze detection results
-            detections = analyze_bot_detection(result)
-            
-            print(f"\n🔍 Bot Detection Analysis:")
-            print(f"  - WebDriver Detected: {'❌ Yes' if detections['webdriver'] else '✅ No'}")
-            print(f"  - Headless Detected: {'❌ Yes' if detections['headless'] else '✅ No'}")
-            print(f"  - Automation Detected: {'❌ Yes' if detections['automation'] else '✅ No'}")
-            print(f"  - Failed Tests: {detections['failed_tests']}")
-            
-            # Show some content
-            if result.markdown.raw_markdown:
-                print(f"\nContent preview:")
-                lines = result.markdown.raw_markdown.split('\n')
-                for line in lines[:20]:  # Show first 20 lines
-                    if any(keyword in line.lower() for keyword in ['test', 'pass', 'fail', 'yes', 'no']):
-                        print(f"  {line.strip()}")
-        
-        return result, detections if result.success else {}
-
-async def main():
-    """Run the comparison"""
-    print("🤖 Crawl4AI - Bot Detection Test")
-    print(f"Testing at: {TEST_URL}")
-    print("This site runs various browser fingerprinting tests\n")
-    
-    # Test regular browser
-    regular_result, regular_detections = await test_browser_mode("Regular Browser")
-    
-    # Small delay
-    await asyncio.sleep(2)
-    
-    # Test undetected browser
-    undetected_adapter = UndetectedAdapter()
-    undetected_result, undetected_detections = await test_browser_mode(
-        "Undetected Browser", 
-        undetected_adapter
-    )
-    
-    # Summary comparison
-    print(f"\n{'='*60}")
-    print("COMPARISON SUMMARY")
-    print(f"{'='*60}")
-    
-    print(f"\n{'Test':<25} {'Regular':<15} {'Undetected':<15}")
-    print(f"{'-'*55}")
-    
-    if regular_detections and undetected_detections:
-        print(f"{'WebDriver Detection':<25} {'❌ Detected' if regular_detections['webdriver'] else '✅ Passed':<15} {'❌ Detected' if undetected_detections['webdriver'] else '✅ Passed':<15}")
-        print(f"{'Headless Detection':<25} {'❌ Detected' if regular_detections['headless'] else '✅ Passed':<15} {'❌ Detected' if undetected_detections['headless'] else '✅ Passed':<15}")
-        print(f"{'Automation Detection':<25} {'❌ Detected' if regular_detections['automation'] else '✅ Passed':<15} {'❌ Detected' if undetected_detections['automation'] else '✅ Passed':<15}")
-        print(f"{'Failed Tests':<25} {regular_detections['failed_tests']:<15} {undetected_detections['failed_tests']:<15}")
-    
-    print(f"\n{'='*60}")
-    
-    if undetected_detections.get('failed_tests', 0) < regular_detections.get('failed_tests', 1):
-        print("✅ Undetected browser performed better at evading detection!")
-    else:
-        print("ℹ️  Both browsers had similar detection results")
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/undetectability/undetected_cloudflare_test.py
+++ b/docs/examples/undetectability/undetected_cloudflare_test.py
@@ -1,164 +0,0 @@
-"""
-Undetected Browser Test - Cloudflare Protected Site
-Tests the difference between regular and undetected modes on a Cloudflare-protected site
-"""
-
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler, 
-    BrowserConfig, 
-    CrawlerRunConfig,
-    UndetectedAdapter
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-# Test URL with Cloudflare protection
-TEST_URL = "https://nowsecure.nl"
-
-async def test_regular_browser():
-    """Test with regular browser - likely to be blocked"""
-    print("=" * 60)
-    print("Testing with Regular Browser")
-    print("=" * 60)
-    
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True,
-        viewport_width=1920,
-        viewport_height=1080,
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        config = CrawlerRunConfig(
-            delay_before_return_html=2.0,
-            simulate_user=True,
-            magic=True,  # Try with magic mode too
-        )
-        
-        result = await crawler.arun(url=TEST_URL, config=config)
-        
-        print(f"\n✓ Success: {result.success}")
-        print(f"✓ Status Code: {result.status_code}")
-        print(f"✓ HTML Length: {len(result.html)}")
-        
-        # Check for Cloudflare challenge
-        if result.html:
-            cf_indicators = [
-                "Checking your browser",
-                "Please stand by",
-                "cloudflare",
-                "cf-browser-verification",
-                "Access denied",
-                "Ray ID"
-            ]
-            
-            detected = False
-            for indicator in cf_indicators:
-                if indicator.lower() in result.html.lower():
-                    print(f"⚠️  Cloudflare Challenge Detected: '{indicator}' found")
-                    detected = True
-                    break
-            
-            if not detected and len(result.markdown.raw_markdown) > 100:
-                print("✅ Successfully bypassed Cloudflare!")
-                print(f"Content preview: {result.markdown.raw_markdown[:200]}...")
-            elif not detected:
-                print("⚠️  Page loaded but content seems minimal")
-        
-        return result
-
-async def test_undetected_browser():
-    """Test with undetected browser - should bypass Cloudflare"""
-    print("\n" + "=" * 60)
-    print("Testing with Undetected Browser")
-    print("=" * 60)
-    
-    browser_config = BrowserConfig(
-        headless=False,  # Headless is easier to detect
-        verbose=True,
-        viewport_width=1920,
-        viewport_height=1080,
-    )
-    
-    # Create undetected adapter
-    undetected_adapter = UndetectedAdapter()
-    
-    # Create strategy with undetected adapter
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=undetected_adapter
-    )
-    
-    async with AsyncWebCrawler(
-        crawler_strategy=crawler_strategy,
-        config=browser_config
-    ) as crawler:
-        config = CrawlerRunConfig(
-            delay_before_return_html=2.0,
-            simulate_user=True,
-        )
-        
-        result = await crawler.arun(url=TEST_URL, config=config)
-        
-        print(f"\n✓ Success: {result.success}")
-        print(f"✓ Status Code: {result.status_code}")
-        print(f"✓ HTML Length: {len(result.html)}")
-        
-        # Check for Cloudflare challenge
-        if result.html:
-            cf_indicators = [
-                "Checking your browser",
-                "Please stand by",
-                "cloudflare",
-                "cf-browser-verification",
-                "Access denied",
-                "Ray ID"
-            ]
-            
-            detected = False
-            for indicator in cf_indicators:
-                if indicator.lower() in result.html.lower():
-                    print(f"⚠️  Cloudflare Challenge Detected: '{indicator}' found")
-                    detected = True
-                    break
-            
-            if not detected and len(result.markdown.raw_markdown) > 100:
-                print("✅ Successfully bypassed Cloudflare!")
-                print(f"Content preview: {result.markdown.raw_markdown[:200]}...")
-            elif not detected:
-                print("⚠️  Page loaded but content seems minimal")
-        
-        return result
-
-async def main():
-    """Compare regular vs undetected browser"""
-    print("🤖 Crawl4AI - Cloudflare Bypass Test")
-    print(f"Testing URL: {TEST_URL}\n")
-    
-    # Test regular browser
-    regular_result = await test_regular_browser()
-    
-    # Small delay
-    await asyncio.sleep(2)
-    
-    # Test undetected browser
-    undetected_result = await test_undetected_browser()
-    
-    # Summary
-    print("\n" + "=" * 60)
-    print("SUMMARY")
-    print("=" * 60)
-    print(f"Regular Browser:")
-    print(f"  - Success: {regular_result.success}")
-    print(f"  - Content Length: {len(regular_result.markdown.raw_markdown) if regular_result.markdown else 0}")
-    
-    print(f"\nUndetected Browser:")
-    print(f"  - Success: {undetected_result.success}")
-    print(f"  - Content Length: {len(undetected_result.markdown.raw_markdown) if undetected_result.markdown else 0}")
-    
-    if undetected_result.success and len(undetected_result.markdown.raw_markdown) > len(regular_result.markdown.raw_markdown):
-        print("\n✅ Undetected browser successfully bypassed protection!")
-    print("=" * 60)
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/examples/undetectability/undetected_vs_regular_comparison.py
+++ b/docs/examples/undetectability/undetected_vs_regular_comparison.py
@@ -1,184 +0,0 @@
-"""
-Undetected vs Regular Browser Comparison
-This example demonstrates the difference between regular and undetected browser modes
-when accessing sites with bot detection services.
-
-Based on tested anti-bot services:
- Cloudflare
- Kasada
- Akamai
- DataDome
- Bet365
- And others
-"""
-
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler,
-    BrowserConfig,
-    CrawlerRunConfig,
-    PlaywrightAdapter,
-    UndetectedAdapter,
-    CrawlResult
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-
-# Test URLs for various bot detection services
-TEST_SITES = {
-    "Cloudflare Protected": "https://nowsecure.nl",
-    # "Bot Detection Test": "https://bot.sannysoft.com",
-    # "Fingerprint Test": "https://fingerprint.com/products/bot-detection",
-    # "Browser Scan": "https://browserscan.net",
-    # "CreepJS": "https://abrahamjuliot.github.io/creepjs",
-}
-
-
-async def test_with_adapter(url: str, adapter_name: str, adapter):
-    """Test a URL with a specific adapter"""
-    browser_config = BrowserConfig(
-        headless=False,  # Better for avoiding detection
-        viewport_width=1920,
-        viewport_height=1080,
-        verbose=True,
-    )
-    
-    # Create the crawler strategy with the adapter
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=adapter
-    )
-    
-    print(f"\n{'='*60}")
-    print(f"Testing with {adapter_name} adapter")
-    print(f"URL: {url}")
-    print(f"{'='*60}")
-    
-    try:
-        async with AsyncWebCrawler(
-            crawler_strategy=crawler_strategy,
-            config=browser_config
-        ) as crawler:
-            crawler_config = CrawlerRunConfig(
-                delay_before_return_html=3.0,  # Give page time to load
-                wait_for_images=True,
-                screenshot=True,
-                simulate_user=True,  # Add user simulation
-            )
-            
-            result: CrawlResult = await crawler.arun(
-                url=url,
-                config=crawler_config
-            )
-            
-            # Check results
-            print(f"✓ Status Code: {result.status_code}")
-            print(f"✓ Success: {result.success}")
-            print(f"✓ HTML Length: {len(result.html)}")
-            print(f"✓ Markdown Length: {len(result.markdown.raw_markdown)}")
-            
-            # Check for common bot detection indicators
-            detection_indicators = [
-                "Access denied",
-                "Please verify you are human",
-                "Checking your browser",
-                "Enable JavaScript",
-                "captcha",
-                "403 Forbidden",
-                "Bot detection",
-                "Security check"
-            ]
-            
-            content_lower = result.markdown.raw_markdown.lower()
-            detected = False
-            for indicator in detection_indicators:
-                if indicator.lower() in content_lower:
-                    print(f"⚠️  Possible detection: Found '{indicator}'")
-                    detected = True
-                    break
-            
-            if not detected:
-                print("✅ No obvious bot detection triggered!")
-                # Show first 200 chars of content
-                print(f"Content preview: {result.markdown.raw_markdown[:200]}...")
-            
-            return result.success and not detected
-            
-    except Exception as e:
-        print(f"❌ Error: {str(e)}")
-        return False
-
-
-async def compare_adapters(url: str, site_name: str):
-    """Compare regular and undetected adapters on the same URL"""
-    print(f"\n{'#'*60}")
-    print(f"# Testing: {site_name}")
-    print(f"{'#'*60}")
-    
-    # Test with regular adapter
-    regular_adapter = PlaywrightAdapter()
-    regular_success = await test_with_adapter(url, "Regular", regular_adapter)
-    
-    # Small delay between tests
-    await asyncio.sleep(2)
-    
-    # Test with undetected adapter
-    undetected_adapter = UndetectedAdapter()
-    undetected_success = await test_with_adapter(url, "Undetected", undetected_adapter)
-    
-    # Summary
-    print(f"\n{'='*60}")
-    print(f"Summary for {site_name}:")
-    print(f"Regular Adapter: {'✅ Passed' if regular_success else '❌ Blocked/Detected'}")
-    print(f"Undetected Adapter: {'✅ Passed' if undetected_success else '❌ Blocked/Detected'}")
-    print(f"{'='*60}")
-    
-    return regular_success, undetected_success
-
-
-async def main():
-    """Run comparison tests on multiple sites"""
-    print("🤖 Crawl4AI Browser Adapter Comparison")
-    print("Testing regular vs undetected browser modes\n")
-    
-    results = {}
-    
-    # Test each site
-    for site_name, url in TEST_SITES.items():
-        regular, undetected = await compare_adapters(url, site_name)
-        results[site_name] = {
-            "regular": regular,
-            "undetected": undetected
-        }
-        
-        # Delay between different sites
-        await asyncio.sleep(3)
-    
-    # Final summary
-    print(f"\n{'#'*60}")
-    print("# FINAL RESULTS")
-    print(f"{'#'*60}")
-    print(f"{'Site':<30} {'Regular':<15} {'Undetected':<15}")
-    print(f"{'-'*60}")
-    
-    for site, result in results.items():
-        regular_status = "✅ Passed" if result["regular"] else "❌ Blocked"
-        undetected_status = "✅ Passed" if result["undetected"] else "❌ Blocked"
-        print(f"{site:<30} {regular_status:<15} {undetected_status:<15}")
-    
-    # Calculate success rates
-    regular_success = sum(1 for r in results.values() if r["regular"])
-    undetected_success = sum(1 for r in results.values() if r["undetected"])
-    total = len(results)
-    
-    print(f"\n{'='*60}")
-    print(f"Success Rates:")
-    print(f"Regular Adapter: {regular_success}/{total} ({regular_success/total*100:.1f}%)")
-    print(f"Undetected Adapter: {undetected_success}/{total} ({undetected_success/total*100:.1f}%)")
-    print(f"{'='*60}")
-
-
-if __name__ == "__main__":
-    # Note: This example may take a while to run as it tests multiple sites
-    # You can comment out sites in TEST_SITES to run faster tests
-    asyncio.run(main())
--- a/docs/examples/undetected_simple_demo.py
+++ b/docs/examples/undetected_simple_demo.py
@@ -1,118 +0,0 @@
-"""
-Simple Undetected Browser Demo
-Demonstrates the basic usage of undetected browser mode
-"""
-
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler, 
-    BrowserConfig, 
-    CrawlerRunConfig,
-    UndetectedAdapter
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-async def crawl_with_regular_browser(url: str):
-    """Crawl with regular browser"""
-    print("\n[Regular Browser Mode]")
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True,
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(
-            url=url,
-            config=CrawlerRunConfig(
-                delay_before_return_html=2.0
-            )
-        )
-        
-        print(f"Success: {result.success}")
-        print(f"Status: {result.status_code}")
-        print(f"Content length: {len(result.markdown.raw_markdown)}")
-        
-        # Check for bot detection keywords
-        content = result.markdown.raw_markdown.lower()
-        if any(word in content for word in ["cloudflare", "checking your browser", "please wait"]):
-            print("⚠️  Bot detection triggered!")
-        else:
-            print("✅ Page loaded successfully")
-        
-        return result
-
-async def crawl_with_undetected_browser(url: str):
-    """Crawl with undetected browser"""
-    print("\n[Undetected Browser Mode]")
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True,
-    )
-    
-    # Create undetected adapter and strategy
-    undetected_adapter = UndetectedAdapter()
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=undetected_adapter
-    )
-    
-    async with AsyncWebCrawler(
-        crawler_strategy=crawler_strategy,
-        config=browser_config
-    ) as crawler:
-        result = await crawler.arun(
-            url=url,
-            config=CrawlerRunConfig(
-                delay_before_return_html=2.0
-            )
-        )
-        
-        print(f"Success: {result.success}")
-        print(f"Status: {result.status_code}")
-        print(f"Content length: {len(result.markdown.raw_markdown)}")
-        
-        # Check for bot detection keywords
-        content = result.markdown.raw_markdown.lower()
-        if any(word in content for word in ["cloudflare", "checking your browser", "please wait"]):
-            print("⚠️  Bot detection triggered!")
-        else:
-            print("✅ Page loaded successfully")
-        
-        return result
-
-async def main():
-    """Demo comparing regular vs undetected modes"""
-    print("🤖 Crawl4AI Undetected Browser Demo")
-    print("="*50)
-    
-    # Test URLs - you can change these
-    test_urls = [
-        "https://www.example.com",  # Simple site
-        "https://httpbin.org/headers",  # Shows request headers
-    ]
-    
-    for url in test_urls:
-        print(f"\n📍 Testing URL: {url}")
-        
-        # Test with regular browser
-        regular_result = await crawl_with_regular_browser(url)
-        
-        # Small delay
-        await asyncio.sleep(2)
-        
-        # Test with undetected browser
-        undetected_result = await crawl_with_undetected_browser(url)
-        
-        # Compare results
-        print(f"\n📊 Comparison for {url}:")
-        print(f"Regular browser content: {len(regular_result.markdown.raw_markdown)} chars")
-        print(f"Undetected browser content: {len(undetected_result.markdown.raw_markdown)} chars")
-        
-        if url == "https://httpbin.org/headers":
-            # Show headers for comparison
-            print("\nHeaders seen by server:")
-            print("Regular:", regular_result.markdown.raw_markdown[:500])
-            print("\nUndetected:", undetected_result.markdown.raw_markdown[:500])
-
-if __name__ == "__main__":
-    asyncio.run(main())
--- a/docs/md_v2/advanced/advanced-features.md
+++ b/docs/md_v2/advanced/advanced-features.md
@@ -358,77 +358,9 @@ if __name__ == "__main__":

 ---

---
-
-## 7. Anti-Bot Features (Stealth Mode & Undetected Browser)
-
-Crawl4AI provides two powerful features to bypass bot detection:
-
-### 7.1 Stealth Mode
-
-Stealth mode uses playwright-stealth to modify browser fingerprints and behaviors. Enable it with a simple flag:
-
-```python
-browser_config = BrowserConfig(
-    enable_stealth=True,  # Activates stealth mode
-    headless=False
-)
-```
-
-**When to use**: Sites with basic bot detection (checking navigator.webdriver, plugins, etc.)
-
-### 7.2 Undetected Browser
-
-For advanced bot detection, use the undetected browser adapter:
-
-```python
-from crawl4ai import UndetectedAdapter
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-# Create undetected adapter
-adapter = UndetectedAdapter()
-strategy = AsyncPlaywrightCrawlerStrategy(
-    browser_config=browser_config,
-    browser_adapter=adapter
-)
-
-async with AsyncWebCrawler(crawler_strategy=strategy, config=browser_config) as crawler:
-    # Your crawling code
-```
-
-**When to use**: Sites with sophisticated bot detection (Cloudflare, DataDome, etc.)
-
-### 7.3 Combining Both
-
-For maximum evasion, combine stealth mode with undetected browser:
-
-```python
-browser_config = BrowserConfig(
-    enable_stealth=True,  # Enable stealth
-    headless=False
-)
-
-adapter = UndetectedAdapter()  # Use undetected browser
-```
-
-### Choosing the Right Approach
-
-| Detection Level | Recommended Approach |
-|----------------|---------------------|
-| No protection | Regular browser |
-| Basic checks | Regular + Stealth mode |
-| Advanced protection | Undetected browser |
-| Maximum evasion | Undetected + Stealth mode |
-
-**Best Practice**: Start with regular browser + stealth mode. Only use undetected browser if needed, as it may be slightly slower.
-
-See [Undetected Browser Mode](undetected-browser.md) for detailed examples.
-
---
-
 ## Conclusion & Next Steps

-You've now explored several **advanced** features:
+You’ve now explored several **advanced** features:

 - **Proxy Usage**  
 - **PDF & Screenshot** capturing for large or critical pages  
@@ -436,10 +368,7 @@ You've now explored several **advanced** features:
 - **Custom Headers** for language or specialized requests  
 - **Session Persistence** via storage state
 - **Robots.txt Compliance**
- **Anti-Bot Features** (Stealth Mode & Undetected Browser)

-With these power tools, you can build robust scraping workflows that mimic real user behavior, handle secure sites, capture detailed snapshots, manage sessions across multiple runs, and bypass bot detection—streamlining your entire data collection pipeline.
+With these power tools, you can build robust scraping workflows that mimic real user behavior, handle secure sites, capture detailed snapshots, and manage sessions across multiple runs—streamlining your entire data collection pipeline.

