docs: add zhihu post

[e06084]

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[gemini-code-assist]

Summary of Changes

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This pull request expands the project's documentation and promotional content by introducing a new Chinese-language post for Zhihu, aimed at a broader audience. Concurrently, an existing English post for Reddit was significantly revised to offer a more detailed technical overview of the Dingo v2.1.0 evaluation framework, emphasizing its layered approach and RAG capabilities. These changes enhance the accessibility and depth of information available about the Dingo platform.

Highlights

• New Zhihu Post Added: A new documentation post for Zhihu, written in Chinese, has been added to detail Dingo v2.1.0 features, including its SaaS platform and core technical updates.
• Reddit Post Content Rewritten: The existing Reddit post has been completely rewritten to provide a more in-depth explanation of Dingo's layered evaluation architecture (Rule, LLM, VLM, Agent) and RAG capabilities, shifting its focus from a general release announcement to a technical deep-dive.
• Hacker News Post Update: The Hacker News post was modified to remove specific GitHub repository metadata (star count and license information) from the GitHub link.

Changelog

• docs/posts/v2.1.0_hacker_news.md
  • Removed star count and license information from the GitHub link.
• docs/posts/v2.1.0_reddit.md
  • Rewrote the entire post to focus on Dingo's layered evaluation architecture (Rule, LLM, VLM, Agent) and RAG evaluation, shifting from a general release announcement to a technical explanation.
• docs/posts/v2.1.0_zhihu.md
  • Added a new documentation file containing a detailed post in Chinese about Dingo v2.1.0, including its SaaS platform, core technical updates, and quick start guide.

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[gemini-code-assist]

Code Review

This pull request updates the documentation for the Dingo v2.1.0 release across different platforms. It refines the Hacker News post by removing specific star count and license details from the GitHub link. The Reddit post is completely rewritten from a formal release announcement to a more engaging, problem-solution-oriented discussion about automating data quality checks for LLM training data, highlighting a layered evaluation approach and agent-based fact-checking. Additionally, a new, comprehensive release announcement in Chinese is added for the Zhihu platform, detailing Dingo v2.1.0's features, SaaS platform, and core technical updates like the four-layer evaluation architecture and Agent-as-a-Judge.