Hexo Blog RAG FAQs

Question 1

What is Hexo Blog RAG and how does it work?

Accepted Answer

Hexo Blog RAG transforms your Hexo blog into a personalized knowledge base for large language models (LLMs). It uses vector-based semantic search via the Model Context Protocol (MCP), allowing AI assistants to directly access and semantically search your blog content.

Question 2

How can Hexo Blog RAG enhance my interactions with AI assistants?

Accepted Answer

By providing AI assistants with direct access to your blog's content, Hexo Blog RAG enables them to offer more accurate, context-rich, and personalized answers relevant to your specific knowledge base, whether for technical questions, learning, or content creation.

Question 3

What are the main benefits of using Hexo Blog RAG for my blog?

Accepted Answer

Key benefits include knowledge reuse, personalized AI answers based on your unique content, instant retrieval of information, and privacy control as your data is stored locally. It turns your accumulated blog posts into an active, AI-accessible resource.

Question 4

Can I choose which embedding model to use with Hexo Blog RAG?

Accepted Answer

Yes, Hexo Blog RAG supports multiple embedding models to suit your needs, including a simple hash-based method, OpenAI, and Qwen, giving you flexibility in how your content is vectorized for search.

Question 5

How does Hexo Blog RAG handle updates to my blog content?

Accepted Answer

It features incremental indexing based on file hashes and real-time file monitoring. This means your knowledge base automatically and efficiently updates whenever you add, modify, or delete posts in your Hexo blog's source directory.

Hexo Blog RAG

Hexo Blog RAG

About

Key Features

Use Cases

About

Key Features

Use Cases