RAG FAQs

Question 1

What are the benefits of using RAG for document management?

Accepted Answer

RAG automates the traditionally manual process of PDF indexing, provides efficient semantic search, and offers intelligent re-indexing to keep your document corpus up-to-date with minimal effort, all within isolated spaces.

Question 2

Does RAG support multiple separate projects or spaces?

Accepted Answer

Yes, RAG ensures per-space state isolation. Each `agentil-agent` space gets its own dedicated document index and metadata, preventing conflicts and maintaining project separation.

Question 3

What kind of search capabilities does RAG offer?

Accepted Answer

RAG provides powerful semantic search over indexed documents, allowing you to find content based on meaning rather than just keywords. You can configure the number of top-k results returned.

Question 4

What is RAG and its primary function?

Accepted Answer

RAG (Retrieval Augmented Generation) is an MCP server designed for semantic search and document retrieval. Its primary function is to automatically index PDF files within designated `agentil-agent` spaces.

Question 5

How does RAG manage document indexing?

Accepted Answer

RAG automatically scans the `documents/` directory within an `agentil-agent` space. It intelligently re-indexes only new or changed PDF files, storing them in a dedicated per-space index.

RAG

主要功能

使用案例

RAG

主要功能

使用案例