-**Note**: In future versions, we may enable stealth mode and undetected browser by default. For now, users should explicitly enable these features when needed.
-
-**Last Updated**: 2025-01-17
+**Last Updated**: 2025-01-01
--- a/docs/md_v2/advanced/multi-url-crawling.md
+++ b/docs/md_v2/advanced/multi-url-crawling.md
@@ -404,182 +404,7 @@ for result in results:
        print(f"Duration: {dr.end_time - dr.start_time}")
 ```

-## 6. URL-Specific Configurations
-
-When crawling diverse content types, you often need different configurations for different URLs. For example:
- PDFs need specialized extraction
- Blog pages benefit from content filtering
- Dynamic sites need JavaScript execution
- API endpoints need JSON parsing
-
-### 6.1 Basic URL Pattern Matching
-
-```python
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, MatchMode
-from crawl4ai.processors.pdf import PDFContentScrapingStrategy
-from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
-from crawl4ai.content_filter_strategy import PruningContentFilter
-from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
-
-async def crawl_mixed_content():
-    # Configure different strategies for different content
-    configs = [
-        # PDF files - specialized extraction
-        CrawlerRunConfig(
-            url_matcher="*.pdf",
-            scraping_strategy=PDFContentScrapingStrategy()
-        ),
-        
-        # Blog/article pages - content filtering
-        CrawlerRunConfig(
-            url_matcher=["*/blog/*", "*/article/*"],
-            markdown_generator=DefaultMarkdownGenerator(
-                content_filter=PruningContentFilter(threshold=0.48)
-            )
-        ),
-        
-        # Dynamic pages - JavaScript execution
-        CrawlerRunConfig(
-            url_matcher=lambda url: 'github.com' in url,
-            js_code="window.scrollTo(0, 500);"
-        ),
-        
-        # API endpoints - JSON extraction
-        CrawlerRunConfig(
-            url_matcher=lambda url: 'api' in url or url.endswith('.json'),
-            # Custome settings for JSON extraction
-        ),
-        
-        # Default config for everything else
-        CrawlerRunConfig()  # No url_matcher means it matches ALL URLs (fallback)
-    ]
-    
-    # Mixed URLs
-    urls = [
-        "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",
-        "https://blog.python.org/",
-        "https://github.com/microsoft/playwright",
-        "https://httpbin.org/json",
-        "https://example.com/"
-    ]
-    
-    async with AsyncWebCrawler() as crawler:
-        results = await crawler.arun_many(
-            urls=urls,
-            config=configs  # Pass list of configs
-        )
-        
-        for result in results:
-            print(f"{result.url}: {len(result.markdown)} chars")
-```
-
-### 6.2 Advanced Pattern Matching
-
-**Important**: A `CrawlerRunConfig` without `url_matcher` (or with `url_matcher=None`) matches ALL URLs. This makes it perfect as a default/fallback configuration.
-
-The `url_matcher` parameter supports three types of patterns:
-
-#### Glob Patterns (Strings)
-```python
-# Simple patterns
-"*.pdf"                    # Any PDF file
-"*/api/*"                  # Any URL with /api/ in path
-"https://*.example.com/*"  # Subdomain matching
-"*://example.com/blog/*"   # Any protocol
-```
-
-#### Custom Functions
-```python
-# Complex logic with lambdas
-lambda url: url.startswith('https://') and 'secure' in url
-lambda url: len(url) > 50 and url.count('/') > 5
-lambda url: any(domain in url for domain in ['api.', 'data.', 'feed.'])
-```
-
-#### Mixed Lists with AND/OR Logic
-```python
-# Combine multiple conditions
-CrawlerRunConfig(
-    url_matcher=[
-        "https://*",                        # Must be HTTPS
-        lambda url: 'internal' in url,      # Must contain 'internal'
-        lambda url: not url.endswith('.pdf') # Must not be PDF
-    ],
-    match_mode=MatchMode.AND  # ALL conditions must match
-)
-```
-
-### 6.3 Practical Example: News Site Crawler
-
-```python
-async def crawl_news_site():
-    dispatcher = MemoryAdaptiveDispatcher(
-        memory_threshold_percent=70.0,
-        rate_limiter=RateLimiter(base_delay=(1.0, 2.0))
-    )
-    
-    configs = [
-        # Homepage - light extraction
-        CrawlerRunConfig(
-            url_matcher=lambda url: url.rstrip('/') == 'https://news.ycombinator.com',
-            css_selector="nav, .headline",
-            extraction_strategy=None
-        ),
-        
-        # Article pages - full extraction
-        CrawlerRunConfig(
-            url_matcher="*/article/*",
-            extraction_strategy=CosineStrategy(
-                semantic_filter="article content",
-                word_count_threshold=100
-            ),
-            screenshot=True,
-            excluded_tags=["nav", "aside", "footer"]
-        ),
-        
-        # Author pages - metadata focus
-        CrawlerRunConfig(
-            url_matcher="*/author/*",
-            extraction_strategy=JsonCssExtractionStrategy({
-                "name": "h1.author-name",
-                "bio": ".author-bio",
-                "articles": "article.post-card h2"
-            })
-        ),
-        
-        # Everything else
-        CrawlerRunConfig()
-    ]
-    
-    async with AsyncWebCrawler() as crawler:
-        results = await crawler.arun_many(
-            urls=news_urls,
-            config=configs,
-            dispatcher=dispatcher
-        )
-```
-
-### 6.4 Best Practices
-
-1. **Order Matters**: Configs are evaluated in order - put specific patterns before general ones
-2. **Default Config Behavior**: 
-   - A config without `url_matcher` matches ALL URLs
-   - Always include a default config as the last item if you want to handle all URLs
-   - Without a default config, unmatched URLs will fail with "No matching configuration found"
-3. **Test Your Patterns**: Use the config's `is_match()` method to test patterns:
-   ```python
-   config = CrawlerRunConfig(url_matcher="*.pdf")
-   print(config.is_match("https://example.com/doc.pdf"))  # True
-   
-   default_config = CrawlerRunConfig()  # No url_matcher
-   print(default_config.is_match("https://any-url.com"))  # True - matches everything!
-   ```
-4. **Optimize for Performance**: 
-   - Disable JS for static content
-   - Skip screenshots for data APIs
-   - Use appropriate extraction strategies
-
-## 7. Summary
+## 6. Summary

 1. **Two Dispatcher Types**:

--- a/docs/md_v2/advanced/session-management.md
+++ b/docs/md_v2/advanced/session-management.md
@@ -49,75 +49,46 @@ from crawl4ai import JsonCssExtractionStrategy
 from crawl4ai.cache_context import CacheMode

 async def crawl_dynamic_content():
-    url = "https://github.com/microsoft/TypeScript/commits/main"
-    session_id = "wait_for_session"
-    all_commits = []
+    async with AsyncWebCrawler() as crawler:
+        session_id = "github_commits_session"
+        url = "https://github.com/microsoft/TypeScript/commits/main"
+        all_commits = []

-    js_next_page = """
-    const commits = document.querySelectorAll('li[data-testid="commit-row-item"] h4');
-    if (commits.length > 0) {
-        window.lastCommit = commits[0].textContent.trim();
-    }
-    const button = document.querySelector('a[data-testid="pagination-next-button"]');
-    if (button) {button.click(); console.log('button clicked') }
-    """
+        # Define extraction schema
+        schema = {
+            "name": "Commit Extractor",
+            "baseSelector": "li.Box-sc-g0xbh4-0",
+            "fields": [{
+                "name": "title", "selector": "h4.markdown-title", "type": "text"
+            }],
+        }
+        extraction_strategy = JsonCssExtractionStrategy(schema)

-    wait_for = """() => {
-        const commits = document.querySelectorAll('li[data-testid="commit-row-item"] h4');
-        if (commits.length === 0) return false;
-        const firstCommit = commits[0].textContent.trim();
-        return firstCommit !== window.lastCommit;
-    }"""
-    
-    schema = {
-        "name": "Commit Extractor",
-        "baseSelector": "li[data-testid='commit-row-item']",
-        "fields": [
-            {
-                "name": "title",
-                "selector": "h4 a",
-                "type": "text",
-                "transform": "strip",
-            },
-        ],
-    }
-    extraction_strategy = JsonCssExtractionStrategy(schema, verbose=True)
-    
-    
-    browser_config = BrowserConfig(
-        verbose=True,
-        headless=False,
-    )
-        
-    async with AsyncWebCrawler(config=browser_config) as crawler:
+        # JavaScript and wait configurations
+        js_next_page = """document.querySelector('a[data-testid="pagination-next-button"]').click();"""
+        wait_for = """() => document.querySelectorAll('li.Box-sc-g0xbh4-0').length > 0"""
+
+        # Crawl multiple pages
        for page in range(3):
-            crawler_config = CrawlerRunConfig(
+            config = CrawlerRunConfig(
+                url=url,
                session_id=session_id,
-                css_selector="li[data-testid='commit-row-item']",
                extraction_strategy=extraction_strategy,
                js_code=js_next_page if page > 0 else None,
                wait_for=wait_for if page > 0 else None,
                js_only=page > 0,
-                cache_mode=CacheMode.BYPASS,
-                capture_console_messages=True,
+                cache_mode=CacheMode.BYPASS
            )
-            
-            result = await crawler.arun(url=url, config=crawler_config)
-            
-            if result.console_messages:
-                print(f"Page {page + 1} console messages:", result.console_messages)
-            
-            if result.extracted_content:
-                # print(f"Page {page + 1} result:", result.extracted_content)
+
+            result = await crawler.arun(config=config)
+            if result.success:
                commits = json.loads(result.extracted_content)
                all_commits.extend(commits)
                print(f"Page {page + 1}: Found {len(commits)} commits")
-            else:
-                print(f"Page {page + 1}: No content extracted")

-        print(f"Successfully crawled {len(all_commits)} commits across 3 pages")
        # Clean up session
        await crawler.crawler_strategy.kill_session(session_id)
+        return all_commits
 ```

 ---
--- a/docs/md_v2/advanced/undetected-browser.md
+++ b/docs/md_v2/advanced/undetected-browser.md
@@ -1,394 +0,0 @@
-# Undetected Browser Mode
-
-## Overview
-
-Crawl4AI offers two powerful anti-bot features to help you access websites with bot detection:
-
-1. **Stealth Mode** - Uses playwright-stealth to modify browser fingerprints and behaviors
-2. **Undetected Browser Mode** - Advanced browser adapter with deep-level patches for sophisticated bot detection
-
-This guide covers both features and helps you choose the right approach for your needs.
-
-## Anti-Bot Features Comparison
-
-| Feature | Regular Browser | Stealth Mode | Undetected Browser |
-|---------|----------------|--------------|-------------------|
-| WebDriver Detection | ❌ | ✅ | ✅ |
-| Navigator Properties | ❌ | ✅ | ✅ |
-| Plugin Emulation | ❌ | ✅ | ✅ |
-| CDP Detection | ❌ | Partial | ✅ |
-| Deep Browser Patches | ❌ | ❌ | ✅ |
-| Performance Impact | None | Minimal | Moderate |
-| Setup Complexity | None | None | Minimal |
-
-## When to Use Each Approach
-
-### Use Regular Browser + Stealth Mode When:
- Sites have basic bot detection (checking navigator.webdriver, plugins, etc.)
- You need good performance with basic protection
- Sites check for common automation indicators
-
-### Use Undetected Browser When:
- Sites employ sophisticated bot detection services (Cloudflare, DataDome, etc.)
- Stealth mode alone isn't sufficient
- You're willing to trade some performance for better evasion
-
-### Best Practice: Progressive Enhancement
-1. **Start with**: Regular browser + Stealth mode
-2. **If blocked**: Switch to Undetected browser
-3. **If still blocked**: Combine Undetected browser + Stealth mode
-
-## Stealth Mode
-
-Stealth mode is the simpler anti-bot solution that works with both regular and undetected browsers:
-
-```python
-from crawl4ai import AsyncWebCrawler, BrowserConfig
-
-# Enable stealth mode with regular browser
-browser_config = BrowserConfig(
-    enable_stealth=True,  # Simple flag to enable
-    headless=False       # Better for avoiding detection
-)
-
-async with AsyncWebCrawler(config=browser_config) as crawler:
-    result = await crawler.arun("https://example.com")
-```
-
-### What Stealth Mode Does:
- Removes `navigator.webdriver` flag
- Modifies browser fingerprints
- Emulates realistic plugin behavior
- Adjusts navigator properties
- Fixes common automation leaks
-
-## Undetected Browser Mode
-
-For sites with sophisticated bot detection that stealth mode can't bypass, use the undetected browser adapter:
-
-### Key Features
-
- **Drop-in Replacement**: Uses the same API as regular browser mode
- **Enhanced Stealth**: Built-in patches to evade common detection methods
- **Browser Adapter Pattern**: Seamlessly switch between regular and undetected modes
- **Automatic Installation**: `crawl4ai-setup` installs all necessary browser dependencies
-
-### Quick Start
-
-```python
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler, 
-    BrowserConfig, 
-    CrawlerRunConfig,
-    UndetectedAdapter
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-async def main():
-    # Create the undetected adapter
-    undetected_adapter = UndetectedAdapter()
-    
-    # Create browser config
-    browser_config = BrowserConfig(
-        headless=False,  # Headless mode can be detected easier
-        verbose=True,
-    )
-    
-    # Create the crawler strategy with undetected adapter
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=undetected_adapter
-    )
-    
-    # Create the crawler with our custom strategy
-    async with AsyncWebCrawler(
-        crawler_strategy=crawler_strategy,
-        config=browser_config
-    ) as crawler:
-        # Your crawling code here
-        result = await crawler.arun(
-            url="https://example.com",
-            config=CrawlerRunConfig()
-        )
-        print(result.markdown[:500])
-
-asyncio.run(main())
-```
-
-## Combining Both Features
-
-For maximum evasion, combine stealth mode with undetected browser:
-
-```python
-from crawl4ai import AsyncWebCrawler, BrowserConfig, UndetectedAdapter
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-# Create browser config with stealth enabled
-browser_config = BrowserConfig(
-    enable_stealth=True,  # Enable stealth mode
-    headless=False
-)
-
-# Create undetected adapter
-adapter = UndetectedAdapter()
-
-# Create strategy with both features
-strategy = AsyncPlaywrightCrawlerStrategy(
-    browser_config=browser_config,
-    browser_adapter=adapter
-)
-
-async with AsyncWebCrawler(
-    crawler_strategy=strategy,
-    config=browser_config
-) as crawler:
-    result = await crawler.arun("https://protected-site.com")
-```
-
-## Examples
-
-### Example 1: Basic Stealth Mode
-
-```python
-import asyncio
-from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig
-
-async def test_stealth_mode():
-    # Simple stealth mode configuration
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=False
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(
-            url="https://bot.sannysoft.com",
-            config=CrawlerRunConfig(screenshot=True)
-        )
-        
-        if result.success:
-            print("✓ Successfully accessed bot detection test site")
-            # Save screenshot to verify detection results
-            if result.screenshot:
-                import base64
-                with open("stealth_test.png", "wb") as f:
-                    f.write(base64.b64decode(result.screenshot))
-                print("✓ Screenshot saved - check for green (passed) tests")
-
-asyncio.run(test_stealth_mode())
-```
-
-### Example 2: Undetected Browser Mode
-
-```python
-import asyncio
-from crawl4ai import (
-    AsyncWebCrawler,
-    BrowserConfig,
-    CrawlerRunConfig,
-    UndetectedAdapter
-)
-from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
-
-
-async def main():
-    # Create browser config
-    browser_config = BrowserConfig(
-        headless=False,
-        verbose=True,
-    )
-    
-    # Create the undetected adapter
-    undetected_adapter = UndetectedAdapter()
-    
-    # Create the crawler strategy with the undetected adapter
-    crawler_strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=undetected_adapter
-    )
-    
-    # Create the crawler with our custom strategy
-    async with AsyncWebCrawler(
-        crawler_strategy=crawler_strategy,
-        config=browser_config
-    ) as crawler:
-        # Configure the crawl
-        crawler_config = CrawlerRunConfig(
-            markdown_generator=DefaultMarkdownGenerator(
-                content_filter=PruningContentFilter()
-            ),
-            capture_console_messages=True,  # Test adapter console capture
-        )
-        
-        # Test on a site that typically detects bots
-        print("Testing undetected adapter...")
-        result: CrawlResult = await crawler.arun(
-            url="https://www.helloworld.org", 
-            config=crawler_config
-        )
-        
-        print(f"Status: {result.status_code}")
-        print(f"Success: {result.success}")
-        print(f"Console messages captured: {len(result.console_messages or [])}")
-        print(f"Markdown content (first 500 chars):\n{result.markdown.raw_markdown[:500]}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())
-```
-
-## Browser Adapter Pattern
-
-The undetected browser support is implemented using an adapter pattern, allowing seamless switching between different browser implementations:
-
-```python
-# Regular browser adapter (default)
-from crawl4ai import PlaywrightAdapter
-regular_adapter = PlaywrightAdapter()
-
-# Undetected browser adapter
-from crawl4ai import UndetectedAdapter
-undetected_adapter = UndetectedAdapter()
-```
-
-The adapter handles:
- JavaScript execution
- Console message capture
- Error handling
- Browser-specific optimizations
-
-## Best Practices
-
-1. **Avoid Headless Mode**: Detection is easier in headless mode
-   ```python
-   browser_config = BrowserConfig(headless=False)
-   ```
-
-2. **Use Reasonable Delays**: Don't rush through pages
-   ```python
-   crawler_config = CrawlerRunConfig(
-       wait_time=3.0,  # Wait 3 seconds after page load
-       delay_before_return_html=2.0  # Additional delay
-   )
-   ```
-
-3. **Rotate User Agents**: You can customize user agents
-   ```python
-   browser_config = BrowserConfig(
-       headers={"User-Agent": "your-user-agent"}
-   )
-   ```
-
-4. **Handle Failures Gracefully**: Some sites may still detect and block
-   ```python
-   if not result.success:
-       print(f"Crawl failed: {result.error_message}")
-   ```
-
-## Advanced Usage Tips
-
-### Progressive Detection Handling
-
-```python
-async def crawl_with_progressive_evasion(url):
-    # Step 1: Try regular browser with stealth
-    browser_config = BrowserConfig(
-        enable_stealth=True,
-        headless=False
-    )
-    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
-        result = await crawler.arun(url)
-        if result.success and "Access Denied" not in result.html:
-            return result
-    
-    # Step 2: If blocked, try undetected browser
-    print("Regular + stealth blocked, trying undetected browser...")
-    
-    adapter = UndetectedAdapter()
-    strategy = AsyncPlaywrightCrawlerStrategy(
-        browser_config=browser_config,
-        browser_adapter=adapter
-    )
-    
-    async with AsyncWebCrawler(
-        crawler_strategy=strategy,
-        config=browser_config
-    ) as crawler:
-        result = await crawler.arun(url)
-        return result
-```
-
-## Installation
-
-The undetected browser dependencies are automatically installed when you run:
-
-```bash
-crawl4ai-setup
-```
-
-This command installs all necessary browser dependencies for both regular and undetected modes.
-
-## Limitations
-
- **Performance**: Slightly slower than regular mode due to additional patches
- **Headless Detection**: Some sites can still detect headless mode
- **Resource Usage**: May use more resources than regular mode
- **Not 100% Guaranteed**: Advanced anti-bot services are constantly evolving
-
-## Troubleshooting
-
-### Browser Not Found
-
-Run the setup command:
-```bash
-crawl4ai-setup
-```
-
-### Detection Still Occurring
-
-Try combining with other features:
-```python
-crawler_config = CrawlerRunConfig(
-    simulate_user=True,  # Add user simulation
-    magic=True,  # Enable magic mode
-    wait_time=5.0,  # Longer waits
-)
-```
-
-### Performance Issues
-
-If experiencing slow performance:
-```python
-# Use selective undetected mode only for protected sites
-if is_protected_site(url):
-    adapter = UndetectedAdapter()
-else:
-    adapter = PlaywrightAdapter()  # Default adapter
-```
-
-## Future Plans
-
-**Note**: In future versions of Crawl4AI, we may enable stealth mode and undetected browser by default to provide better out-of-the-box success rates. For now, users should explicitly enable these features when needed.
-
-## Conclusion
-
-Crawl4AI provides flexible anti-bot solutions:
-
-1. **Start Simple**: Use regular browser + stealth mode for most sites
-2. **Escalate if Needed**: Switch to undetected browser for sophisticated protection
-3. **Combine for Maximum Effect**: Use both features together when facing the toughest challenges
-
-Remember:
- Always respect robots.txt and website terms of service
- Use appropriate delays to avoid overwhelming servers
- Consider the performance trade-offs of each approach
- Test progressively to find the minimum necessary evasion level
-
-## See Also
-
- [Advanced Features](advanced-features.md) - Overview of all advanced features
- [Proxy & Security](proxy-security.md) - Using proxies with anti-bot features
- [Session Management](session-management.md) - Maintaining sessions across requests
- [Identity Based Crawling](identity-based-crawling.md) - Additional anti-detection strategies
--- a/docs/md_v2/advanced/virtual-scroll.md
+++ b/docs/md_v2/advanced/virtual-scroll.md
@@ -91,12 +91,13 @@ async def crawl_twitter_timeline():
        wait_after_scroll=1.0  # Twitter needs time to load
    )
    
-    browser_config = BrowserConfig(headless=True)  # Set to False to watch it work
    config = CrawlerRunConfig(
-        virtual_scroll_config=virtual_config
+        virtual_scroll_config=virtual_config,
+        # Optional: Set headless=False to watch it work
+        # browser_config=BrowserConfig(headless=False)
    )
    
-    async with AsyncWebCrawler(config=browser_config) as crawler:
+    async with AsyncWebCrawler() as crawler:
        result = await crawler.arun(
            url="https://twitter.com/search?q=AI",
            config=config
@@ -199,7 +200,7 @@ Use **scan_full_page** when:
 Virtual Scroll works seamlessly with extraction strategies:

 ```python
-from crawl4ai import LLMExtractionStrategy, LLMConfig
+from crawl4ai import LLMExtractionStrategy

 # Define extraction schema
 schema = {
@@ -221,7 +222,7 @@ config = CrawlerRunConfig(
        scroll_count=20
    ),
    extraction_strategy=LLMExtractionStrategy(
-        llm_config=LLMConfig(provider="openai/gpt-4o-mini"),
+        provider="openai/gpt-4o-mini",
        schema=schema
    )
 )
--- a/docs/md_v2/api/arun_many.md
+++ b/docs/md_v2/api/arun_many.md
@@ -7,7 +7,7 @@
 ```python
 async def arun_many(
    urls: Union[List[str], List[Any]],
-    config: Optional[Union[CrawlerRunConfig, List[CrawlerRunConfig]]] = None,
+    config: Optional[CrawlerRunConfig] = None,
    dispatcher: Optional[BaseDispatcher] = None,
    ...
 ) -> Union[List[CrawlResult], AsyncGenerator[CrawlResult, None]]:
@@ -15,9 +15,7 @@ async def arun_many(
    Crawl multiple URLs concurrently or in batches.

