Add blog: In-context search

[wangxingjun778]

• New Blog Post on RAG Evolution: Introduced a new blog post analyzing the technical evolution of Retrieval-Augmented Generation (RAG) systems towards In-Context Search (ICS).
• Comparison of ICS Paradigms: Compared traditional RAG (LightRAG) with two advanced ICS paradigms: PageIndex (hierarchical structural reasoning) and Sirchmunk (statistical agility and self-evolution).
• Shift to LLM-Native Reasoning: Explored the fundamental shift from index-centric retrieval to LLM-native reasoning within the context window.
• Challenges and Future Directions: Discussed critical challenges in ICS, such as token scalability, computational latency, and evaluation complexity, along with future research directions.
• Chinese Translation Provided: Provided a Chinese translation of the blog post to reach a broader audience.

[gemini-code-assist]

Summary of Changes

Hello @wangxingjun778, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request adds a new blog post that thoroughly examines the progression of Retrieval-Augmented Generation (RAG) systems, emphasizing the transition to In-Context Search (ICS). It contrasts established RAG methods with innovative ICS frameworks like PageIndex and Sirchmunk, detailing their architectural philosophies, mechanisms, and implications. The post also addresses the current limitations and future directions of ICS, offering valuable insights into the evolving landscape of LLM-native architectures.

Highlights

• New Blog Post on RAG Evolution: Introduced a new blog post analyzing the technical evolution of Retrieval-Augmented Generation (RAG) systems towards In-Context Search (ICS).
• Comparison of ICS Paradigms: Compared traditional RAG (LightRAG) with two advanced ICS paradigms: PageIndex (hierarchical structural reasoning) and Sirchmunk (statistical agility and self-evolution).
• Shift to LLM-Native Reasoning: Explored the fundamental shift from index-centric retrieval to LLM-native reasoning within the context window.
• Challenges and Future Directions: Discussed critical challenges in ICS, such as token scalability, computational latency, and evaluation complexity, along with future research directions.
• Chinese Translation Provided: Provided a Chinese translation of the blog post to reach a broader audience.

🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console.

Changelog

• content/blog/in-context-search/index.md
  • Added a new blog post titled "From Index-Centric Retrieval to In-Context Reasoning: The Technical Evolution of RAG Systems", detailing the shift from traditional RAG to In-Context Search (ICS) and comparing different ICS paradigms.
• content/blog/in-context-search/index.zh.md
  • Added a Chinese translation of the blog post "From Index-Centric Retrieval to In-Context Reasoning: The Technical Evolution of RAG Systems".

Activity

• No human activity has been recorded on this pull request yet.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[gemini-code-assist]

Code Review

This pull request adds a new blog post about the evolution of RAG systems, provided in both English and Chinese. The content is well-structured and detailed. I've identified a couple of minor issues in the markdown files that could be improved for clarity and correctness. Specifically, there's a placeholder author name that should be updated and a minor inconsistency in the section numbering in the Chinese version of the post.

[gemini-code-assist]

The author is listed as me. This appears to be a placeholder and should be updated to the actual author's name or handle for proper attribution.

Suggested change

	- me
	- Your Name

[gemini-code-assist]

The author is listed as me. This appears to be a placeholder and should be updated to the actual author's name or handle for proper attribution.

Suggested change

	- me
	- 您的名字

[gemini-code-assist]

The section numbering is inconsistent. This section is numbered 5., but the previous section is 3.4 and the following one is 4.1. This should be corrected to 4. to maintain logical flow.

Suggested change

	## 5. 挑战与未来研究方向
	## 4. 挑战与未来研究方向