feat(README): update for v0.10.0 、

- Introduced hybrid OCR text extraction capabilities in v0.10.0
- Significantly improved parsing performance in complex text distribution scenarios- Combined advantages of accurate content extraction and faster speed in text mode with more precise span/line region recognition in OCR mode
- Updated both English and Chinese README files

README.md

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 # Changelog
+- 2024/11/22 0.10.0 released. Introducing hybrid OCR text extraction capabilities,
+  - Significantly improved parsing performance in complex text distribution scenarios such as dense formulas, irregular span regions, and text represented by images.
+  - Combines the dual advantages of accurate content extraction and faster speed in text mode, and more precise span/line region recognition in OCR mode.
 - 2024/11/15 0.9.3 released. Integrated [RapidTable](https://github.com/RapidAI/RapidTable) for table recognition, improving single-table parsing speed by more than 10 times, with higher accuracy and lower GPU memory usage.
 - 2024/11/06 0.9.2 released. Integrated the [StructTable-InternVL2-1B](https://huggingface.co/U4R/StructTable-InternVL2-1B) model for table recognition functionality.
 - 2024/10/31 0.9.0 released. This is a major new version with extensive code refactoring, addressing numerous issues, improving performance, reducing hardware requirements, and enhancing usability:

README_zh-CN.md

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 </div>
 
 # 更新记录
+- 2024/11/22 0.10.0发布，通过引入混合OCR文本提取能力，
+  - 在公式密集、span区域不规范、部分文本使用图像表现等复杂文本分布场景下获得解析效果的显著提升
+  - 同时具备文本模式内容提取准确、速度更快与OCR模式span/line区域识别更准的双重优势
 - 2024/11/15 0.9.3发布，为表格识别功能接入了[RapidTable](https://github.com/RapidAI/RapidTable),单表解析速度提升10倍以上，准确率更高，显存占用更低
 - 2024/11/06 0.9.2发布，为表格识别功能接入了[StructTable-InternVL2-1B](https://huggingface.co/U4R/StructTable-InternVL2-1B)模型
 - 2024/10/31 0.9.0发布，这是我们进行了大量代码重构的全新版本，解决了众多问题，提升了性能，降低了硬件需求，并提供了更丰富的易用性：