    :param urls: A list of URLs (or tasks) to crawl.
-    :param config: (Optional) Either:
-        - A single `CrawlerRunConfig` applying to all URLs
-        - A list of `CrawlerRunConfig` objects with url_matcher patterns
+    :param config: (Optional) A default `CrawlerRunConfig` applying to each crawl.
    :param dispatcher: (Optional) A concurrency controller (e.g. MemoryAdaptiveDispatcher).
    ...
    :return: Either a list of `CrawlResult` objects, or an async generator if streaming is enabled.
@@ -97,70 +95,10 @@ results = await crawler.arun_many(
 )
 ```

-### URL-Specific Configurations
-
-Instead of using one config for all URLs, provide a list of configs with `url_matcher` patterns:
-
-```python
-from crawl4ai import CrawlerRunConfig, MatchMode
-from crawl4ai.processors.pdf import PDFContentScrapingStrategy
-from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
-from crawl4ai.content_filter_strategy import PruningContentFilter
-from crawl4ai.markdown_generation_strategy import DefaultMarkdownGenerator
-
-# PDF files - specialized extraction
-pdf_config = CrawlerRunConfig(
-    url_matcher="*.pdf",
-    scraping_strategy=PDFContentScrapingStrategy()
-)
-
-# Blog/article pages - content filtering
-blog_config = CrawlerRunConfig(
-    url_matcher=["*/blog/*", "*/article/*", "*python.org*"],
-    markdown_generator=DefaultMarkdownGenerator(
-        content_filter=PruningContentFilter(threshold=0.48)
-    )
-)
-
-# Dynamic pages - JavaScript execution
-github_config = CrawlerRunConfig(
-    url_matcher=lambda url: 'github.com' in url,
-    js_code="window.scrollTo(0, 500);"
-)
-
-# API endpoints - JSON extraction
-api_config = CrawlerRunConfig(
-    url_matcher=lambda url: 'api' in url or url.endswith('.json'),
-    # Custome settings for JSON extraction
-)
-
-# Default fallback config
-default_config = CrawlerRunConfig()  # No url_matcher means it never matches except as fallback
-
-# Pass the list of configs - first match wins!
-results = await crawler.arun_many(
-    urls=[
-        "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",  # → pdf_config
-        "https://blog.python.org/",  # → blog_config
-        "https://github.com/microsoft/playwright",  # → github_config
-        "https://httpbin.org/json",  # → api_config
-        "https://example.com/"  # → default_config
-    ],
-    config=[pdf_config, blog_config, github_config, api_config, default_config]
-)
-```
-
-**URL Matching Features**:
- **String patterns**: `"*.pdf"`, `"*/blog/*"`, `"*python.org*"`
- **Function matchers**: `lambda url: 'api' in url`
- **Mixed patterns**: Combine strings and functions with `MatchMode.OR` or `MatchMode.AND`
- **First match wins**: Configs are evaluated in order
-
 **Key Points**:
 - Each URL is processed by the same or separate sessions, depending on the dispatcher’s strategy.
 - `dispatch_result` in each `CrawlResult` (if using concurrency) can hold memory and timing info.  
 - If you need to handle authentication or session IDs, pass them in each individual task or within your run config.
- **Important**: Always include a default config (without `url_matcher`) as the last item if you want to handle all URLs. Otherwise, unmatched URLs will fail.

 ### Return Value

--- a/docs/md_v2/api/parameters.md
+++ b/docs/md_v2/api/parameters.md
@@ -208,71 +208,6 @@ config = CrawlerRunConfig(

 See [Virtual Scroll documentation](../../advanced/virtual-scroll.md) for detailed examples.

---
-
-### I) **URL Matching Configuration**
-
-| **Parameter**          | **Type / Default**           | **What It Does**                                                                                                                    |
-|------------------------|------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|
-| **`url_matcher`**      | `UrlMatcher` (None)          | Pattern(s) to match URLs against. Can be: string (glob), function, or list of mixed types. **None means match ALL URLs**         |
-| **`match_mode`**       | `MatchMode` (MatchMode.OR)   | How to combine multiple matchers in a list: `MatchMode.OR` (any match) or `MatchMode.AND` (all must match)                       |
-
-The `url_matcher` parameter enables URL-specific configurations when used with `arun_many()`:
-
-```python
-from crawl4ai import CrawlerRunConfig, MatchMode
-from crawl4ai.processors.pdf import PDFContentScrapingStrategy
-from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
-
-# Simple string pattern (glob-style)
-pdf_config = CrawlerRunConfig(
-    url_matcher="*.pdf",
-    scraping_strategy=PDFContentScrapingStrategy()
-)
-
-# Multiple patterns with OR logic (default)
-blog_config = CrawlerRunConfig(
-    url_matcher=["*/blog/*", "*/article/*", "*/news/*"],
-    match_mode=MatchMode.OR  # Any pattern matches
-)
-
-# Function matcher
-api_config = CrawlerRunConfig(
-    url_matcher=lambda url: 'api' in url or url.endswith('.json'),
-    # Other settings like extraction_strategy
-)
-
-# Mixed: String + Function with AND logic
-complex_config = CrawlerRunConfig(
-    url_matcher=[
-        lambda url: url.startswith('https://'),  # Must be HTTPS
-        "*.org/*",                               # Must be .org domain
-        lambda url: 'docs' in url                # Must contain 'docs'
-    ],
-    match_mode=MatchMode.AND  # ALL conditions must match
-)
-
-# Combined patterns and functions with AND logic
-secure_docs = CrawlerRunConfig(
-    url_matcher=["https://*", lambda url: '.doc' in url],
-    match_mode=MatchMode.AND  # Must be HTTPS AND contain .doc
-)
-
-# Default config - matches ALL URLs
-default_config = CrawlerRunConfig()  # No url_matcher = matches everything
-```
-
-**UrlMatcher Types:**
- **None (default)**: When `url_matcher` is None or not set, the config matches ALL URLs
- **String patterns**: Glob-style patterns like `"*.pdf"`, `"*/api/*"`, `"https://*.example.com/*"`
- **Functions**: `lambda url: bool` - Custom logic for complex matching
- **Lists**: Mix strings and functions, combined with `MatchMode.OR` or `MatchMode.AND`
-
-**Important Behavior:**
- When passing a list of configs to `arun_many()`, URLs are matched against each config's `url_matcher` in order. First match wins!
- If no config matches a URL and there's no default config (one without `url_matcher`), the URL will fail with "No matching configuration found"
- Always include a default config as the last item if you want to handle all URLs
-
 ---## 2.2 Helper Methods

 Both `BrowserConfig` and `CrawlerRunConfig` provide a `clone()` method to create modified copies:
--- a/docs/md_v2/blog/index.md
+++ b/docs/md_v2/blog/index.md
@@ -20,30 +20,24 @@ Ever wondered why your AI coding assistant struggles with your library despite c

 ## Latest Release

-### [Crawl4AI v0.7.3 – The Multi-Config Intelligence Update](releases/0.7.3.md)
-*August 6, 2025*
+### [Crawl4AI v0.7.0 – The Adaptive Intelligence Update](releases/0.7.0.md)
+*January 28, 2025*

-Crawl4AI v0.7.3 brings smarter URL-specific configurations, flexible Docker deployments, and critical stability improvements. Configure different crawling strategies for different URL patterns in a single batch—perfect for mixed content sites with docs, blogs, and APIs.
+Crawl4AI v0.7.0 introduces groundbreaking intelligence features that transform how crawlers understand and adapt to websites. This release brings Adaptive Crawling that learns website patterns, Virtual Scroll support for infinite pages, intelligent Link Preview with 3-layer scoring, and the powerful Async URL Seeder for massive URL discovery.

 Key highlights:
- **Multi-URL Configurations**: Different strategies for different URL patterns in one crawl
- **Flexible Docker LLM Providers**: Configure providers via environment variables  
- **Bug Fixes**: Critical stability improvements for production deployments
- **Documentation Updates**: Clearer examples and improved API documentation
+- **Adaptive Crawling**: Crawlers that learn and adapt to website structures automatically
+- **Virtual Scroll Support**: Complete content extraction from modern infinite scroll pages  
+- **Link Preview**: 3-layer scoring system for intelligent link prioritization
+- **Async URL Seeder**: Discover thousands of URLs in seconds with smart filtering
+- **Performance Boost**: Up to 3x faster with optimized resource handling

-[Read full release notes →](releases/0.7.3.md)
+[Read full release notes →](releases/0.7.0.md)

 ---

 ## Previous Releases

-### [Crawl4AI v0.7.0 – The Adaptive Intelligence Update](releases/0.7.0.md)
-*January 28, 2025*
-
-Introduced groundbreaking intelligence features including Adaptive Crawling, Virtual Scroll support, intelligent Link Preview, and the Async URL Seeder for massive URL discovery.
-
-[Read release notes →](releases/0.7.0.md)
-
 ### [Crawl4AI v0.6.0 – World-Aware Crawling, Pre-Warmed Browsers, and the MCP API](releases/0.6.0.md)
 *December 23, 2024*

--- a/docs/md_v2/blog/releases/0.7.0.md
+++ b/docs/md_v2/blog/releases/0.7.0.md
@@ -10,8 +10,9 @@ Today I'm releasing Crawl4AI v0.7.0—the Adaptive Intelligence Update. This rel

 - **Adaptive Crawling**: Your crawler now learns and adapts to website patterns
 - **Virtual Scroll Support**: Complete content extraction from infinite scroll pages
- **Link Preview with Intelligent Scoring**: Intelligent link analysis and prioritization
+- **Link Preview with 3-Layer Scoring**: Intelligent link analysis and prioritization
 - **Async URL Seeder**: Discover thousands of URLs in seconds with intelligent filtering
+- **PDF Parsing**: Extract data from PDF documents
 - **Performance Optimizations**: Significant speed and memory improvements

 ## 🧠 Adaptive Crawling: Intelligence Through Pattern Learning
@@ -29,41 +30,44 @@ The Adaptive Crawler maintains a persistent state for each domain, tracking:
 - Extraction confidence scores

 ```python
-from crawl4ai import AsyncWebCrawler, AdaptiveCrawler, AdaptiveConfig
-import asyncio
+from crawl4ai import AdaptiveCrawler, AdaptiveConfig, CrawlState

-async def main():
-    
-    # Configure adaptive crawler
-    config = AdaptiveConfig(
-        strategy="statistical",  # or "embedding" for semantic understanding
-        max_pages=10,
-        confidence_threshold=0.7,  # Stop at 70% confidence
-        top_k_links=3,  # Follow top 3 links per page
-        min_gain_threshold=0.05  # Need 5% information gain to continue
+# Initialize with custom learning parameters
+config = AdaptiveConfig(
+    confidence_threshold=0.7,    # Min confidence to use learned patterns
+    max_history=100,            # Remember last 100 crawls per domain
+    learning_rate=0.2,          # How quickly to adapt to changes
+    patterns_per_page=3,        # Patterns to learn per page type
+    extraction_strategy='css'   # 'css' or 'xpath'
+)
+
+adaptive_crawler = AdaptiveCrawler(config)
+
+# First crawl - crawler learns the structure
+async with AsyncWebCrawler() as crawler:
+    result = await crawler.arun(
+        "https://news.example.com/article/12345",
+        config=CrawlerRunConfig(
+            adaptive_config=config,
+            extraction_hints={  # Optional hints to speed up learning
+                "title": "article h1",
+                "content": "article .body-content"
+            }
+        )
    )
    
-    async with AsyncWebCrawler(verbose=False) as crawler:
-        adaptive = AdaptiveCrawler(crawler, config)
-        
-        print("Starting adaptive crawl about Python decorators...")
-        result = await adaptive.digest(
-            start_url="https://docs.python.org/3/glossary.html",
-            query="python decorators functions wrapping"
-        )
-        
-        print(f"\n✅ Crawling Complete!")
-        print(f"• Confidence Level: {adaptive.confidence:.0%}")
-        print(f"• Pages Crawled: {len(result.crawled_urls)}")
-        print(f"• Knowledge Base: {len(adaptive.state.knowledge_base)} documents")
-        
-        # Get most relevant content
-        relevant = adaptive.get_relevant_content(top_k=3)
-        print(f"\nMost Relevant Pages:")
-        for i, page in enumerate(relevant, 1):
-            print(f"{i}. {page['url']} (relevance: {page['score']:.2%})")
+    # Crawler identifies and stores patterns
+    if result.success:
+        state = adaptive_crawler.get_state("news.example.com")
+        print(f"Learned {len(state.patterns)} patterns")
+        print(f"Confidence: {state.avg_confidence:.2%}")

-asyncio.run(main())
+# Subsequent crawls - uses learned patterns
+result2 = await crawler.arun(
+    "https://news.example.com/article/67890",
+    config=CrawlerRunConfig(adaptive_config=config)
+)
+# Automatically extracts using learned patterns!
 ```

 **Expected Real-World Impact:**
@@ -88,7 +92,9 @@ twitter_config = VirtualScrollConfig(
    container_selector="[data-testid='primaryColumn']",
    scroll_count=20,                    # Number of scrolls
    scroll_by="container_height",       # Smart scrolling by container size
-    wait_after_scroll=1.0              # Let content load
+    wait_after_scroll=1.0,             # Let content load
+    capture_method="incremental",       # Capture new content on each scroll
+    deduplicate=True                   # Remove duplicate elements
 )

 # For e-commerce product grids (Instagram style)
@@ -96,7 +102,8 @@ grid_config = VirtualScrollConfig(
    container_selector="main .product-grid",
    scroll_count=30,
    scroll_by=800,                     # Fixed pixel scrolling
-    wait_after_scroll=1.5              # Images need time
+    wait_after_scroll=1.5,             # Images need time
+    stop_on_no_change=True            # Smart stopping
 )

 # For news feeds with lazy loading
@@ -104,7 +111,9 @@ news_config = VirtualScrollConfig(
    container_selector=".article-feed",
    scroll_count=50,
    scroll_by="page_height",           # Viewport-based scrolling
-    wait_after_scroll=0.5              # Wait for content to load
+    wait_after_scroll=0.5,
+    wait_for_selector=".article-card",  # Wait for specific elements
+    timeout=30000                      # Max 30 seconds total
 )

 # Use it in your crawl
@@ -148,63 +157,68 @@ async with AsyncWebCrawler() as crawler:

 **My Solution:** I implemented a three-layer scoring system that analyzes links like a human would—considering their position, context, and relevance to your goals.

-### Intelligent Link Analysis and Scoring
+### The Three-Layer Scoring System

 ```python
-import asyncio
-from crawl4ai import CrawlerRunConfig, CacheMode, AsyncWebCrawler
-from crawl4ai.adaptive_crawler import LinkPreviewConfig
+from crawl4ai import LinkPreviewConfig

-async def main():
-    # Configure intelligent link analysis
-    link_config = LinkPreviewConfig(
-        include_internal=True,
-        include_external=False,
-        max_links=10,
-        concurrency=5,
-        query="python tutorial",  # For contextual scoring
-        score_threshold=0.3,
-        verbose=True
+# Configure intelligent link analysis
+link_config = LinkPreviewConfig(
+    # What to analyze
+    include_internal=True,
+    include_external=True,
+    max_links=100,              # Analyze top 100 links
+    
+    # Relevance scoring
+    query="machine learning tutorials",  # Your interest
+    score_threshold=0.3,        # Minimum relevance score
+    
+    # Performance
+    concurrent_requests=10,     # Parallel processing
+    timeout_per_link=5000,      # 5s per link
+    
+    # Advanced scoring weights
+    scoring_weights={
+        "intrinsic": 0.3,       # Link quality indicators
+        "contextual": 0.5,      # Relevance to query
+        "popularity": 0.2       # Link prominence
+    }
+)
+
+# Use in your crawl
+result = await crawler.arun(
+    "https://tech-blog.example.com",
+    config=CrawlerRunConfig(
+        link_preview_config=link_config,
+        score_links=True
    )
-    # Use in your crawl
-    async with AsyncWebCrawler() as crawler:
-        result = await crawler.arun(
-            "https://www.geeksforgeeks.org/",
-            config=CrawlerRunConfig(
-                link_preview_config=link_config,
-                score_links=True,  # Enable intrinsic scoring
-                cache_mode=CacheMode.BYPASS
-            )
-        )
+)

-        # Access scored and sorted links
-        if result.success and result.links:
-            for link in result.links.get("internal", []):
-                text = link.get('text', 'No text')[:40]
-                print(
-                    text,
-                    f"{link.get('intrinsic_score', 0):.1f}/10" if link.get('intrinsic_score') is not None else "0.0/10",
-                    f"{link.get('contextual_score', 0):.2f}/1" if link.get('contextual_score') is not None else "0.00/1",
-                    f"{link.get('total_score', 0):.3f}" if link.get('total_score') is not None else "0.000"
-                )
-
-asyncio.run(main())
+# Access scored and sorted links
+for link in result.links["internal"][:10]:  # Top 10 internal links
+    print(f"Score: {link['total_score']:.3f}")
+    print(f"  Intrinsic: {link['intrinsic_score']:.1f}/10")  # Position, attributes
+    print(f"  Contextual: {link['contextual_score']:.1f}/1")  # Relevance to query
+    print(f"  URL: {link['href']}")
+    print(f"  Title: {link['head_data']['title']}")
+    print(f"  Description: {link['head_data']['meta']['description'][:100]}...")
 ```

 **Scoring Components:**

-1. **Intrinsic Score**: Based on link quality indicators
+1. **Intrinsic Score (0-10)**: Based on link quality indicators
   - Position on page (navigation, content, footer)
   - Link attributes (rel, title, class names)
   - Anchor text quality and length
   - URL structure and depth

-2. **Contextual Score**: Relevance to your query using BM25 algorithm
+2. **Contextual Score (0-1)**: Relevance to your query
+   - Semantic similarity using embeddings
   - Keyword matching in link text and title
   - Meta description analysis
   - Content preview scoring

-3. **Total Score**: Combined score for final ranking
+3. **Total Score**: Weighted combination for final ranking

 **Expected Real-World Impact:**
 - **Research Efficiency**: Find relevant papers 10x faster by following only high-score links
@@ -221,34 +235,58 @@ asyncio.run(main())
 ### Technical Architecture

 ```python
-import asyncio
 from crawl4ai import AsyncUrlSeeder, SeedingConfig

-async def main():
-    async with AsyncUrlSeeder() as seeder:
-        # Discover Python tutorial URLs
-        config = SeedingConfig(
-            source="sitemap",  # Use sitemap
-            pattern="*python*",  # URL pattern filter
-            extract_head=True,  # Get metadata
-            query="python tutorial",  # For relevance scoring
-            scoring_method="bm25",
-            score_threshold=0.2,
-            max_urls=10
-        )
-        
-        print("Discovering Python async tutorial URLs...")
-        urls = await seeder.urls("https://www.geeksforgeeks.org/", config)
-        
-        print(f"\n✅ Found {len(urls)} relevant URLs:")
-        for i, url_info in enumerate(urls[:5], 1):
-            print(f"\n{i}. {url_info['url']}")
-            if url_info.get('relevance_score'):
-                print(f"   Relevance: {url_info['relevance_score']:.3f}")
-            if url_info.get('head_data', {}).get('title'):
-                print(f"   Title: {url_info['head_data']['title'][:60]}...")
+# Basic discovery - find all product pages
+seeder_config = SeedingConfig(
+    # Discovery sources
+    source="sitemap+cc",        # Sitemap + Common Crawl
+    
+    # Filtering
+    pattern="*/product/*",      # URL pattern matching
+    ignore_patterns=["*/reviews/*", "*/questions/*"],
+    
+    # Validation
+    live_check=True,           # Verify URLs are alive
+    max_urls=5000,             # Stop at 5000 URLs
+    
+    # Performance  
+    concurrency=100,           # Parallel requests
+    hits_per_sec=10           # Rate limiting
+)

-asyncio.run(main())
+seeder = AsyncUrlSeeder(seeder_config)
+urls = await seeder.discover("https://shop.example.com")
+
+# Advanced: Relevance-based discovery
+research_config = SeedingConfig(
+    source="crawl+sitemap",    # Deep crawl + sitemap
+    pattern="*/blog/*",        # Blog posts only
+    
+    # Content relevance
+    extract_head=True,         # Get meta tags
+    query="quantum computing tutorials",
+    scoring_method="bm25",     # Or "semantic" (coming soon)
+    score_threshold=0.4,       # High relevance only
+    
+    # Smart filtering
+    filter_nonsense_urls=True,  # Remove .xml, .txt, etc.
+    min_content_length=500,     # Skip thin content
+    
+    force=True                 # Bypass cache
+)
+
+# Discover with progress tracking
+discovered = []
+async for batch in seeder.discover_iter("https://physics-blog.com", research_config):
+    discovered.extend(batch)
+    print(f"Found {len(discovered)} relevant URLs so far...")
+
+# Results include scores and metadata
+for url_data in discovered[:5]:
+    print(f"URL: {url_data['url']}")
+    print(f"Score: {url_data['score']:.3f}")
+    print(f"Title: {url_data['title']}")
 ```

 **Discovery Methods:**
@@ -271,18 +309,35 @@ This release includes significant performance improvements through optimized res
 ### What We Optimized

