docs: add v0.7.4 release blog post and update documentation
- Add comprehensive v0.7.4 release blog post with LLMTableExtraction feature highlight - Update blog index to feature v0.7.4 as latest release - Update README.md to showcase v0.7.4 features alongside v0.7.3 - Accurately describe dispatcher fix as bug fix rather than major enhancement - Include practical code examples for new LLMTableExtraction capabilities
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README.md
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README.md
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Crawl4AI turns the web into clean, LLM ready Markdown for RAG, agents, and data pipelines. Fast, controllable, battle tested by a 50k+ star community.
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[✨ Check out latest update v0.7.3](#-recent-updates)
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[✨ Check out latest update v0.7.4](#-recent-updates)
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✨ New in v0.7.3: Undetected Browser Support, Multi-URL Configurations, Memory Monitoring, Enhanced Table Extraction, GitHub Sponsors. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.3.md)
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✨ New in v0.7.4: Revolutionary LLM Table Extraction with intelligent chunking, enhanced concurrency fixes, memory management refactor, and critical stability improvements. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.4.md)
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✨ Recent v0.7.3: Undetected Browser Support, Multi-URL Configurations, Memory Monitoring, Enhanced Table Extraction, GitHub Sponsors. [Release notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.3.md)
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<details>
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<summary>🤓 <strong>My Personal Story</strong></summary>
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## ✨ Recent Updates
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<details>
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<summary><strong>Version 0.7.4 Release Highlights - The Intelligent Table Extraction & Performance Update</strong></summary>
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- **🚀 LLMTableExtraction**: Revolutionary table extraction with intelligent chunking for massive tables:
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```python
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from crawl4ai import LLMTableExtraction, LLMConfig
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# Configure intelligent table extraction
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table_strategy = LLMTableExtraction(
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llm_config=LLMConfig(provider="openai/gpt-4.1-mini"),
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enable_chunking=True, # Handle massive tables
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chunk_token_threshold=5000, # Smart chunking threshold
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overlap_threshold=100, # Maintain context between chunks
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extraction_type="structured" # Get structured data output
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)
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config = CrawlerRunConfig(table_extraction_strategy=table_strategy)
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result = await crawler.arun("https://complex-tables-site.com", config=config)
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# Tables are automatically chunked, processed, and merged
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for table in result.tables:
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print(f"Extracted table: {len(table['data'])} rows")
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```
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- **⚡ Dispatcher Bug Fix**: Fixed sequential processing bottleneck in arun_many for fast-completing tasks
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- **🧹 Memory Management Refactor**: Consolidated memory utilities into main utils module for cleaner architecture
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- **🔧 Browser Manager Fixes**: Resolved race conditions in concurrent page creation with thread-safe locking
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- **🔗 Advanced URL Processing**: Better handling of raw:// URLs and base tag link resolution
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- **🛡️ Enhanced Proxy Support**: Flexible proxy configuration supporting both dict and string formats
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[Full v0.7.4 Release Notes →](https://github.com/unclecode/crawl4ai/blob/main/docs/blog/release-v0.7.4.md)
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</details>
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<details>
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<summary><strong>Version 0.7.3 Release Highlights - The Multi-Config Intelligence Update</strong></summary>
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