Docs RAG FAQs

Question 1

What types of documents can Docs RAG handle?

Accepted Answer

Docs RAG can process Git repositories (cloned directories) and plain text files (.txt extension) stored in a local directory. It uses llama-index with Google's Gemini embeddings for indexing.

Question 2

How do I query my documents after adding them?

Accepted Answer

Use the `rag_query` tool, providing the document ID and your query. The tool returns AI-generated responses based on the context retrieved from the specified document.

Question 3

What is Docs RAG?

Accepted Answer

Docs RAG is a tool that enables you to query your local documents (like Git repositories and text files) using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).

Question 4

How do I add documents to Docs RAG?

Accepted Answer

You can add Git repositories using the `add_git_repository` tool (specifying the repository URL, optional name, and subdirectory) or text files using the `add_text_file` tool (providing the file URL).

Question 5

What tools are available in Docs RAG?

Accepted Answer

Docs RAG provides tools such as `list_documents` to list available documents, `rag_query` to query documents using RAG, `add_git_repository` to add Git repositories, and `add_text_file` to add text files.

Docs RAG

主要功能

使用案例

Docs RAG

主要功能

使用案例