 ```python
-# Optimized crawling with v0.7.0 improvements
+# Before v0.7.0 (slow)
 results = []
 for url in urls:
-    result = await crawler.arun(
-        url,
-        config=CrawlerRunConfig(
-            # Performance optimizations
-            wait_until="domcontentloaded",  # Faster than networkidle
-            cache_mode=CacheMode.ENABLED    # Enable caching
-        )
-    )
+    result = await crawler.arun(url)
    results.append(result)
+
+# After v0.7.0 (fast)
+# Automatic batching and connection pooling
+results = await crawler.arun_batch(
+    urls,
+    config=CrawlerRunConfig(
+        # New performance options
+        batch_size=10,              # Process 10 URLs concurrently
+        reuse_browser=True,         # Keep browser warm
+        eager_loading=False,        # Load only what's needed
+        streaming_extraction=True,  # Stream large extractions
+        
+        # Optimized defaults
+        wait_until="domcontentloaded",  # Faster than networkidle
+        exclude_external_resources=True, # Skip third-party assets
+        block_ads=True                  # Ad blocking built-in
+    )
+)
+
+# Memory-efficient streaming for large crawls
+async for result in crawler.arun_stream(large_url_list):
+    # Process results as they complete
+    await process_result(result)
+    # Memory is freed after each iteration
 ```

 **Performance Gains:**
@@ -292,6 +347,24 @@ for url in urls:
 - **Memory Usage**: 60% reduction with streaming processing
 - **Concurrent Crawls**: Handle 5x more parallel requests

+## 📄 PDF Support
+
+PDF extraction is now natively supported in Crawl4AI.
+
+```python
+# Extract data from PDF documents
+result = await crawler.arun(
+    "https://example.com/report.pdf",
+    config=CrawlerRunConfig(
+        pdf_extraction=True,
+        extraction_strategy=JsonCssExtractionStrategy({
+            # Works on converted PDF structure
+            "title": {"selector": "h1", "type": "text"},
+            "sections": {"selector": "h2", "type": "list"}
+        })
+    )
+)
+```

 ## 🔧 Important Changes

--- a/docs/md_v2/blog/releases/0.7.1.md
+++ b/docs/md_v2/blog/releases/0.7.1.md
@@ -1,43 +0,0 @@
-# 🛠️ Crawl4AI v0.7.1: Minor Cleanup Update
-
-*July 17, 2025 • 2 min read*
-
---
-
-A small maintenance release that removes unused code and improves documentation.
-
-## 🎯 What's Changed
-
- **Removed unused StealthConfig** from `crawl4ai/browser_manager.py`
- **Updated documentation** with better examples and parameter explanations
- **Fixed virtual scroll configuration** examples in docs
-
-## 🧹 Code Cleanup
-
-Removed unused `StealthConfig` import and configuration that wasn't being used anywhere in the codebase. The project uses its own custom stealth implementation through JavaScript injection instead.
-
-```python
-# Removed unused code:
-from playwright_stealth import StealthConfig
-stealth_config = StealthConfig(...)  # This was never used
-```
-
-## 📖 Documentation Updates
-
- Fixed adaptive crawling parameter examples
- Updated session management documentation
- Corrected virtual scroll configuration examples
-
-## 🚀 Installation
-
-```bash
-pip install crawl4ai==0.7.1
-```
-
-No breaking changes - upgrade directly from v0.7.0.
-
---
-
-Questions? Issues? 
- GitHub: [github.com/unclecode/crawl4ai](https://github.com/unclecode/crawl4ai)
- Discord: [discord.gg/crawl4ai](https://discord.gg/jP8KfhDhyN)
--- a/docs/md_v2/blog/releases/0.7.2.md
+++ b/docs/md_v2/blog/releases/0.7.2.md
@@ -1,98 +0,0 @@
-# 🚀 Crawl4AI v0.7.2: CI/CD & Dependency Optimization Update
-
-*July 25, 2025 • 3 min read*
-
---
-
-This release introduces automated CI/CD pipelines for seamless releases and optimizes dependencies for a lighter, more efficient package.
-
-## 🎯 What's New
-
-### 🔄 Automated Release Pipeline
- **GitHub Actions CI/CD**: Automated PyPI and Docker Hub releases on tag push
- **Multi-platform Docker images**: Support for both AMD64 and ARM64 architectures
- **Version consistency checks**: Ensures tag, package, and Docker versions align
- **Automated release notes**: GitHub releases created automatically
-
-### 📦 Dependency Optimization
- **Moved sentence-transformers to optional dependencies**: Significantly reduces default installation size
- **Lighter Docker images**: Optimized Dockerfile for faster builds and smaller images
- **Better dependency management**: Core vs. optional dependencies clearly separated
-
-## 🏗️ CI/CD Pipeline
-
-The new automated release process ensures consistent, reliable releases:
-
-```yaml
-# Trigger releases with a simple tag
-git tag v0.7.2
-git push origin v0.7.2
-
-# Automatically:
-# ✅ Validates version consistency
-# ✅ Builds and publishes to PyPI
-# ✅ Builds multi-platform Docker images
-# ✅ Pushes to Docker Hub with proper tags
-# ✅ Creates GitHub release
-```
-
-## 💾 Lighter Installation
-
-Default installation is now significantly smaller:
-
-```bash
-# Core installation (smaller, faster)
-pip install crawl4ai==0.7.2
-
-# With ML features (includes sentence-transformers)
-pip install crawl4ai[transformer]==0.7.2
-
-# Full installation
-pip install crawl4ai[all]==0.7.2
-```
-
-## 🐳 Docker Improvements
-
-Enhanced Docker support with multi-platform images:
-
-```bash
-# Pull the latest version
-docker pull unclecode/crawl4ai:0.7.2
-docker pull unclecode/crawl4ai:latest
-
-# Available tags:
-# - unclecode/crawl4ai:0.7.2 (specific version)
-# - unclecode/crawl4ai:0.7 (minor version)
-# - unclecode/crawl4ai:0 (major version)
-# - unclecode/crawl4ai:latest
-```
-
-## 🔧 Technical Details
-
-### Dependency Changes
- `sentence-transformers` moved from required to optional dependencies
- Reduces default installation by ~500MB
- No impact on functionality when transformer features aren't needed
-
-### CI/CD Configuration
- GitHub Actions workflows for automated releases
- Version validation before publishing
- Parallel PyPI and Docker Hub deployments
- Automatic tagging strategy for Docker images
-
-## 🚀 Installation
-
-```bash
-pip install crawl4ai==0.7.2
-```
-
-No breaking changes - direct upgrade from v0.7.0 or v0.7.1.
-
---
-
-Questions? Issues? 
- GitHub: [github.com/unclecode/crawl4ai](https://github.com/unclecode/crawl4ai)
- Discord: [discord.gg/crawl4ai](https://discord.gg/jP8KfhDhyN)
- Twitter: [@unclecode](https://x.com/unclecode)
-
-*P.S. The new CI/CD pipeline will make future releases faster and more reliable. Thanks for your patience as we improve our release process!*
--- a/docs/md_v2/blog/releases/0.7.3.md
+++ b/docs/md_v2/blog/releases/0.7.3.md
@@ -1,170 +0,0 @@
-# 🚀 Crawl4AI v0.7.3: The Multi-Config Intelligence Update
-
-*August 6, 2025 • 5 min read*
-
---
-
-Today I'm releasing Crawl4AI v0.7.3—the Multi-Config Intelligence Update. This release brings smarter URL-specific configurations, flexible Docker deployments, important bug fixes, and documentation improvements that make Crawl4AI more robust and production-ready.
-
-## 🎯 What's New at a Glance
-
- **Multi-URL Configurations**: Different crawling strategies for different URL patterns in a single batch
- **Flexible Docker LLM Providers**: Configure LLM providers via environment variables
- **Bug Fixes**: Resolved several critical issues for better stability
- **Documentation Updates**: Clearer examples and improved API documentation
-
-## 🎨 Multi-URL Configurations: One Size Doesn't Fit All
-
-**The Problem:** You're crawling a mix of documentation sites, blogs, and API endpoints. Each needs different handling—caching for docs, fresh content for news, structured extraction for APIs. Previously, you'd run separate crawls or write complex conditional logic.
-
-**My Solution:** I implemented URL-specific configurations that let you define different strategies for different URL patterns in a single crawl batch. First match wins, with optional fallback support.
-
-### Technical Implementation
-
-```python
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, MatchMode
-
-# Define specialized configs for different content types
-configs = [
-    # Documentation sites - aggressive caching, include links
-    CrawlerRunConfig(
-        url_matcher=["*docs*", "*documentation*"],
-        cache_mode="write",
-        markdown_generator_options={"include_links": True}
-    ),
-    
-    # News/blog sites - fresh content, scroll for lazy loading
-    CrawlerRunConfig(
-        url_matcher=lambda url: 'blog' in url or 'news' in url,
-        cache_mode="bypass",
-        js_code="window.scrollTo(0, document.body.scrollHeight/2);"
-    ),
-    
-    # API endpoints - structured extraction
-    CrawlerRunConfig(
-        url_matcher=["*.json", "*api*"],
-        extraction_strategy=LLMExtractionStrategy(
-            provider="openai/gpt-4o-mini",
-            extraction_type="structured"
-        )
-    ),
-    
-    # Default fallback for everything else
-    CrawlerRunConfig()  # No url_matcher = matches everything
-]
-
-# Crawl multiple URLs with appropriate configs
-async with AsyncWebCrawler() as crawler:
-    results = await crawler.arun_many(
-        urls=[
-            "https://docs.python.org/3/",      # → Uses documentation config
-            "https://blog.python.org/",        # → Uses blog config  
-            "https://api.github.com/users",    # → Uses API config
-            "https://example.com/"             # → Uses default config
-        ],
-        config=configs
-    )
-```
-
-**Matching Capabilities:**
- **String Patterns**: Wildcards like `"*.pdf"`, `"*/blog/*"`
- **Function Matchers**: Lambda functions for complex logic
- **Mixed Matchers**: Combine strings and functions with AND/OR logic
- **Fallback Support**: Default config when nothing matches
-
-**Expected Real-World Impact:**
- **Mixed Content Sites**: Handle blogs, docs, and downloads in one crawl
- **Multi-Domain Crawling**: Different strategies per domain without separate runs
- **Reduced Complexity**: No more if/else forests in your extraction code
- **Better Performance**: Each URL gets exactly the processing it needs
-
-## 🐳 Docker: Flexible LLM Provider Configuration
-
-**The Problem:** Hardcoded LLM providers in Docker deployments. Want to switch from OpenAI to Groq? Rebuild and redeploy. Testing different models? Multiple Docker images.
-
-**My Solution:** Configure LLM providers via environment variables. Switch providers without touching code or rebuilding images.
-
-### Deployment Flexibility
-
-```bash
-# Option 1: Direct environment variables
-docker run -d \
-  -e LLM_PROVIDER="groq/llama-3.2-3b-preview" \
-  -e GROQ_API_KEY="your-key" \
-  -p 11235:11235 \
-  unclecode/crawl4ai:latest
-
-# Option 2: Using .llm.env file (recommended for production)
-# Create .llm.env file:
-# LLM_PROVIDER=openai/gpt-4o-mini
-# OPENAI_API_KEY=your-openai-key
-# GROQ_API_KEY=your-groq-key
-
-docker run -d \
-  --env-file .llm.env \
-  -p 11235:11235 \
-  unclecode/crawl4ai:latest
-```
-
-Override per request when needed:
-```python
-# Use default provider from .llm.env
-response = requests.post("http://localhost:11235/crawl", json={
-    "url": "https://example.com",
-    "extraction_strategy": {"type": "llm"}
-})
-
-# Override to use different provider for this specific request
-response = requests.post("http://localhost:11235/crawl", json={
-    "url": "https://complex-page.com",
-    "extraction_strategy": {
-        "type": "llm",
-        "provider": "openai/gpt-4"  # Override default
-    }
-})
-```
-
-**Expected Real-World Impact:**
- **Cost Optimization**: Use cheaper models for simple tasks, premium for complex
- **A/B Testing**: Compare provider performance without deployment changes
- **Fallback Strategies**: Switch providers on-the-fly during outages
- **Development Flexibility**: Test locally with one provider, deploy with another
- **Secure Configuration**: Keep API keys in `.llm.env` file, not in commands
-
-## 🔧 Bug Fixes & Improvements
-
-This release includes several important bug fixes that improve stability and reliability:
-
- **URL Matcher Fallback**: Fixed edge cases in URL pattern matching logic
- **Memory Management**: Resolved memory leaks in long-running crawl sessions
- **Sitemap Processing**: Fixed redirect handling in sitemap fetching
- **Table Extraction**: Improved table detection and extraction accuracy
- **Error Handling**: Better error messages and recovery from network failures
-
-## 📚 Documentation Enhancements
-
-Based on community feedback, we've updated:
- Clearer examples for multi-URL configuration
- Improved CrawlResult documentation with all available fields
- Fixed typos and inconsistencies across documentation
- Added real-world URLs in examples for better understanding
- New comprehensive demo showcasing all v0.7.3 features
-
-## 🙏 Acknowledgments
-
-Thanks to our contributors and the entire community for feedback and bug reports.
-
-## 📚 Resources
-
- [Full Documentation](https://docs.crawl4ai.com)
- [GitHub Repository](https://github.com/unclecode/crawl4ai)
- [Discord Community](https://discord.gg/crawl4ai)
- [Feature Demo](https://github.com/unclecode/crawl4ai/blob/main/docs/releases_review/demo_v0.7.3.py)
-
---
-
-*Crawl4AI continues to evolve with your needs. This release makes it smarter, more flexible, and more stable. Try the new multi-config feature and flexible Docker deployment—they're game changers!*
-
-**Happy Crawling! 🕷️**
-
-*- The Crawl4AI Team*
--- a/docs/md_v2/core/adaptive-crawling.md
+++ b/docs/md_v2/core/adaptive-crawling.md
@@ -35,7 +35,7 @@ from crawl4ai import AsyncWebCrawler, AdaptiveCrawler

 async def main():
    async with AsyncWebCrawler() as crawler:
-        # Create an adaptive crawler (config is optional)
+        # Create an adaptive crawler
        adaptive = AdaptiveCrawler(crawler)
        
        # Start crawling with a query
@@ -59,13 +59,13 @@ async def main():
 from crawl4ai import AdaptiveConfig

 config = AdaptiveConfig(
-    confidence_threshold=0.8,    # Stop when 80% confident (default: 0.7)
-    max_pages=30,               # Maximum pages to crawl (default: 20)
-    top_k_links=5,              # Links to follow per page (default: 3)
+    confidence_threshold=0.7,    # Stop when 70% confident (default: 0.8)
+    max_pages=20,               # Maximum pages to crawl (default: 50)
+    top_k_links=3,              # Links to follow per page (default: 5)
    min_gain_threshold=0.05     # Minimum expected gain to continue (default: 0.1)
 )

-adaptive = AdaptiveCrawler(crawler, config)
+adaptive = AdaptiveCrawler(crawler, config=config)
 ```

 ## Crawling Strategies
@@ -198,8 +198,8 @@ if result.metrics.get('is_irrelevant', False):
 The confidence score (0-1) indicates how sufficient the gathered information is:
 - **0.0-0.3**: Insufficient information, needs more crawling
 - **0.3-0.6**: Partial information, may answer basic queries
- **0.6-0.7**: Good coverage, can answer most queries
- **0.7-1.0**: Excellent coverage, comprehensive information
+- **0.6-0.8**: Good coverage, can answer most queries
+- **0.8-1.0**: Excellent coverage, comprehensive information

 ### Statistics Display

@@ -257,9 +257,9 @@ new_adaptive.import_knowledge_base("knowledge_base.jsonl")
 - Avoid overly broad queries

 ### 2. Threshold Tuning
- Start with default (0.7) for general use
- Lower to 0.5-0.6 for exploratory crawling
- Raise to 0.8+ for exhaustive coverage
+- Start with default (0.8) for general use
+- Lower to 0.6-0.7 for exploratory crawling
+- Raise to 0.9+ for exhaustive coverage

 ### 3. Performance Optimization
 - Use appropriate `max_pages` limits
--- a/docs/md_v2/core/browser-crawler-config.md
+++ b/docs/md_v2/core/browser-crawler-config.md
@@ -29,7 +29,6 @@ class BrowserConfig:
        text_mode=False,
        light_mode=False,
        extra_args=None,
-        enable_stealth=False,
        # ... other advanced parameters omitted here
    ):
        ...
@@ -85,11 +84,6 @@ class BrowserConfig:
    - Additional flags for the underlying browser.  
    - E.g. `["--disable-extensions"]`.

-11. **`enable_stealth`**:  
-    - If `True`, enables stealth mode using playwright-stealth.  
-    - Modifies browser fingerprints to avoid basic bot detection.  
-    - Default is `False`. Recommended for sites with bot protection.
-
 ### Helper Methods

 Both configuration classes provide a `clone()` method to create modified copies:
@@ -215,13 +209,7 @@ class CrawlerRunConfig:
    - The maximum number of concurrent crawl sessions.  
    - Helps prevent overwhelming the system.

-14. **`url_matcher`** & **`match_mode`**:  
-    - Enable URL-specific configurations when used with `arun_many()`.
-    - Set `url_matcher` to patterns (glob, function, or list) to match specific URLs.
-    - Use `match_mode` (OR/AND) to control how multiple patterns combine.
-    - See [URL-Specific Configurations](../api/arun_many.md#url-specific-configurations) for examples.
-
-15. **`display_mode`**:  
+14. **`display_mode`**:  
    - The display mode for progress information (`DETAILED`, `BRIEF`, etc.).  
    - Affects how much information is printed during the crawl.

--- a/docs/md_v2/core/c4a-script.md
+++ b/docs/md_v2/core/c4a-script.md
@@ -52,9 +52,11 @@ That's it! In just a few lines, you've automated a complete search workflow.

 Want to learn by doing? We've got you covered:

-**🚀 [Live Demo](https://docs.crawl4ai.com/apps/c4a-script/)** - Try C4A-Script in your browser right now!
+**🚀 [Live Demo](https://docs.crawl4ai.com/c4a-script/demo)** - Try C4A-Script in your browser right now!

-**📁 [Tutorial Examples](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/c4a_script/)** - Complete examples with source code
+**📁 [Tutorial Examples](/examples/c4a_script/)** - Complete examples with source code
+
+**🛠️ [Local Tutorial](/examples/c4a_script/tutorial/)** - Run the interactive tutorial on your machine

 ### Running the Tutorial Locally

--- a/docs/md_v2/core/content-selection.md
+++ b/docs/md_v2/core/content-selection.md
@@ -350,22 +350,15 @@ if __name__ == "__main__":

 ## 6. Scraping Modes

-Crawl4AI uses `LXMLWebScrapingStrategy` (LXML-based) as the default scraping strategy for HTML content processing. This strategy offers excellent performance, especially for large HTML documents.
-
-**Note:** For backward compatibility, `WebScrapingStrategy` is still available as an alias for `LXMLWebScrapingStrategy`.
+Crawl4AI provides two different scraping strategies for HTML content processing: `WebScrapingStrategy` (BeautifulSoup-based, default) and `LXMLWebScrapingStrategy` (LXML-based). The LXML strategy offers significantly better performance, especially for large HTML documents.

 ```python
 from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, LXMLWebScrapingStrategy

 async def main():
-    # Default configuration already uses LXMLWebScrapingStrategy
-    config = CrawlerRunConfig()
-    
-    # Or explicitly specify it if desired
-    config_explicit = CrawlerRunConfig(
-        scraping_strategy=LXMLWebScrapingStrategy()
+    config = CrawlerRunConfig(
+        scraping_strategy=LXMLWebScrapingStrategy()  # Faster alternative to default BeautifulSoup
    )
-    
    async with AsyncWebCrawler() as crawler:
        result = await crawler.arun(
            url="https://example.com", 
@@ -424,20 +417,21 @@ class CustomScrapingStrategy(ContentScrapingStrategy):

 ### Performance Considerations

-The LXML strategy provides excellent performance, particularly when processing large HTML documents, offering up to 10-20x faster processing compared to BeautifulSoup-based approaches.
+The LXML strategy can be up to 10-20x faster than BeautifulSoup strategy, particularly when processing large HTML documents. However, please note:

-Benefits of LXML strategy:
- Fast processing of large HTML documents (especially >100KB)
- Efficient memory usage
- Good handling of well-formed HTML
- Robust table detection and extraction
+1. LXML strategy is currently experimental
+2. In some edge cases, the parsing results might differ slightly from BeautifulSoup
+3. If you encounter any inconsistencies between LXML and BeautifulSoup results, please [raise an issue](https://github.com/codeium/crawl4ai/issues) with a reproducible example

-### Backward Compatibility
+Choose LXML strategy when:
+- Processing large HTML documents (recommended for >100KB)
+- Performance is critical
+- Working with well-formed HTML

-For users upgrading from earlier versions:
- `WebScrapingStrategy` is now an alias for `LXMLWebScrapingStrategy`
- Existing code using `WebScrapingStrategy` will continue to work without modification
- No changes are required to your existing code
+Stick to BeautifulSoup strategy (default) when:
+- Maximum compatibility is needed
+- Working with malformed HTML
+- Exact parsing behavior is critical

 ---

--- a/docs/md_v2/core/crawler-result.md
+++ b/docs/md_v2/core/crawler-result.md
@@ -19,15 +19,13 @@ class MarkdownGenerationResult(BaseModel):
 class CrawlResult(BaseModel):
    url: str
    html: str
-    fit_html: Optional[str] = None
    success: bool
    cleaned_html: Optional[str] = None
    media: Dict[str, List[Dict]] = {}
    links: Dict[str, List[Dict]] = {}
    downloaded_files: Optional[List[str]] = None
-    js_execution_result: Optional[Dict[str, Any]] = None
    screenshot: Optional[str] = None
-    pdf: Optional[bytes] = None
+    pdf : Optional[bytes] = None
    mhtml: Optional[str] = None
    markdown: Optional[Union[str, MarkdownGenerationResult]] = None
    extracted_content: Optional[str] = None
@@ -37,12 +35,6 @@ class CrawlResult(BaseModel):
    response_headers: Optional[dict] = None
    status_code: Optional[int] = None
    ssl_certificate: Optional[SSLCertificate] = None
-    dispatch_result: Optional[DispatchResult] = None
-    redirected_url: Optional[str] = None
-    network_requests: Optional[List[Dict[str, Any]]] = None
-    console_messages: Optional[List[Dict[str, Any]]] = None
-    tables: List[Dict] = Field(default_factory=list)
-
    class Config:
        arbitrary_types_allowed = True
 ```
@@ -53,13 +45,11 @@ class CrawlResult(BaseModel):
 |-------------------------------------------|-----------------------------------------------------------------------------------------------------|
 | **url (`str`)**                           | The final or actual URL crawled (in case of redirects).                                             |
 | **html (`str`)**                          | Original, unmodified page HTML. Good for debugging or custom processing.                            |
-| **fit_html (`Optional[str]`)**            | Preprocessed HTML optimized for extraction and content filtering.                                    |
 | **success (`bool`)**                      | `True` if the crawl completed without major errors, else `False`.                                   |
 | **cleaned_html (`Optional[str]`)**        | Sanitized HTML with scripts/styles removed; can exclude tags if configured via `excluded_tags` etc. |
 | **media (`Dict[str, List[Dict]]`)**       | Extracted media info (images, audio, etc.), each with attributes like `src`, `alt`, `score`, etc.   |
 | **links (`Dict[str, List[Dict]]`)**       | Extracted link data, split by `internal` and `external`. Each link usually has `href`, `text`, etc. |
 | **downloaded_files (`Optional[List[str]]`)** | If `accept_downloads=True` in `BrowserConfig`, this lists the filepaths of saved downloads.         |
-| **js_execution_result (`Optional[Dict[str, Any]]`)** | Results from JavaScript execution during crawling. |
 | **screenshot (`Optional[str]`)**          | Screenshot of the page (base64-encoded) if `screenshot=True`.                                       |
 | **pdf (`Optional[bytes]`)**               | PDF of the page if `pdf=True`.                                                                      |
 | **mhtml (`Optional[str]`)**               | MHTML snapshot of the page if `capture_mhtml=True`. Contains the full page with all resources.      |
@@ -71,11 +61,6 @@ class CrawlResult(BaseModel):
 | **response_headers (`Optional[dict]`)**   | HTTP response headers, if captured.                                                                 |
 | **status_code (`Optional[int]`)**         | HTTP status code (e.g., 200 for OK).                                                                |
 | **ssl_certificate (`Optional[SSLCertificate]`)** | SSL certificate info if `fetch_ssl_certificate=True`.                                               |
-| **dispatch_result (`Optional[DispatchResult]`)** | Additional concurrency and resource usage information when crawling URLs in parallel.               |
-| **redirected_url (`Optional[str]`)**      | The URL after any redirects (different from `url` which is the final URL).                          |
-| **network_requests (`Optional[List[Dict[str, Any]]]`)** | List of network requests, responses, and failures captured during the crawl if `capture_network_requests=True`. |
-| **console_messages (`Optional[List[Dict[str, Any]]]`)** | List of browser console messages captured during the crawl if `capture_console_messages=True`.       |
-| **tables (`List[Dict]`)**                 | Table data extracted from HTML tables with structure `[{headers, rows, caption, summary}]`.           |

 ---

@@ -187,7 +172,7 @@ Here:

 ---

-## 5. More Fields: Links, Media, Tables and More
+## 5. More Fields: Links, Media, and More

 ### 5.1 `links`

@@ -207,77 +192,7 @@ for img in images:
    print("Image URL:", img["src"], "Alt:", img.get("alt"))
 ```

-### 5.3 `tables`
-
-The `tables` field contains structured data extracted from HTML tables found on the crawled page. Tables are analyzed based on various criteria to determine if they are actual data tables (as opposed to layout tables), including:
-
- Presence of thead and tbody sections
- Use of th elements for headers
- Column consistency
- Text density
- And other factors
-
-Tables that score above the threshold (default: 7) are extracted and stored in result.tables.
-
-### Accessing Table data:
-```python
-import asyncio
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
-
-async def main():
-    async with AsyncWebCrawler() as crawler:
-        result = await crawler.arun(
-            url="https://www.w3schools.com/html/html_tables.asp",
-            config=CrawlerRunConfig(
-                table_score_threshold=7  # Minimum score for table detection
-            )
-        )
-
-        if result.success and result.tables:
-            print(f"Found {len(result.tables)} tables")
-
-            for i, table in enumerate(result.tables):
-                print(f"\nTable {i+1}:")
-                print(f"Caption: {table.get('caption', 'No caption')}")
-                print(f"Headers: {table['headers']}")
-                print(f"Rows: {len(table['rows'])}")
-
-                # Print first few rows as example
-                for j, row in enumerate(table['rows'][:3]):
-                    print(f"  Row {j+1}: {row}")
-
-if __name__ == "__main__":
-    asyncio.run(main())
-
-```
-
-### Configuring Table Extraction:
-
-You can adjust the sensitivity of the table detection algorithm with:
-
-```python
-config = CrawlerRunConfig(
-    table_score_threshold=5  # Lower value = more tables detected (default: 7)
-)
-```
-
-Each extracted table contains: 
-
- `headers`: Column header names 
- `rows`: List of rows, each containing cell values
- `caption`: Table caption text (if available) 
- `summary`: Table summary attribute (if specified)
-
-### Table Extraction Tips
-
- Not all HTML tables are extracted - only those detected as "data tables" vs. layout tables.
- Tables with inconsistent cell counts, nested tables, or those used purely for layout may be skipped.
- If you're missing tables, try adjusting the `table_score_threshold` to a lower value (default is 7).
-
-The table detection algorithm scores tables based on features like consistent columns, presence of headers, text density, and more. Tables scoring above the threshold are considered data tables worth extracting.
-
-
-### 5.4 `screenshot`, `pdf`, and `mhtml`
+### 5.3 `screenshot`, `pdf`, and `mhtml`

 If you set `screenshot=True`, `pdf=True`, or `capture_mhtml=True` in **`CrawlerRunConfig`**, then:

@@ -298,7 +213,7 @@ if result.mhtml:

 The MHTML (MIME HTML) format is particularly useful as it captures the entire web page including all of its resources (CSS, images, scripts, etc.) in a single file, making it perfect for archiving or offline viewing.

-### 5.5 `ssl_certificate`
+### 5.4 `ssl_certificate`

 If `fetch_ssl_certificate=True`, `result.ssl_certificate` holds details about the site’s SSL cert, such as issuer, validity dates, etc.

--- a/docs/md_v2/core/docker-deployment.md
+++ b/docs/md_v2/core/docker-deployment.md
@@ -58,15 +58,15 @@ Pull and run images directly from Docker Hub without building locally.

 #### 1. Pull the Image

-Our latest release is `0.7.3`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.
+Our latest release candidate is `0.7.0-r1`. Images are built with multi-arch manifests, so Docker automatically pulls the correct version for your system.

-> 💡 **Note**: The `latest` tag points to the stable `0.7.3` version.
+> ⚠️ **Important Note**: The `latest` tag currently points to the stable `0.6.0` version. After testing and validation, `0.7.0` (without -r1) will be released and `latest` will be updated. For now, please use `0.7.0-r1` to test the new features.

 ```bash
-# Pull the latest version
-docker pull unclecode/crawl4ai:0.7.3
+# Pull the release candidate (for testing new features)
+docker pull unclecode/crawl4ai:0.7.0-r1

-# Or pull using the latest tag
+# Or pull the current stable version (0.6.0)
 docker pull unclecode/crawl4ai:latest
 ```

@@ -126,7 +126,7 @@ docker stop crawl4ai && docker rm crawl4ai
 #### Docker Hub Versioning Explained

 *   **Image Name:** `unclecode/crawl4ai`
-*   **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.7.3`)
+*   **Tag Format:** `LIBRARY_VERSION[-SUFFIX]` (e.g., `0.7.0-r1`)
    *   `LIBRARY_VERSION`: The semantic version of the core `crawl4ai` Python library
    *   `SUFFIX`: Optional tag for release candidates (``) and revisions (`r1`)
 *   **`latest` Tag:** Points to the most recent stable version
@@ -154,30 +154,6 @@ cp deploy/docker/.llm.env.example .llm.env
 # Now edit .llm.env and add your API keys
 ```

-**Flexible LLM Provider Configuration:**
-
-The Docker setup now supports flexible LLM provider configuration through three methods:
-
-1. **Environment Variable** (Highest Priority): Set `LLM_PROVIDER` to override the default
-   ```bash
-   export LLM_PROVIDER="anthropic/claude-3-opus"
-   # Or in your .llm.env file:
-   # LLM_PROVIDER=anthropic/claude-3-opus
-   ```
-
-2. **API Request Parameter**: Specify provider per request
-   ```json
-   {
-     "url": "https://example.com",
-     "f": "llm",
-     "provider": "groq/mixtral-8x7b"
-   }
-   ```
-
-3. **Config File Default**: Falls back to `config.yml` (default: `openai/gpt-4o-mini`)
-
-The system automatically selects the appropriate API key based on the configured `api_key_env` in the config file.
-
 #### 3. Build and Run with Compose

 The `docker-compose.yml` file in the project root provides a simplified approach that automatically handles architecture detection using buildx.
@@ -692,7 +668,7 @@ app:

 # Default LLM Configuration
 llm:
-  provider: "openai/gpt-4o-mini"  # Can be overridden by LLM_PROVIDER env var
+  provider: "openai/gpt-4o-mini"
  api_key_env: "OPENAI_API_KEY"
  # api_key: sk-...  # If you pass the API key directly then api_key_env will be ignored

--- a/docs/md_v2/core/examples.md
+++ b/docs/md_v2/core/examples.md
@@ -28,8 +28,11 @@ This page provides a comprehensive list of example scripts that demonstrate vari
 | Example | Description | Link |
 |---------|-------------|------|
 | Deep Crawling | An extensive tutorial on deep crawling capabilities, demonstrating BFS and BestFirst strategies, stream vs. non-stream execution, filters, scorers, and advanced configurations. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/deepcrawl_example.py) |
+<<<<<<< HEAD
 | Virtual Scroll | Comprehensive examples for handling virtualized scrolling on sites like Twitter, Instagram. Demonstrates different scrolling scenarios with local test server. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/virtual_scroll_example.py) |
+=======
 | Adaptive Crawling | Demonstrates intelligent crawling that automatically determines when sufficient information has been gathered. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/adaptive_crawling/) |
+>>>>>>> feature/progressive-crawling
 | Dispatcher | Shows how to use the crawl dispatcher for advanced workload management. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/dispatcher_example.py) |
 | Storage State | Tutorial on managing browser storage state for persistence. | [View Guide](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/storage_state_tutorial.md) |
 | Network Console Capture | Demonstrates how to capture and analyze network requests and console logs. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/network_console_capture_example.py) |
@@ -54,16 +57,6 @@ This page provides a comprehensive list of example scripts that demonstrate vari
 | Crypto Analysis | Demonstrates how to crawl and analyze cryptocurrency data. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/crypto_analysis_example.py) |
 | SERP API | Demonstrates using Crawl4AI with search engine result pages. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/serp_api_project_11_feb.py) |

-## Anti-Bot & Stealth Features
-
-| Example | Description | Link |
-|---------|-------------|------|
-| Stealth Mode Quick Start | Five practical examples showing how to use stealth mode for bypassing basic bot detection. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/stealth_mode_quick_start.py) |
-| Stealth Mode Comprehensive | Comprehensive demonstration of stealth mode features with bot detection testing and comparisons. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/stealth_mode_example.py) |
-| Undetected Browser | Simple example showing how to use the undetected browser adapter. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/hello_world_undetected.py) |
-| Undetected Browser Demo | Basic demo comparing regular and undetected browser modes. | [View Code](https://github.com/unclecode/crawl4ai/blob/main/docs/examples/undetected_simple_demo.py) |
-| Undetected Tests | Advanced tests comparing regular vs undetected browsers on various bot detection services. | [View Folder](https://github.com/unclecode/crawl4ai/tree/main/docs/examples/undetectability/) |
-
 ## Customization & Security

 | Example | Description | Link |
@@ -124,4 +117,4 @@ Some examples may require:

 ## Contributing New Examples

-If you've created an interesting example that demonstrates a unique use case or feature of Crawl4AI, we encourage you to contribute it to our examples collection. Please see our [contribution guidelines](https://github.com/unclecode/crawl4ai/blob/main/CONTRIBUTORS.md) for more information.
+If you've created an interesting example that demonstrates a unique use case or feature of Crawl4AI, we encourage you to contribute it to our examples collection. Please see our [contribution guidelines](https://github.com/unclecode/crawl4ai/blob/main/CONTRIBUTORS.md) for more information.
--- a/docs/md_v2/core/installation.md
+++ b/docs/md_v2/core/installation.md
@@ -18,7 +18,7 @@ crawl4ai-setup
 ```

 **What does it do?**
- Installs or updates required browser dependencies for both regular and undetected modes
+- Installs or updates required Playwright browsers (Chromium, Firefox, etc.)
 - Performs OS-level checks (e.g., missing libs on Linux)
 - Confirms your environment is ready to crawl

--- a/docs/md_v2/core/link-media.md
+++ b/docs/md_v2/core/link-media.md
@@ -125,7 +125,7 @@ Here's a full example you can copy, paste, and run immediately:
 ```python
 import asyncio
 from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
-from crawl4ai import LinkPreviewConfig
+from crawl4ai.async_configs import LinkPreviewConfig

 async def extract_link_heads_example():
    """
@@ -237,7 +237,7 @@ if __name__ == "__main__":
 The `LinkPreviewConfig` class supports these options:

 ```python
-from crawl4ai import LinkPreviewConfig
+from crawl4ai.async_configs import LinkPreviewConfig

 link_preview_config = LinkPreviewConfig(
    # BASIC SETTINGS
@@ -520,8 +520,7 @@ This approach is handy when you still want external links but need to block cert

 ### 4.1 Accessing `result.media`

-By default, Crawl4AI collects images, audio and video URLs it finds on the page. These are stored in `result.media`, a dictionary keyed by media type (e.g., `images`, `videos`, `audio`).
-**Note: Tables have been moved from `result.media["tables"]` to the new `result.tables` format for better organization and direct access.**
+By default, Crawl4AI collects images, audio, video URLs, and data tables it finds on the page. These are stored in `result.media`, a dictionary keyed by media type (e.g., `images`, `videos`, `audio`, `tables`).

 **Basic Example**:

@@ -535,6 +534,14 @@ if result.success:
        print(f"           Alt text: {img.get('alt', '')}")
        print(f"           Score: {img.get('score')}")
        print(f"           Description: {img.get('desc', '')}\n")
+    
+    # Get tables
+    tables = result.media.get("tables", [])
+    print(f"Found {len(tables)} data tables in total.")
+    for i, table in enumerate(tables):
+        print(f"[Table {i}] Caption: {table.get('caption', 'No caption')}")
+        print(f"           Columns: {len(table.get('headers', []))}")
+        print(f"           Rows: {len(table.get('rows', []))}")
 ```

 **Structure Example**:
@@ -561,6 +568,19 @@ result.media = {
  "audio": [
    # Similar structure but with audio-specific fields
  ],
+  "tables": [
+    {
+      "headers": ["Name", "Age", "Location"],
+      "rows": [
+        ["John Doe", "34", "New York"],
+        ["Jane Smith", "28", "San Francisco"],
+        ["Alex Johnson", "42", "Chicago"]
+      ],
+      "caption": "Employee Directory",
+      "summary": "Directory of company employees"
+    },
+    # More tables if present
+  ]
 }
 ```

@@ -588,7 +608,53 @@ crawler_cfg = CrawlerRunConfig(

 This setting attempts to discard images from outside the primary domain, keeping only those from the site you’re crawling.

-### 4.3 Additional Media Config
+### 3.3 Working with Tables
+
+Crawl4AI can detect and extract structured data from HTML tables. Tables are analyzed based on various criteria to determine if they are actual data tables (as opposed to layout tables), including:
+
+- Presence of thead and tbody sections
+- Use of th elements for headers
+- Column consistency
+- Text density
+- And other factors
+
+Tables that score above the threshold (default: 7) are extracted and stored in `result.media.tables`.
+
+**Accessing Table Data**:
+
+```python
+if result.success:
+    tables = result.media.get("tables", [])
+    print(f"Found {len(tables)} data tables on the page")
+    
+    if tables:
+        # Access the first table
+        first_table = tables[0]
+        print(f"Table caption: {first_table.get('caption', 'No caption')}")
+        print(f"Headers: {first_table.get('headers', [])}")
+        
+        # Print the first 3 rows
+        for i, row in enumerate(first_table.get('rows', [])[:3]):
+            print(f"Row {i+1}: {row}")
+```
+
+**Configuring Table Extraction**:
+
+You can adjust the sensitivity of the table detection algorithm with:
+
+```python
+crawler_cfg = CrawlerRunConfig(
+    table_score_threshold=5  # Lower value = more tables detected (default: 7)
+)
+```
+
+Each extracted table contains:
+- `headers`: Column header names
+- `rows`: List of rows, each containing cell values
+- `caption`: Table caption text (if available)
+- `summary`: Table summary attribute (if specified)
+
+### 3.4 Additional Media Config

 - **`screenshot`**: Set to `True` if you want a full-page screenshot stored as `base64` in `result.screenshot`.  
 - **`pdf`**: Set to `True` if you want a PDF version of the page in `result.pdf`.  
@@ -629,7 +695,7 @@ The MHTML format is particularly useful because:

 ---

-## 5. Putting It All Together: Link & Media Filtering
+## 4. Putting It All Together: Link & Media Filtering

 Here’s a combined example demonstrating how to filter out external links, skip certain domains, and exclude external images:

@@ -677,7 +743,7 @@ if __name__ == "__main__":

 ---

-## 6. Common Pitfalls & Tips
+## 5. Common Pitfalls & Tips

 1. **Conflicting Flags**:  
   - `exclude_external_links=True` but then also specifying `exclude_social_media_links=True` is typically fine, but understand that the first setting already discards *all* external links. The second becomes somewhat redundant.  
@@ -696,3 +762,10 @@ if __name__ == "__main__":
 ---

 **That’s it for Link & Media Analysis!** You’re now equipped to filter out unwanted sites and zero in on the images and videos that matter for your project.
+### Table Extraction Tips
+
+- Not all HTML tables are extracted - only those detected as "data tables" vs. layout tables.
+- Tables with inconsistent cell counts, nested tables, or those used purely for layout may be skipped.
+- If you're missing tables, try adjusting the `table_score_threshold` to a lower value (default is 7).
+
+The table detection algorithm scores tables based on features like consistent columns, presence of headers, text density, and more. Tables scoring above the threshold are considered data tables worth extracting.
--- a/docs/md_v2/core/url-seeding.md
+++ b/docs/md_v2/core/url-seeding.md
@@ -137,7 +137,7 @@ async def smart_blog_crawler():
            word_count_threshold=300  # Only substantial articles
        )
        
-        # Extract URLs and crawl them
+        # Extract URLs and stream results as they come
        tutorial_urls = [t["url"] for t in tutorials[:10]]
        results = await crawler.arun_many(tutorial_urls, config=config)
        
@@ -231,7 +231,7 @@ Common Crawl is a massive public dataset that regularly crawls the entire web. I

 ```python
 # Use both sources
-config = SeedingConfig(source="sitemap+cc")
+config = SeedingConfig(source="cc+sitemap")
 urls = await seeder.urls("example.com", config)
 ```

@@ -241,13 +241,13 @@ The `SeedingConfig` object is your control panel. Here's everything you can conf

 | Parameter | Type | Default | Description |
 |-----------|------|---------|-------------|
-| `source` | str | "sitemap+cc" | URL source: "cc" (Common Crawl), "sitemap", or "sitemap+cc" |
+| `source` | str | "cc" | URL source: "cc" (Common Crawl), "sitemap", or "cc+sitemap" |
 | `pattern` | str | "*" | URL pattern filter (e.g., "*/blog/*", "*.html") |
 | `extract_head` | bool | False | Extract metadata from page `<head>` |
 | `live_check` | bool | False | Verify URLs are accessible |
 | `max_urls` | int | -1 | Maximum URLs to return (-1 = unlimited) |
 | `concurrency` | int | 10 | Parallel workers for fetching |
-| `hits_per_sec` | int | 5 | Rate limit for requests |
+| `hits_per_sec` | int | None | Rate limit for requests |
 | `force` | bool | False | Bypass cache, fetch fresh data |
 | `verbose` | bool | False | Show detailed progress |
 | `query` | str | None | Search query for BM25 scoring |
@@ -522,7 +522,7 @@ urls = await seeder.urls("docs.example.com", config)
 ```python
 # Find specific products
 config = SeedingConfig(
-    source="sitemap+cc",  # Use both sources
+    source="cc+sitemap",  # Use both sources
    extract_head=True,
    query="wireless headphones noise canceling",
    scoring_method="bm25",
@@ -782,7 +782,7 @@ class ResearchAssistant:
        
        # Step 1: Discover relevant URLs
        config = SeedingConfig(
-            source="sitemap+cc",     # Maximum coverage
+            source="cc+sitemap",     # Maximum coverage
            extract_head=True,       # Get metadata
            query=topic,             # Research topic
            scoring_method="bm25",   # Smart scoring
@@ -832,8 +832,7 @@ class ResearchAssistant:
            # Extract URLs and crawl all articles
            article_urls = [article['url'] for article in top_articles]
            results = []
-            crawl_results = await crawler.arun_many(article_urls, config=config)
-            async for result in crawl_results:
+            async for result in await crawler.arun_many(article_urls, config=config):
                if result.success:
                    results.append({
                        'url': result.url,
@@ -934,10 +933,10 @@ config = SeedingConfig(concurrency=10, hits_per_sec=5)
 # When crawling many URLs
 async with AsyncWebCrawler() as crawler:
    # Assuming urls is a list of URL strings
-    crawl_results = await crawler.arun_many(urls, config=config)
+    results = await crawler.arun_many(urls, config=config)
    
    # Process as they arrive
-    async for result in crawl_results:
+    async for result in results:
        process_immediately(result)  # Don't wait for all
 ```

@@ -1021,7 +1020,7 @@ config = SeedingConfig(

 # E-commerce product discovery
 config = SeedingConfig(
-    source="sitemap+cc",
+    source="cc+sitemap",
    pattern="*/product/*",
    extract_head=True,
    live_check=True
--- a/docs/md_v2/migration/webscraping-strategy-migration.md
+++ b/docs/md_v2/migration/webscraping-strategy-migration.md
@@ -1,92 +0,0 @@
-# WebScrapingStrategy Migration Guide
-
-## Overview
-
-Crawl4AI has simplified its content scraping architecture. The BeautifulSoup-based `WebScrapingStrategy` has been deprecated in favor of the faster LXML-based implementation. However, **no action is required** - your existing code will continue to work.
-
-## What Changed?
-
-1. **`WebScrapingStrategy` is now an alias** for `LXMLWebScrapingStrategy`
-2. **The BeautifulSoup implementation has been removed** (~1000 lines of redundant code)
-3. **`LXMLWebScrapingStrategy` inherits directly** from `ContentScrapingStrategy`
-4. **Performance remains optimal** with LXML as the sole implementation
-
-## Backward Compatibility
-
-**Your existing code continues to work without any changes:**
-
-```python
-# This still works perfectly
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, WebScrapingStrategy
-
-config = CrawlerRunConfig(
-    scraping_strategy=WebScrapingStrategy()  # Works as before
-)
-```
-
-## Migration Options
-
-You have three options:
-
-### Option 1: Do Nothing (Recommended)
-Your code will continue to work. `WebScrapingStrategy` is permanently aliased to `LXMLWebScrapingStrategy`.
-
-### Option 2: Update Imports (Optional)
-For clarity, you can update your imports:
-
-```python
-# Old (still works)
-from crawl4ai import WebScrapingStrategy
-strategy = WebScrapingStrategy()
-
-# New (more explicit)
-from crawl4ai import LXMLWebScrapingStrategy
-strategy = LXMLWebScrapingStrategy()
-```
-
-### Option 3: Use Default Configuration
-Since `LXMLWebScrapingStrategy` is the default, you can omit the strategy parameter:
-
-```python
-# Simplest approach - uses LXMLWebScrapingStrategy by default
-config = CrawlerRunConfig()
-```
-
-## Type Hints
-
-If you use type hints, both work:
-
-```python
-from crawl4ai import WebScrapingStrategy, LXMLWebScrapingStrategy
-
-def process_with_strategy(strategy: WebScrapingStrategy) -> None:
-    # Works with both WebScrapingStrategy and LXMLWebScrapingStrategy
-    pass
-
-# Both are valid
-process_with_strategy(WebScrapingStrategy())
-process_with_strategy(LXMLWebScrapingStrategy())
-```
-
-## Subclassing
-
-If you've subclassed `WebScrapingStrategy`, it continues to work:
-
-```python
-class MyCustomStrategy(WebScrapingStrategy):
-    def __init__(self):
-        super().__init__()
-        # Your custom code
-```
-
-## Performance Benefits
-
-By consolidating to LXML:
- **10-20x faster** HTML parsing for large documents
- **Lower memory usage**
- **Consistent behavior** across all use cases
- **Simplified maintenance** and bug fixes
-
-## Summary
-
-This change simplifies Crawl4AI's internals while maintaining 100% backward compatibility. Your existing code continues to work, and you get better performance automatically.
--- a/docs/releases_review/crawl4ai_v0_7_0_showcase.py
+++ b/docs/releases_review/crawl4ai_v0_7_0_showcase.py
@@ -28,7 +28,7 @@ from rich import box

 from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, AdaptiveCrawler, AdaptiveConfig, BrowserConfig, CacheMode
 from crawl4ai import AsyncUrlSeeder, SeedingConfig
-from crawl4ai import LinkPreviewConfig, VirtualScrollConfig
+from crawl4ai.async_configs import LinkPreviewConfig, VirtualScrollConfig
 from crawl4ai import c4a_compile, CompilationResult

 # Initialize Rich console for beautiful output
--- a/docs/releases_review/v0_7_0_features_demo.py
+++ b/docs/releases_review/v0_7_0_features_demo.py
@@ -13,13 +13,14 @@ from crawl4ai import (
    BrowserConfig,
    CacheMode,
    # New imports for v0.7.0
-    VirtualScrollConfig,
    LinkPreviewConfig,
+    VirtualScrollConfig,
    AdaptiveCrawler,
    AdaptiveConfig,
    AsyncUrlSeeder,
    SeedingConfig,
    c4a_compile,
+    CompilationResult
 )


@@ -169,16 +170,16 @@ async def demo_url_seeder():
        # Discover Python tutorial URLs
        config = SeedingConfig(
            source="sitemap",  # Use sitemap
-            pattern="*python*",  # URL pattern filter
+            pattern="*tutorial*",  # URL pattern filter
            extract_head=True,  # Get metadata
-            query="python tutorial",  # For relevance scoring
+            query="python async programming",  # For relevance scoring
            scoring_method="bm25",
            score_threshold=0.2,
            max_urls=10
        )
        
        print("Discovering Python async tutorial URLs...")
-        urls = await seeder.urls("https://www.geeksforgeeks.org/", config)
+        urls = await seeder.urls("docs.python.org", config)
        
        print(f"\n✅ Found {len(urls)} relevant URLs:")
        for i, url_info in enumerate(urls[:5], 1):
@@ -244,6 +245,39 @@ IF (EXISTS `.price-filter`) THEN CLICK `input[data-max-price="100"]`
        print(f"❌ Compilation error: {result.first_error.message}")


+async def demo_pdf_support():
+    """
+    Demo 6: PDF Parsing Support
+    
+    Shows how to extract content from PDF files.
+    Note: Requires 'pip install crawl4ai[pdf]'
+    """
+    print("\n" + "="*60)
+    print("📄 DEMO 6: PDF Parsing Support")
+    print("="*60)
+    
+    try:
+        # Check if PDF support is installed
+        import PyPDF2
+        
+        # Example: Process a PDF URL
+        config = CrawlerRunConfig(
+            cache_mode=CacheMode.BYPASS,
+            pdf=True,  # Enable PDF generation
+            extract_text_from_pdf=True  # Extract text content
+        )
+        
+        print("PDF parsing is available!")
+        print("You can now crawl PDF URLs and extract their content.")
+        print("\nExample usage:")
+        print('  result = await crawler.arun("https://example.com/document.pdf")')
+        print('  pdf_text = result.extracted_content  # Contains extracted text')
+        
+    except ImportError:
+        print("⚠️  PDF support not installed.")
+        print("Install with: pip install crawl4ai[pdf]")
+
+
 async def main():
    """Run all demos"""
    print("\n🚀 Crawl4AI v0.7.0 Feature Demonstrations")
@@ -255,6 +289,7 @@ async def main():
        ("Virtual Scroll", demo_virtual_scroll),
        ("URL Seeder", demo_url_seeder),
        ("C4A Script", demo_c4a_script),
+        ("PDF Support", demo_pdf_support)
    ]
    
    for name, demo_func in demos:
@@ -274,6 +309,7 @@ async def main():
    print("• Virtual Scroll: Capture all content from modern web pages")
    print("• URL Seeder: Pre-discover and filter URLs efficiently")
    print("• C4A Script: Simple language for complex automations")
+    print("• PDF Support: Extract content from PDF documents")


 if __name__ == "__main__":
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -45,7 +45,6 @@ nav:
    - "Lazy Loading": "advanced/lazy-loading.md"
    - "Hooks & Auth": "advanced/hooks-auth.md"
    - "Proxy & Security": "advanced/proxy-security.md"
-    - "Undetected Browser": "advanced/undetected-browser.md"
    - "Session Management": "advanced/session-management.md"
    - "Multi-URL Crawling": "advanced/multi-url-crawling.md"
    - "Crawl Dispatcher": "advanced/crawl-dispatcher.md"
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -13,37 +13,38 @@ authors = [
    {name = "Unclecode", email = "unclecode@kidocode.com"}
 ]
 dependencies = [
-    "aiofiles>=24.1.0",
-    "aiohttp>=3.11.11",
    "aiosqlite~=0.20",
-    "anyio>=4.0.0",
    "lxml~=5.3",
    "litellm>=1.53.1",
    "numpy>=1.26.0,<3",
    "pillow>=10.4",
    "playwright>=1.49.0",
-    "patchright>=1.49.0",
    "python-dotenv~=1.0",
    "requests~=2.26",
    "beautifulsoup4~=4.12",
    "tf-playwright-stealth>=1.1.0",
    "xxhash~=3.4",
    "rank-bm25~=0.2",
+    "aiofiles>=24.1.0",
    "snowballstemmer~=2.2",
    "pydantic>=2.10",
    "pyOpenSSL>=24.3.0",
    "psutil>=6.1.1",
-    "PyYAML>=6.0",
    "nltk>=3.9.1",
+    "playwright",
    "rich>=13.9.4",
+    "cssselect>=1.2.0",
    "httpx>=0.27.2",
    "httpx[http2]>=0.27.2",
    "fake-useragent>=2.0.3",
    "click>=8.1.7",
+    "pyperclip>=1.8.2",
    "chardet>=5.2.0",
+    "aiohttp>=3.11.11",
    "brotli>=1.1.0",
    "humanize>=4.10.0",
    "lark>=1.2.2",
+    "sentence-transformers>=2.2.0",
    "alphashape>=1.3.1",
    "shapely>=2.0.0"
 ]
@@ -61,8 +62,8 @@ classifiers = [
 [project.optional-dependencies]
 pdf = ["PyPDF2"]  
 torch = ["torch", "nltk", "scikit-learn"]
-transformer = ["transformers", "tokenizers", "sentence-transformers"]
-cosine = ["torch", "transformers", "nltk", "sentence-transformers"]
+transformer = ["transformers", "tokenizers"]
+cosine = ["torch", "transformers", "nltk"]
 sync = ["selenium"]
 all = [
    "PyPDF2",
@@ -71,8 +72,8 @@ all = [
    "scikit-learn",
    "transformers",
    "tokenizers",
-    "sentence-transformers",
-    "selenium"
+    "selenium",
+    "PyPDF2"  
 ]

 [project.scripts]
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,32 +1,30 @@
 # Note: These requirements are also specified in pyproject.toml
 # This file is kept for development environment setup and compatibility
-aiofiles>=24.1.0
-aiohttp>=3.11.11
 aiosqlite~=0.20
-anyio>=4.0.0
 lxml~=5.3
 litellm>=1.53.1
 numpy>=1.26.0,<3
 pillow>=10.4
 playwright>=1.49.0
-patchright>=1.49.0
 python-dotenv~=1.0
 requests~=2.26
 beautifulsoup4~=4.12
 tf-playwright-stealth>=1.1.0
 xxhash~=3.4
 rank-bm25~=0.2
+aiofiles>=24.1.0
 colorama~=0.4
 snowballstemmer~=2.2
 pydantic>=2.10
 pyOpenSSL>=24.3.0
 psutil>=6.1.1
-PyYAML>=6.0
 nltk>=3.9.1
 rich>=13.9.4
+cssselect>=1.2.0
 chardet>=5.2.0
 brotli>=1.1.0
 httpx[http2]>=0.27.2
+sentence-transformers>=2.2.0
 alphashape>=1.3.1
 shapely>=2.0.0

--- a/test_stealth_compatibility.py
+++ b/test_stealth_compatibility.py
@@ -0,0 +1,141 @@
+#!/usr/bin/env python3
+"""
+Test suite for playwright-stealth backward compatibility.
+Tests that stealth functionality works automatically without user configuration.
+"""
+
+import pytest
+import asyncio
+from unittest.mock import Mock, patch, MagicMock
+
+
+class TestPlaywrightStealthCompatibility:
+    """Test playwright-stealth backward compatibility with transparent operation"""
+
+    def test_api_detection_works(self):
+        """Test that API detection works correctly"""
+        from crawl4ai.async_crawler_strategy import STEALTH_NEW_API
+        # The value depends on which version is installed, but should not be undefined
+        assert STEALTH_NEW_API is not None or STEALTH_NEW_API is False or STEALTH_NEW_API is None
+
+    @pytest.mark.asyncio
+    @patch('crawl4ai.async_crawler_strategy.STEALTH_NEW_API', True)
+    @patch('crawl4ai.async_crawler_strategy.Stealth')
+    async def test_apply_stealth_new_api(self, mock_stealth_class):
+        """Test stealth application with new API works transparently"""
+        from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
+        
+        # Setup mock
+        mock_stealth_instance = Mock()
+        mock_stealth_instance.apply_stealth_async = Mock()
+        mock_stealth_class.return_value = mock_stealth_instance
+        
+        # Create strategy instance
+        strategy = AsyncPlaywrightCrawlerStrategy()
+        
+        # Mock page
+        mock_page = Mock()
+        
+        # Test the method - should work transparently
+        await strategy._apply_stealth(mock_page)
+        
+        # Verify new API was used
+        mock_stealth_class.assert_called_once()
+        mock_stealth_instance.apply_stealth_async.assert_called_once_with(mock_page)
+
+    @pytest.mark.asyncio
+    @patch('crawl4ai.async_crawler_strategy.STEALTH_NEW_API', False)
+    async def test_apply_stealth_legacy_api(self):
+        """Test stealth application with legacy API works transparently"""
+        from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
+        
+        # Mock stealth_async function by setting it as a module attribute
+        mock_stealth_async = Mock()
+        mock_stealth_async.return_value = None
+        
+        # Import the module to add the mock function
+        import crawl4ai.async_crawler_strategy
+        crawl4ai.async_crawler_strategy.stealth_async = mock_stealth_async
+        
+        try:
+            # Create strategy instance
+            strategy = AsyncPlaywrightCrawlerStrategy()
+            
+            # Mock page
+            mock_page = Mock()
+            
+            # Test the method - should work transparently
+            await strategy._apply_stealth(mock_page)
+            
+            # Verify legacy API was used
+            mock_stealth_async.assert_called_once_with(mock_page)
+        finally:
+            # Clean up
+            if hasattr(crawl4ai.async_crawler_strategy, 'stealth_async'):
+                delattr(crawl4ai.async_crawler_strategy, 'stealth_async')
+
+    @pytest.mark.asyncio
+    @patch('crawl4ai.async_crawler_strategy.STEALTH_NEW_API', None)
+    async def test_apply_stealth_no_library(self):
+        """Test stealth application when no stealth library is available"""
+        from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
+        
+        # Create strategy instance
+        strategy = AsyncPlaywrightCrawlerStrategy()
+        
+        # Mock page
+        mock_page = Mock()
+        
+        # Test the method - should work transparently even without stealth
+        await strategy._apply_stealth(mock_page)
+        
+        # Should complete without error even when no stealth is available
+
+    @pytest.mark.asyncio
+    @patch('crawl4ai.async_crawler_strategy.STEALTH_NEW_API', True)
+    @patch('crawl4ai.async_crawler_strategy.Stealth')
+    async def test_stealth_error_handling(self, mock_stealth_class):
+        """Test that stealth errors are handled gracefully without breaking crawling"""
+        from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
+        
+        # Setup mock to raise an error
+        mock_stealth_instance = Mock()
+        mock_stealth_instance.apply_stealth_async = Mock(side_effect=Exception("Stealth failed"))
+        mock_stealth_class.return_value = mock_stealth_instance
+        
+        # Create strategy instance
+        strategy = AsyncPlaywrightCrawlerStrategy()
+        
+        # Mock page
+        mock_page = Mock()
+        
+        # Test the method - should not raise an error, continue silently
+        await strategy._apply_stealth(mock_page)
+        
+        # Should complete without raising the stealth error
+
+    def test_strategy_creation_without_config(self):
+        """Test that strategy can be created without any stealth configuration"""
+        from crawl4ai.async_crawler_strategy import AsyncPlaywrightCrawlerStrategy
+        
+        # Should work without any stealth-related parameters
+        strategy = AsyncPlaywrightCrawlerStrategy()
+        assert strategy is not None
+        assert hasattr(strategy, '_apply_stealth')
+
+    def test_browser_config_works_without_stealth_param(self):
+        """Test that BrowserConfig works without stealth parameter"""
+        from crawl4ai.async_configs import BrowserConfig
+        
+        # Should work without stealth parameter
+        config = BrowserConfig()
+        assert config is not None
+        
+        # Should also work with other parameters
+        config = BrowserConfig(headless=False, browser_type="firefox")
+        assert config.headless == False
+        assert config.browser_type == "firefox"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
--- a/tests/async/test_content_scraper_strategy.py
+++ b/tests/async/test_content_scraper_strategy.py
@@ -12,8 +12,11 @@ parent_dir = os.path.dirname(
 sys.path.append(parent_dir)
 __location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))

-from crawl4ai.content_scraping_strategy import LXMLWebScrapingStrategy
-# This test compares the same strategy with itself now since WebScrapingStrategy is deprecated
+from crawl4ai.content_scraping_strategy import WebScrapingStrategy
+from crawl4ai.content_scraping_strategy import (
+    WebScrapingStrategy as WebScrapingStrategyCurrent,
+)
+# from crawl4ai.content_scrapping_strategy_current import WebScrapingStrategy as WebScrapingStrategyCurrent


@dataclass
@@ -29,8 +32,8 @@ class TestResult:

 class StrategyTester:
    def __init__(self):
-        self.new_scraper = LXMLWebScrapingStrategy()
-        self.current_scraper = LXMLWebScrapingStrategy()  # Same strategy now
+        self.new_scraper = WebScrapingStrategy()
+        self.current_scraper = WebScrapingStrategyCurrent()
        with open(__location__ + "/sample_wikipedia.html", "r", encoding="utf-8") as f:
            self.WIKI_HTML = f.read()
        self.results = {"new": [], "current": []}
--- a/tests/check_dependencies.py
+++ b/tests/check_dependencies.py
@@ -1,344 +0,0 @@
-#!/usr/bin/env python3
-"""
-Dependency checker for Crawl4AI
-Analyzes imports in the codebase and shows which files use them
-"""
-
-import ast
-import os
-import sys
-from pathlib import Path
-from typing import Set, Dict, List, Tuple
-from collections import defaultdict
-import re
-import toml
-
-# Standard library modules to ignore
-STDLIB_MODULES = {
-    'abc', 'argparse', 'asyncio', 'base64', 'collections', 'concurrent', 'contextlib',
-    'copy', 'datetime', 'decimal', 'email', 'enum', 'functools', 'glob', 'hashlib',
-    'http', 'importlib', 'io', 'itertools', 'json', 'logging', 'math', 'mimetypes',
-    'multiprocessing', 'os', 'pathlib', 'pickle', 'platform', 'pprint', 'random',
-    're', 'shutil', 'signal', 'socket', 'sqlite3', 'string', 'subprocess', 'sys',
-    'tempfile', 'threading', 'time', 'traceback', 'typing', 'unittest', 'urllib',
-    'uuid', 'warnings', 'weakref', 'xml', 'zipfile', 'dataclasses', 'secrets',
-    'statistics', 'textwrap', 'queue', 'csv', 'gzip', 'tarfile', 'configparser',
-    'inspect', 'operator', 'struct', 'binascii', 'codecs', 'locale', 'gc',
-    'atexit', 'builtins', 'html', 'errno', 'fcntl', 'pwd', 'grp', 'resource',
-    'termios', 'tty', 'pty', 'select', 'selectors', 'ssl', 'zlib', 'bz2',
-    'lzma', 'types', 'copy', 'pydoc', 'profile', 'cProfile', 'timeit',
-    'trace', 'doctest', 'pdb', 'contextvars', 'dataclasses', 'graphlib',
-    'zoneinfo', 'tomllib', 'cgi', 'wsgiref', 'fileinput', 'linecache',
-    'tokenize', 'tabnanny', 'compileall', 'dis', 'pickletools', 'formatter',
-    '__future__', 'array', 'ctypes', 'heapq', 'bisect', 'array', 'weakref',
-    'types', 'copy', 'pprint', 'repr', 'numbers', 'cmath', 'fractions',
-    'statistics', 'itertools', 'functools', 'operator', 'pathlib', 'fileinput',
-    'stat', 'filecmp', 'tempfile', 'glob', 'fnmatch', 'linecache', 'shutil',
-    'pickle', 'copyreg', 'shelve', 'marshal', 'dbm', 'sqlite3', 'zlib', 'gzip',
-    'bz2', 'lzma', 'zipfile', 'tarfile', 'configparser', 'netrc', 'xdrlib',
-    'plistlib', 'hashlib', 'hmac', 'secrets', 'os', 'io', 'time', 'argparse',
-    'getopt', 'logging', 'getpass', 'curses', 'platform', 'errno', 'ctypes',
-    'threading', 'multiprocessing', 'concurrent', 'subprocess', 'sched', 'queue',
-    'contextvars', 'asyncio', 'socket', 'ssl', 'email', 'json', 'mailcap',
-    'mailbox', 'mimetypes', 'base64', 'binhex', 'binascii', 'quopri', 'uu',
-    'html', 'xml', 'webbrowser', 'cgi', 'cgitb', 'wsgiref', 'urllib', 'http',
-    'ftplib', 'poplib', 'imaplib', 'nntplib', 'smtplib', 'smtpd', 'telnetlib',
-    'uuid', 'socketserver', 'xmlrpc', 'ipaddress', 'audioop', 'aifc', 'sunau',
-    'wave', 'chunk', 'colorsys', 'imghdr', 'sndhdr', 'ossaudiodev', 'gettext',
-    'locale', 'turtle', 'cmd', 'shlex', 'tkinter', 'typing', 'pydoc', 'doctest',
-    'unittest', 'test', '2to3', 'distutils', 'venv', 'ensurepip', 'zipapp',
-    'py_compile', 'compileall', 'dis', 'pickletools', 'pdb', 'timeit', 'trace',
-    'tracemalloc', 'warnings', 'faulthandler', 'pdb', 'dataclasses', 'cgi', 
-    'cgitb', 'chunk', 'crypt', 'imghdr', 'mailcap', 'nis', 'nntplib', 'optparse',
-    'ossaudiodev', 'pipes', 'smtpd', 'sndhdr', 'spwd', 'sunau', 'telnetlib',
-    'uu', 'xdrlib', 'msilib', 'pstats', 'rlcompleter', 'tkinter', 'ast'
-}
-
-# Known package name mappings (import name -> package name)
-PACKAGE_MAPPINGS = {
-    'bs4': 'beautifulsoup4',
-    'PIL': 'pillow',
-    'cv2': 'opencv-python',
-    'sklearn': 'scikit-learn',
-    'yaml': 'PyYAML',
-    'OpenSSL': 'pyOpenSSL',
-    'sqlalchemy': 'SQLAlchemy',
-    'playwright': 'playwright',
-    'patchright': 'patchright',
-    'dotenv': 'python-dotenv',
-    'fake_useragent': 'fake-useragent',
-    'playwright_stealth': 'tf-playwright-stealth',
-    'sentence_transformers': 'sentence-transformers',
-    'rank_bm25': 'rank-bm25',
-    'snowballstemmer': 'snowballstemmer',
-    'PyPDF2': 'PyPDF2',
-    'pdf2image': 'pdf2image',
-}
-
-
-class ImportVisitor(ast.NodeVisitor):
-    """AST visitor to extract imports from Python files"""
-    
-    def __init__(self):
-        self.imports = {}  # Changed to dict to store line numbers
-        self.from_imports = {}
-    
-    def visit_Import(self, node):
-        for alias in node.names:
-            module_name = alias.name.split('.')[0]
-            if module_name not in self.imports:
-                self.imports[module_name] = []
-            self.imports[module_name].append(node.lineno)
-    
-    def visit_ImportFrom(self, node):
-        if node.module and node.level == 0:  # absolute imports only
-            module_name = node.module.split('.')[0]
-            if module_name not in self.from_imports:
-                self.from_imports[module_name] = []
-            self.from_imports[module_name].append(node.lineno)
-
-
-def extract_imports_from_file(filepath: Path) -> Dict[str, List[int]]:
-    """Extract all imports from a Python file with line numbers"""
-    all_imports = {}
-    
-    try:
-        with open(filepath, 'r', encoding='utf-8') as f:
-            content = f.read()
-        
-        tree = ast.parse(content)
-        visitor = ImportVisitor()
-        visitor.visit(tree)
-        
-        # Merge imports and from_imports
-        for module, lines in visitor.imports.items():
-            if module not in all_imports:
-                all_imports[module] = []
-            all_imports[module].extend(lines)
-            
-        for module, lines in visitor.from_imports.items():
-            if module not in all_imports:
-                all_imports[module] = []
-            all_imports[module].extend(lines)
-        
-    except Exception as e:
-        # Silently skip files that can't be parsed
-        pass
-    
-    return all_imports
-
-
-def get_codebase_imports_with_files(root_dir: Path) -> Dict[str, List[Tuple[str, List[int]]]]:
-    """Get all imports from the crawl4ai library and docs folders with file locations and line numbers"""
-    import_to_files = defaultdict(list)
-    
-    # Only scan crawl4ai library folder and docs folder
-    target_dirs = [
-        root_dir / 'crawl4ai',
-        root_dir / 'docs'
-    ]
-    
-    for target_dir in target_dirs:
-        if not target_dir.exists():
-            continue
-            
-        for py_file in target_dir.rglob('*.py'):
-            # Skip __pycache__ directories
-            if '__pycache__' in py_file.parts:
-                continue
-            
-            # Skip setup.py and similar files
-            if py_file.name in ['setup.py', 'setup.cfg', 'conf.py']:
-                continue
-                
-            imports = extract_imports_from_file(py_file)
-            
-            # Map each import to the file and line numbers
-            for imp, line_numbers in imports.items():
-                relative_path = py_file.relative_to(root_dir)
-                import_to_files[imp].append((str(relative_path), sorted(line_numbers)))
-    
-    return dict(import_to_files)
-
-
-def get_declared_dependencies() -> Set[str]:
-    """Get declared dependencies from pyproject.toml and requirements.txt"""
-    declared = set()
-    
-    # Read from pyproject.toml
-    if Path('pyproject.toml').exists():
-        with open('pyproject.toml', 'r') as f:
-            data = toml.load(f)
-        
-        # Get main dependencies
-        deps = data.get('project', {}).get('dependencies', [])
-        for dep in deps:
-            # Parse dependency string (e.g., "numpy>=1.26.0,<3")
-            match = re.match(r'^([a-zA-Z0-9_-]+)', dep)
-            if match:
-                pkg_name = match.group(1).lower()
-                declared.add(pkg_name)
-        
-        # Get optional dependencies
-        optional = data.get('project', {}).get('optional-dependencies', {})
-        for group, deps in optional.items():
-            for dep in deps:
-                match = re.match(r'^([a-zA-Z0-9_-]+)', dep)
-                if match:
-                    pkg_name = match.group(1).lower()
-                    declared.add(pkg_name)
-    
-    # Also check requirements.txt as backup
-    if Path('requirements.txt').exists():
-        with open('requirements.txt', 'r') as f:
-            for line in f:
-                line = line.strip()
-                if line and not line.startswith('#'):
-                    match = re.match(r'^([a-zA-Z0-9_-]+)', line)
-                    if match:
-                        pkg_name = match.group(1).lower()
-                        declared.add(pkg_name)
-    
-    return declared
-
-
-def normalize_package_name(name: str) -> str:
-    """Normalize package name for comparison"""
-    # Handle known mappings first
-    if name in PACKAGE_MAPPINGS:
-        return PACKAGE_MAPPINGS[name].lower()
-    
-    # Basic normalization
-    return name.lower().replace('_', '-')
-
-
-def check_missing_dependencies():
-    """Main function to check for missing dependencies"""
-    print("🔍 Analyzing crawl4ai library and docs folders...\n")
-    
-    # Get all imports with their file locations
-    root_dir = Path('.')
-    import_to_files = get_codebase_imports_with_files(root_dir)
-    
-    # Get declared dependencies
-    declared_deps = get_declared_dependencies()
-    
-    # Normalize declared dependencies
-    normalized_declared = {normalize_package_name(dep) for dep in declared_deps}
-    
-    # Categorize imports
-    external_imports = {}
-    local_imports = {}
-    
-    # Known local packages
-    local_packages = {'crawl4ai'}
-    
-    for imp, file_info in import_to_files.items():
-        # Skip standard library
-        if imp in STDLIB_MODULES:
-            continue
-            
-        # Check if it's a local import
-        if any(imp.startswith(local) for local in local_packages):
-            local_imports[imp] = file_info
-        else:
-            external_imports[imp] = file_info
-    
-    # Check which external imports are not declared
-    not_declared = {}
-    declared_imports = {}
-    
-    for imp, file_info in external_imports.items():
-        normalized_imp = normalize_package_name(imp)
-        
-        # Check if import is covered by declared dependencies
-        found = False
-        for declared in normalized_declared:
-            if normalized_imp == declared or normalized_imp.startswith(declared + '.') or declared.startswith(normalized_imp):
-                found = True
-                break
-        
-        if found:
-            declared_imports[imp] = file_info
-        else:
-            not_declared[imp] = file_info
-    
-    # Print results
-    print(f"📊 Summary:")
-    print(f"  - Total unique imports: {len(import_to_files)}")
-    print(f"  - External imports: {len(external_imports)}")
-    print(f"  - Declared dependencies: {len(declared_deps)}")
-    print(f"  - External imports NOT in dependencies: {len(not_declared)}\n")
-    
-    if not_declared:
-        print("❌ External imports NOT declared in pyproject.toml or requirements.txt:\n")
-        
-        # Sort by import name
-        for imp in sorted(not_declared.keys()):
-            file_info = not_declared[imp]
-            print(f"  📦 {imp}")
-            if imp in PACKAGE_MAPPINGS:
-                print(f"     → Package name: {PACKAGE_MAPPINGS[imp]}")
-            
-            # Show up to 3 files that use this import
-            for i, (file_path, line_numbers) in enumerate(file_info[:3]):
-                # Format line numbers for clickable output
-                if len(line_numbers) == 1:
-                    print(f"     - {file_path}:{line_numbers[0]}")
-                else:
-                    # Show first few line numbers
-                    line_str = ','.join(str(ln) for ln in line_numbers[:3])
-                    if len(line_numbers) > 3:
-                        line_str += f"... ({len(line_numbers)} imports)"
-                    print(f"     - {file_path}: lines {line_str}")
-            
-            if len(file_info) > 3:
-                print(f"     ... and {len(file_info) - 3} more files")
-            print()
-    
-    # Check for potentially unused dependencies
-    print("\n🔎 Checking declared dependencies usage...\n")
-    
-    # Get all used external packages
-    used_packages = set()
-    for imp in external_imports.keys():
-        normalized = normalize_package_name(imp)
-        used_packages.add(normalized)
-    
-    # Find unused
-    unused = []
-    for dep in declared_deps:
-        normalized_dep = normalize_package_name(dep)
-        
-        # Check if any import uses this dependency
-        found_usage = False
-        for used in used_packages:
-            if used == normalized_dep or used.startswith(normalized_dep) or normalized_dep.startswith(used):
-                found_usage = True
-                break
-        
-        if not found_usage:
-            # Some packages are commonly unused directly
-            indirect_deps = {'wheel', 'setuptools', 'pip', 'colorama', 'certifi', 'packaging', 'urllib3'}
-            if normalized_dep not in indirect_deps:
-                unused.append(dep)
-    
-    if unused:
-        print("⚠️  Declared dependencies with NO imports found:")
-        for dep in sorted(unused):
-            print(f"  - {dep}")
-        print("\n  Note: These might be used indirectly or by other dependencies")
-    else:
-        print("✅ All declared dependencies have corresponding imports")
-    
-    print("\n" + "="*60)
-    print("💡 How to use this report:")
-    print("  1. Check each ❌ import to see if it's legitimate")
-    print("  2. If legitimate, add the package to pyproject.toml")
-    print("  3. If it's an internal module or typo, fix the import")
-    print("  4. Review unused dependencies - remove if truly not needed")
-    print("="*60)
-
-
-if __name__ == '__main__':
-    check_missing_dependencies()
--- a/tests/docker/simple_api_test.py
+++ b/tests/docker/simple_api_test.py
@@ -1,345 +0,0 @@
-#!/usr/bin/env python3
-"""
-Simple API Test for Crawl4AI Docker Server v0.7.0
-Uses only built-in Python modules to test all endpoints.
-"""
-
-import urllib.request
-import urllib.parse
-import json
-import time
-import sys
-from typing import Dict, List, Optional
-
-# Configuration
-BASE_URL = "http://localhost:11234"  # Change to your server URL
-TEST_TIMEOUT = 30
-
-class SimpleApiTester:
-    def __init__(self, base_url: str = BASE_URL):
-        self.base_url = base_url
-        self.token = None
-        self.results = []
-        
-    def log(self, message: str):
-        print(f"[INFO] {message}")
-    
-    def test_get_endpoint(self, endpoint: str) -> Dict:
-        """Test a GET endpoint"""
-        url = f"{self.base_url}{endpoint}"
-        start_time = time.time()
-        
-        try:
-            req = urllib.request.Request(url)
-            if self.token:
-                req.add_header('Authorization', f'Bearer {self.token}')
-            
-            with urllib.request.urlopen(req, timeout=TEST_TIMEOUT) as response:
-                response_time = time.time() - start_time
-                status_code = response.getcode()
-                content = response.read().decode('utf-8')
-                
-                # Try to parse JSON
-                try:
-                    data = json.loads(content)
-                except:
-                    data = {"raw_response": content[:200]}
-                
-                return {
-                    "endpoint": endpoint,
-                    "method": "GET",
-                    "status": "PASS" if status_code < 400 else "FAIL",
-                    "status_code": status_code,
-                    "response_time": response_time,
-                    "data": data
-                }
-        except Exception as e:
-            response_time = time.time() - start_time
-            return {
-                "endpoint": endpoint,
-                "method": "GET",
-                "status": "FAIL",
-                "status_code": None,
-                "response_time": response_time,
-                "error": str(e)
-            }
-    
-    def test_post_endpoint(self, endpoint: str, payload: Dict) -> Dict:
-        """Test a POST endpoint"""
-        url = f"{self.base_url}{endpoint}"
-        start_time = time.time()
-        
-        try:
-            data = json.dumps(payload).encode('utf-8')
-            req = urllib.request.Request(url, data=data, method='POST')
-            req.add_header('Content-Type', 'application/json')
-            
-            if self.token:
-                req.add_header('Authorization', f'Bearer {self.token}')
-            
-            with urllib.request.urlopen(req, timeout=TEST_TIMEOUT) as response:
-                response_time = time.time() - start_time
-                status_code = response.getcode()
-                content = response.read().decode('utf-8')
-                
-                # Try to parse JSON
-                try:
-                    data = json.loads(content)
-                except:
-                    data = {"raw_response": content[:200]}
-                
-                return {
-                    "endpoint": endpoint,
-                    "method": "POST",
-                    "status": "PASS" if status_code < 400 else "FAIL",
-                    "status_code": status_code,
-                    "response_time": response_time,
-                    "data": data
-                }
-        except Exception as e:
-            response_time = time.time() - start_time
-            return {
-                "endpoint": endpoint,
-                "method": "POST",
-                "status": "FAIL",
-                "status_code": None,
-                "response_time": response_time,
-                "error": str(e)
-            }
-    
-    def print_result(self, result: Dict):
-        """Print a formatted test result"""
-        status_color = {
-            "PASS": "✅",
-            "FAIL": "❌",
-            "SKIP": "⏭️"
-        }
-        
-        print(f"{status_color[result['status']]} {result['method']} {result['endpoint']} "
-              f"| {result['response_time']:.3f}s | Status: {result['status_code'] or 'N/A'}")
-        
-        if result['status'] == 'FAIL' and 'error' in result:
-            print(f"    Error: {result['error']}")
-        
-        self.results.append(result)
-    
-    def run_all_tests(self):
-        """Run all API tests"""
-        print("🚀 Starting Crawl4AI v0.7.0 API Test Suite")
-        print(f"📡 Testing server at: {self.base_url}")
-        print("=" * 60)
-        
-        # # Test basic endpoints
-        # print("\n=== BASIC ENDPOINTS ===")
-        
-        # # Health check
-        # result = self.test_get_endpoint("/health")
-        # self.print_result(result)
-        
-        
-        # # Schema endpoint
-        # result = self.test_get_endpoint("/schema")
-        # self.print_result(result)
-        
-        # # Metrics endpoint
-        # result = self.test_get_endpoint("/metrics")
-        # self.print_result(result)
-        
-        # # Root redirect
-        # result = self.test_get_endpoint("/")
-        # self.print_result(result)
-        
-        # # Test authentication
-        # print("\n=== AUTHENTICATION ===")
-        
-        # # Get token
-        # token_payload = {"email": "test@example.com"}
-        # result = self.test_post_endpoint("/token", token_payload)
-        # self.print_result(result)
-        
-        # # Extract token if successful
-        # if result['status'] == 'PASS' and 'data' in result:
-        #     token = result['data'].get('access_token')
-        #     if token:
-        #         self.token = token
-        #         self.log(f"Successfully obtained auth token: {token[:20]}...")
-        
-        # Test core APIs
-        print("\n=== CORE APIs ===")
-        
-        test_url = "https://example.com"
-        
-        # Test markdown endpoint
-        md_payload = {
-            "url": test_url,
-            "f": "fit",
-            "q": "test query",
-            "c": "0"
-        }
-        result = self.test_post_endpoint("/md", md_payload)
-        # print(result['data'].get('markdown', ''))
-        self.print_result(result)
-        
-        # Test HTML endpoint
-        html_payload = {"url": test_url}
-        result = self.test_post_endpoint("/html", html_payload)
-        self.print_result(result)
-        
-        # Test screenshot endpoint
-        screenshot_payload = {
-            "url": test_url,
-            "screenshot_wait_for": 2
-        }
-        result = self.test_post_endpoint("/screenshot", screenshot_payload)
-        self.print_result(result)
-        
-        # Test PDF endpoint
-        pdf_payload = {"url": test_url}
-        result = self.test_post_endpoint("/pdf", pdf_payload)
-        self.print_result(result)
-        
-        # Test JavaScript execution
-        js_payload = {
-            "url": test_url,
-            "scripts": ["(() => document.title)()"]
-        }
-        result = self.test_post_endpoint("/execute_js", js_payload)
-        self.print_result(result)
-        
-        # Test crawl endpoint
-        crawl_payload = {
-            "urls": [test_url],
-            "browser_config": {},
-            "crawler_config": {}
-        }
-        result = self.test_post_endpoint("/crawl", crawl_payload)
-        self.print_result(result)
-        
-        # Test config dump
-        config_payload = {"code": "CrawlerRunConfig()"}
-        result = self.test_post_endpoint("/config/dump", config_payload)
-        self.print_result(result)
-        
-        # Test LLM endpoint
-        llm_endpoint = f"/llm/{test_url}?q=Extract%20main%20content"
-        result = self.test_get_endpoint(llm_endpoint)
-        self.print_result(result)
-        
-        # Test ask endpoint
-        ask_endpoint = "/ask?context_type=all&query=crawl4ai&max_results=5"
-        result = self.test_get_endpoint(ask_endpoint)
-        print(result)
-        self.print_result(result)
-        
-        # Test job APIs
-        print("\n=== JOB APIs ===")
-        
-        # Test LLM job
-        llm_job_payload = {
-            "url": test_url,
-            "q": "Extract main content",
-            "cache": False
-        }
-        result = self.test_post_endpoint("/llm/job", llm_job_payload)
-        self.print_result(result)
-        
-        # Test crawl job
-        crawl_job_payload = {
-            "urls": [test_url],
-            "browser_config": {},
-            "crawler_config": {}
-        }
-        result = self.test_post_endpoint("/crawl/job", crawl_job_payload)
-        self.print_result(result)
-        
-        # Test MCP
-        print("\n=== MCP APIs ===")
-        
-        # Test MCP schema
-        result = self.test_get_endpoint("/mcp/schema")
-        self.print_result(result)
-        
-        # Test error handling
-        print("\n=== ERROR HANDLING ===")
-        
-        # Test invalid URL
-        invalid_payload = {"url": "invalid-url", "f": "fit"}
-        result = self.test_post_endpoint("/md", invalid_payload)
-        self.print_result(result)
-        
-        # Test invalid endpoint
-        result = self.test_get_endpoint("/nonexistent")
-        self.print_result(result)
-        
-        # Print summary
-        self.print_summary()
-    
-    def print_summary(self):
-        """Print test results summary"""
-        print("\n" + "=" * 60)
-        print("📊 TEST RESULTS SUMMARY")
-        print("=" * 60)
-        
-        total = len(self.results)
-        passed = sum(1 for r in self.results if r['status'] == 'PASS')
-        failed = sum(1 for r in self.results if r['status'] == 'FAIL')
-        
-        print(f"Total Tests: {total}")
-        print(f"✅ Passed: {passed}")
-        print(f"❌ Failed: {failed}")
-        print(f"📈 Success Rate: {(passed/total)*100:.1f}%")
-        
-        if failed > 0:
-            print("\n❌ FAILED TESTS:")
-            for result in self.results:
-                if result['status'] == 'FAIL':
-                    print(f"  • {result['method']} {result['endpoint']}")
-                    if 'error' in result:
-                        print(f"    Error: {result['error']}")
-        
-        # Performance statistics
-        response_times = [r['response_time'] for r in self.results if r['response_time'] > 0]
-        if response_times:
-            avg_time = sum(response_times) / len(response_times)
-            max_time = max(response_times)
-            print(f"\n⏱️  Average Response Time: {avg_time:.3f}s")
-            print(f"⏱️  Max Response Time: {max_time:.3f}s")
-        
-        # Save detailed report
-        report_file = f"crawl4ai_test_report_{int(time.time())}.json"
-        with open(report_file, 'w') as f:
-            json.dump({
-                "timestamp": time.time(),
-                "server_url": self.base_url,
-                "version": "0.7.0",
-                "summary": {
-                    "total": total,
-                    "passed": passed,
-                    "failed": failed
-                },
-                "results": self.results
-            }, f, indent=2)
-        
-        print(f"\n📄 Detailed report saved to: {report_file}")
-
-def main():
-    """Main test runner"""
-    import argparse
-    
-    parser = argparse.ArgumentParser(description='Crawl4AI v0.7.0 API Test Suite')
-    parser.add_argument('--url', default=BASE_URL, help='Base URL of the server')
-    
-    args = parser.parse_args()
-    
-    tester = SimpleApiTester(args.url)
-    
-    try:
-        tester.run_all_tests()
-    except KeyboardInterrupt:
-        print("\n🛑 Test suite interrupted by user")
-    except Exception as e:
-        print(f"\n💥 Test suite failed with error: {e}")
-        sys.exit(1)
-
-if __name__ == "__main__":
-    main()
--- a/tests/test_arun_many.py
+++ b/tests/test_arun_many.py
@@ -1,42 +0,0 @@
-"""
-Test example for multiple crawler configs feature
-"""
-import asyncio
-import sys
-from pathlib import Path
-
-# Add parent directory to path for imports
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, CacheMode
-from crawl4ai.processors.pdf import PDFContentScrapingStrategy
-
-
-async def test_run_many():
-    default_config = CrawlerRunConfig(
-        cache_mode=CacheMode.BYPASS,
-        # scraping_strategy=PDFContentScrapingStrategy()
-    )
-    
-    test_urls = [
-        # "https://blog.python.org/",  # Blog URL  
-        "https://www.python.org/",  # Generic HTTPS page
-        "https://www.kidocode.com/",  # Generic HTTPS page
-        "https://www.example.com/",  # Generic HTTPS page
-        # "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",
-    ]
-    
-    async with AsyncWebCrawler() as crawler:
-        # Single config - traditional usage still works
-        print("Test 1: Single config (backwards compatible)")
-        result = await crawler.arun_many(
-            urls=test_urls[:2],
-            config=default_config
-        )
-        print(f"Crawled {len(result)} URLs with single config\n")
-        for item in result:
-            print(f"  {item.url} -> {item.status_code}")
-        
-
-if __name__ == "__main__":
-    asyncio.run(test_run_many())
--- a/tests/test_config_matching_only.py
+++ b/tests/test_config_matching_only.py
@@ -1,131 +0,0 @@
-"""
-Test only the config matching logic without running crawler
-"""
-import sys
-from pathlib import Path
-
-# Add parent directory to path for imports
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from crawl4ai.async_configs import CrawlerRunConfig, MatchMode
-
-def test_all_matching_scenarios():
-    print("Testing CrawlerRunConfig.is_match() method")
-    print("=" * 50)
-    
-    # Test 1: Single string pattern
-    print("\n1. Single string pattern (glob style)")
-    config = CrawlerRunConfig(
-        url_matcher="*.pdf",
-        # For example we can set this => scraping_strategy=PDFContentScrapingStrategy()
-    )
-    test_urls = [
-        ("https://example.com/file.pdf", True),
-        ("https://example.com/doc.PDF", False),  # Case sensitive
-        ("https://example.com/file.txt", False),
-        ("file.pdf", True),
-    ]
-    for url, expected in test_urls:
-        result = config.is_match(url)
-        status = "✓" if result == expected else "✗"
-        print(f"  {status} {url} -> {result}")
-    
-    # Test 2: List of patterns with OR
-    print("\n2. List of patterns with OR (default)")
-    config = CrawlerRunConfig(
-        url_matcher=["*/article/*", "*/blog/*", "*.html"],
-        match_mode=MatchMode.OR
-    )
-    test_urls = [
-        ("https://example.com/article/news", True),
-        ("https://example.com/blog/post", True),
-        ("https://example.com/page.html", True),
-        ("https://example.com/page.php", False),
-    ]
-    for url, expected in test_urls:
-        result = config.is_match(url)
-        status = "✓" if result == expected else "✗"
-        print(f"  {status} {url} -> {result}")
-    
-    # Test 3: Custom function
-    print("\n3. Custom function matcher")
-    config = CrawlerRunConfig(
-        url_matcher=lambda url: 'api' in url and (url.endswith('.json') or url.endswith('.xml'))
-    )
-    test_urls = [
-        ("https://api.example.com/data.json", True),
-        ("https://api.example.com/data.xml", True),
-        ("https://api.example.com/data.html", False),
-        ("https://example.com/data.json", False),  # No 'api'
-    ]
-    for url, expected in test_urls:
-        result = config.is_match(url)
-        status = "✓" if result == expected else "✗"
-        print(f"  {status} {url} -> {result}")
-    
-    # Test 4: Mixed list with AND
-    print("\n4. Mixed patterns and functions with AND")
-    config = CrawlerRunConfig(
-        url_matcher=[
-            "https://*",  # Must be HTTPS
-            lambda url: '.com' in url,  # Must have .com
-            lambda url: len(url) < 50  # Must be short
-        ],
-        match_mode=MatchMode.AND
-    )
-    test_urls = [
-        ("https://example.com/page", True),
-        ("http://example.com/page", False),  # Not HTTPS
-        ("https://example.org/page", False),  # No .com
-        ("https://example.com/" + "x" * 50, False),  # Too long
-    ]
-    for url, expected in test_urls:
-        result = config.is_match(url)
-        status = "✓" if result == expected else "✗"
-        print(f"  {status} {url} -> {result}")
-    
-    # Test 5: Complex real-world scenario
-    print("\n5. Complex pattern combinations")
-    config = CrawlerRunConfig(
-        url_matcher=[
-            "*/api/v[0-9]/*",  # API versioned endpoints
-            lambda url: 'graphql' in url,  # GraphQL endpoints
-            "*.json"  # JSON files
-        ],
-        match_mode=MatchMode.OR
-    )
-    test_urls = [
-        ("https://example.com/api/v1/users", True),
-        ("https://example.com/api/v2/posts", True),
-        ("https://example.com/graphql", True),
-        ("https://example.com/data.json", True),
-        ("https://example.com/api/users", False),  # No version
-    ]
-    for url, expected in test_urls:
-        result = config.is_match(url)
-        status = "✓" if result == expected else "✗"
-        print(f"  {status} {url} -> {result}")
-    
-    # Test 6: Edge cases
-    print("\n6. Edge cases")
-    
-    # No matcher
-    config = CrawlerRunConfig()
-    result = config.is_match("https://example.com")
-    print(f"  {'✓' if not result else '✗'} No matcher -> {result}")
-    
-    # Empty list
-    config = CrawlerRunConfig(url_matcher=[])
-    result = config.is_match("https://example.com")
-    print(f"  {'✓' if not result else '✗'} Empty list -> {result}")
-    
-    # None in list (should be skipped)
-    config = CrawlerRunConfig(url_matcher=["*.pdf", None, "*.doc"])
-    result = config.is_match("test.pdf")
-    print(f"  {'✓' if result else '✗'} List with None -> {result}")
-    
-    print("\n" + "=" * 50)
-    print("All matching tests completed!")
-
-if __name__ == "__main__":
-    test_all_matching_scenarios()
--- a/tests/test_config_selection.py
+++ b/tests/test_config_selection.py
@@ -1,87 +0,0 @@
-"""
-Test config selection logic in dispatchers
-"""
-import asyncio
-import sys
-from pathlib import Path
-from unittest.mock import AsyncMock, MagicMock
-
-# Add parent directory to path for imports
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from crawl4ai.async_configs import CrawlerRunConfig, MatchMode
-from crawl4ai.async_dispatcher import BaseDispatcher, MemoryAdaptiveDispatcher
-
-class TestDispatcher(BaseDispatcher):
-    """Simple test dispatcher to verify config selection"""
-    
-    async def crawl_url(self, url, config, task_id, **kwargs):
-        # Just return which config was selected
-        selected = self.select_config(url, config)
-        return {"url": url, "config_id": id(selected)}
-    
-    async def run_urls(self, urls, crawler, config):
-        results = []
-        for url in urls:
-            result = await self.crawl_url(url, config, "test")
-            results.append(result)
-        return results
-
-async def test_dispatcher_config_selection():
-    print("Testing dispatcher config selection")
-    print("=" * 50)
-    
-    # Create test configs with different matchers
-    pdf_config = CrawlerRunConfig(url_matcher="*.pdf")
-    api_config = CrawlerRunConfig(url_matcher=lambda url: 'api' in url)
-    default_config = CrawlerRunConfig()  # No matcher
-    
-    configs = [pdf_config, api_config, default_config]
-    
-    # Create test dispatcher
-    dispatcher = TestDispatcher()
-    
-    # Test single config
-    print("\nTest 1: Single config")
-    result = await dispatcher.crawl_url("https://example.com/file.pdf", pdf_config, "test1")
-    assert result["config_id"] == id(pdf_config)
-    print("✓ Single config works")
-    
-    # Test config list selection
-    print("\nTest 2: Config list selection")
-    test_cases = [
-        ("https://example.com/file.pdf", id(pdf_config)),
-        ("https://api.example.com/data", id(api_config)),
-        ("https://example.com/page", id(configs[0])),  # No match, uses first
-    ]
-    
-    for url, expected_id in test_cases:
-        result = await dispatcher.crawl_url(url, configs, "test")
-        assert result["config_id"] == expected_id, f"URL {url} got wrong config"
-        print(f"✓ {url} -> correct config selected")
-    
-    # Test with MemoryAdaptiveDispatcher
-    print("\nTest 3: MemoryAdaptiveDispatcher config selection")
-    mem_dispatcher = MemoryAdaptiveDispatcher()
-    
-    # Test select_config method directly
-    selected = mem_dispatcher.select_config("https://example.com/doc.pdf", configs)
-    assert selected == pdf_config
-    print("✓ MemoryAdaptiveDispatcher.select_config works")
-    
-    # Test empty config list
-    print("\nTest 4: Edge cases")
-    selected = mem_dispatcher.select_config("https://example.com", [])
-    assert isinstance(selected, CrawlerRunConfig)  # Should return default
-    print("✓ Empty config list returns default config")
-    
-    # Test None config
-    selected = mem_dispatcher.select_config("https://example.com", None)
-    assert isinstance(selected, CrawlerRunConfig)  # Should return default
-    print("✓ None config returns default config")
-    
-    print("\n" + "=" * 50)
-    print("All dispatcher tests passed! ✓")
-
-if __name__ == "__main__":
-    asyncio.run(test_dispatcher_config_selection())
--- a/tests/test_docker_api_with_llm_provider.py
+++ b/tests/test_docker_api_with_llm_provider.py
@@ -1,122 +0,0 @@
-#!/usr/bin/env python3
-"""Test script to verify Docker API with LLM provider configuration."""
-
-import requests
-import json
-import time
-
-BASE_URL = "http://localhost:11235"
-
-def test_health():
-    """Test health endpoint."""
-    print("1. Testing health endpoint...")
-    response = requests.get(f"{BASE_URL}/health")
-    print(f"   Status: {response.status_code}")
-    print(f"   Response: {response.json()}")
-    print()
-
-def test_schema():
-    """Test schema endpoint to see configuration."""
-    print("2. Testing schema endpoint...")
-    response = requests.get(f"{BASE_URL}/schema")
-    print(f"   Status: {response.status_code}")
-    # Print only browser config to keep output concise
-    print(f"   Browser config keys: {list(response.json().get('browser', {}).keys())[:5]}...")
-    print()
-
-def test_markdown_with_llm_filter():
-    """Test markdown endpoint with LLM filter (should use configured provider)."""
-    print("3. Testing markdown endpoint with LLM filter...")
-    print("   This should use the Groq provider from LLM_PROVIDER env var")
-    
-    # Note: This will fail with dummy API keys, but we can see if it tries to use Groq
-    payload = {
-        "url": "https://httpbin.org/html",
-        "f": "llm",
-        "q": "Extract the main content"
-    }
-    
-    response = requests.post(f"{BASE_URL}/md", json=payload)
-    print(f"   Status: {response.status_code}")
-    
-    if response.status_code != 200:
-        print(f"   Error: {response.text[:200]}...")
-    else:
-        print(f"   Success! Markdown length: {len(response.json().get('markdown', ''))} chars")
-    print()
-
-def test_markdown_with_provider_override():
-    """Test markdown endpoint with provider override in request."""
-    print("4. Testing markdown endpoint with provider override...")
-    print("   This should use OpenAI provider from request parameter")
-    
-    payload = {
-        "url": "https://httpbin.org/html",
-        "f": "llm",
-        "q": "Extract the main content",
-        "provider": "openai/gpt-4"  # Override to use OpenAI
-    }
-    
-    response = requests.post(f"{BASE_URL}/md", json=payload)
-    print(f"   Status: {response.status_code}")
-    
-    if response.status_code != 200:
-        print(f"   Error: {response.text[:200]}...")
-    else:
-        print(f"   Success! Markdown length: {len(response.json().get('markdown', ''))} chars")
-    print()
-
-def test_simple_crawl():
-    """Test simple crawl without LLM."""
-    print("5. Testing simple crawl (no LLM required)...")
-    
-    payload = {
-        "urls": ["https://httpbin.org/html"],
-        "browser_config": {
-            "type": "BrowserConfig",
-            "params": {"headless": True}
-        },
-        "crawler_config": {
-            "type": "CrawlerRunConfig",
-            "params": {"cache_mode": "bypass"}
-        }
-    }
-    
-    response = requests.post(f"{BASE_URL}/crawl", json=payload)
-    print(f"   Status: {response.status_code}")
-    
-    if response.status_code == 200:
-        result = response.json()
-        print(f"   Success: {result.get('success')}")
-        print(f"   Results count: {len(result.get('results', []))}")
-        if result.get('results'):
-            print(f"   First result success: {result['results'][0].get('success')}")
-    else:
-        print(f"   Error: {response.text[:200]}...")
-    print()
-
-def test_playground():
-    """Test if playground is accessible."""
-    print("6. Testing playground interface...")
-    response = requests.get(f"{BASE_URL}/playground")
-    print(f"   Status: {response.status_code}")
-    print(f"   Content-Type: {response.headers.get('content-type')}")
-    print()
-
-if __name__ == "__main__":
-    print("=== Crawl4AI Docker API Tests ===\n")
-    print(f"Testing API at {BASE_URL}\n")
-    
-    # Wait a bit for server to be fully ready
-    time.sleep(2)
-    
-    test_health()
-    test_schema()
-    test_simple_crawl()
-    test_playground()
-    
-    print("\nTesting LLM functionality (these may fail with dummy API keys):\n")
-    test_markdown_with_llm_filter()
-    test_markdown_with_provider_override()
-    
-    print("\nTests completed!")
--- a/tests/test_link_extractor.py
+++ b/tests/test_link_extractor.py
@@ -5,7 +5,7 @@ Test script for Link Extractor functionality

 from crawl4ai.models import Link
 from crawl4ai import AsyncWebCrawler, CrawlerRunConfig
-from crawl4ai import LinkPreviewConfig
+from crawl4ai.async_configs import LinkPreviewConfig
 import asyncio
 import sys
 import os
@@ -237,7 +237,7 @@ def test_config_examples():
            print(f"     {key}: {value}")

        print("   Usage:")
-        print("     from crawl4ai import LinkPreviewConfig")
+        print("     from crawl4ai.async_configs import LinkPreviewConfig")
        print("     config = CrawlerRunConfig(")
        print("         link_preview_config=LinkPreviewConfig(")
        for key, value in config_dict.items():
--- a/tests/test_memory_macos.py
+++ b/tests/test_memory_macos.py
@@ -1,71 +0,0 @@
-#!/usr/bin/env python3
-"""Test script to verify macOS memory calculation accuracy."""
-
-import psutil
-import platform
-import time
-from crawl4ai.memory_utils import get_true_memory_usage_percent, get_memory_stats, get_true_available_memory_gb
-
-
-def test_memory_calculation():
-    """Test and compare memory calculations."""
-    print(f"Platform: {platform.system()}")
-    print(f"Python version: {platform.python_version()}")
-    print("-" * 60)
-    
-    # Get psutil's view
-    vm = psutil.virtual_memory()
-    psutil_percent = vm.percent
-    psutil_available_gb = vm.available / (1024**3)
-    total_gb = vm.total / (1024**3)
-    
-    # Get our corrected view
-    true_percent = get_true_memory_usage_percent()
-    true_available_gb = get_true_available_memory_gb()
-    true_percent_calc, available_calc, total_calc = get_memory_stats()
-    
-    print("Memory Statistics Comparison:")
-    print(f"Total Memory: {total_gb:.2f} GB")
-    print()
-    
-    print("PSUtil (Standard) Calculation:")
-    print(f"  - Memory Used: {psutil_percent:.1f}%")
-    print(f"  - Available: {psutil_available_gb:.2f} GB")
-    print()
-    
-    print("Platform-Aware Calculation:")
-    print(f"  - Memory Used: {true_percent:.1f}%")
-    print(f"  - Available: {true_available_gb:.2f} GB")
-    print(f"  - Difference: {true_available_gb - psutil_available_gb:.2f} GB of reclaimable memory")
-    print()
-    
-    # Show the impact on dispatcher behavior
-    print("Impact on MemoryAdaptiveDispatcher:")
-    thresholds = {
-        "Normal": 90.0,
-        "Critical": 95.0,
-        "Recovery": 85.0
-    }
-    
-    for name, threshold in thresholds.items():
-        psutil_triggered = psutil_percent >= threshold
-        true_triggered = true_percent >= threshold
-        print(f"  - {name} Threshold ({threshold}%):")
-        print(f"    PSUtil: {'TRIGGERED' if psutil_triggered else 'OK'}")
-        print(f"    Platform-Aware: {'TRIGGERED' if true_triggered else 'OK'}")
-        if psutil_triggered != true_triggered:
-            print(f"    → Difference: Platform-aware prevents false {'pressure' if psutil_triggered else 'recovery'}")
-    print()
-    
-    # Monitor for a few seconds
-    print("Monitoring memory for 10 seconds...")
-    for i in range(10):
-        vm = psutil.virtual_memory()
-        true_pct = get_true_memory_usage_percent()
-        print(f"  {i+1}s - PSUtil: {vm.percent:.1f}% | Platform-Aware: {true_pct:.1f}%", end="\r")
-        time.sleep(1)
-    print("\n")
-
-
-if __name__ == "__main__":
-    test_memory_calculation()
--- a/tests/test_multi_config.py
+++ b/tests/test_multi_config.py
@@ -1,117 +0,0 @@
-"""
-Test example for multiple crawler configs feature
-"""
-import asyncio
-import sys
-from pathlib import Path
-
-# Add parent directory to path for imports
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, MatchMode, CacheMode
-
-async def test_multi_config():
-    # Create different configs for different URL patterns
-    
-    # Config for PDF files
-    pdf_config = CrawlerRunConfig(
-        url_matcher="*.pdf",
-    )
-    
-    # Config for articles (using multiple patterns with OR logic)
-    article_config = CrawlerRunConfig(
-        url_matcher=["*/news/*", "*blog*", "*/article/*"],
-        match_mode=MatchMode.OR,
-        screenshot=True,
-    )
-    
-    # Config using custom matcher function
-    api_config = CrawlerRunConfig(
-        url_matcher=lambda url: 'api' in url or 'json' in url,
-    )
-    
-    # Config combining patterns and functions with AND logic
-    secure_docs_config = CrawlerRunConfig(
-        url_matcher=[
-            "*.doc*",  # Matches .doc, .docx
-            lambda url: url.startswith('https://')  # Must be HTTPS
-        ],
-        match_mode=MatchMode.AND,
-    )
-    
-    # Default config (no url_matcher means it won't match anything unless it's the fallback)
-    default_config = CrawlerRunConfig(
-        # cache_mode=CacheMode.BYPASS,
-    )
-    
-    # List of configs - order matters! First match wins
-    configs = [
-        pdf_config,
-        article_config, 
-        api_config,
-        secure_docs_config,
-        default_config  # Fallback
-    ]
-    
-    # Test URLs - using real URLs that exist
-    test_urls = [
-        "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf",  # Real PDF
-        "https://www.bbc.com/news/articles/c5y3e3glnldo",  # News article
-        "https://blog.python.org/",  # Blog URL  
-        "https://api.github.com/users/github",  # GitHub API (returns JSON)
-        "https://httpbin.org/json",  # API endpoint that returns JSON
-        "https://www.python.org/",  # Generic HTTPS page
-        "http://info.cern.ch/",  # HTTP (not HTTPS) page
-        "https://example.com/",  # → Default config
-    ]
-    
-    # Test the matching logic
-    print("Config matching test:")
-    print("-" * 50)
-    for url in test_urls:
-        for i, config in enumerate(configs):
-            if config.is_match(url):
-                print(f"{url} -> Config {i} matches")
-                break
-        else:
-            print(f"{url} -> No match, will use fallback (first config)")
-    
-    print("\n" + "=" * 50 + "\n")
-    
-    # Now test with actual crawler
-    async with AsyncWebCrawler() as crawler:
-        # Single config - traditional usage still works
-        print("Test 1: Single config (backwards compatible)")
-        result = await crawler.arun_many(
-            urls=["https://www.python.org/"],
-            config=default_config
-        )
-        print(f"Crawled {len(result)} URLs with single config\n")
-        
-        # Multiple configs - new feature
-        print("Test 2: Multiple configs")
-        # Just test with 2 URLs to avoid timeout
-        results = await crawler.arun_many(
-            urls=test_urls[:2],  # Just test first 2 URLs
-            config=configs  # Pass list of configs
-        )
-        print(f"Crawled {len(results)} URLs with multiple configs")
-        
-        # Using custom matcher inline
-        print("\nTest 3: Inline custom matcher")
-        custom_config = CrawlerRunConfig(
-            url_matcher=lambda url: len(url) > 50 and 'python' in url.lower(),
-            verbose=False
-        )
-        results = await crawler.arun_many(
-            urls=[
-                "https://docs.python.org/3/library/asyncio.html",  # Long URL with 'python'
-                "https://python.org/",  # Short URL with 'python' - won't match
-                "https://www.google.com/"  # No 'python' - won't match
-            ],
-            config=[custom_config, default_config]
-        )
-        print(f"Crawled {len(results)} URLs with custom matcher")
-
-if __name__ == "__main__":
-    asyncio.run(test_multi_config())