Mini-RAG

by John Wheatley
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Description

Category: Learning & Knowledge Management

The Mini-RAG plugin enables local retrieval augmented generation by connecting your notes to a locally running LLM through Ollama. You can start a chat in the context of a specific note or folder, allowing the model to reference only relevant content when generating responses. It supports any Ollama-installed model and provides controls for model selection, temperature adjustment, and even context-free chatting when you want unconstrained responses. Interactions can be initiated directly from right-click menus in the editor or sidebar, and conversations can be saved for later reference.

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323
days
23
days
23
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RequirementsExperimental

  • Ollama installed and running locally

Latest Version

23 days ago

Changelog

Mini-RAG v2.0.1 Release Notes

Features

  • Change model mid-chat

Patches

  • Support fallback to V1 behavior, when generating embeddings not supported by local model
  • Fix embedding model not found error

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Full Changelog: https://github.com/jjwheatley/mini-rag/compare/2.0.1...2.1.0

README file from

Github

Mini-RAG

Local Retrieval Augmented Generation for your Obsidian notes


What is Mini-RAG?

Mini-RAG lets you chat with a locally running LLM, in the context of selected Obsidian notes and folders. When you open a chat with a note or folder, Mini-RAG chunks the content into excerpts, generates vector embeddings for each chunk, and retrieves the most semantically relevant excerpts to include with each query. For the LLM, you can select any locally installed Ollama model (see: Configure Mini-RAG).

Setting Up Mini-RAG

Install Ollama

If you don't already have Ollama installed, you can download and install Ollama here.

This is necessary because Mini-RAG relies on a locally running instance of Ollama for its responses. This is the same reason that Mini-RAG is currently a desktop-only plugin.

Configure Mini-RAG

Open "options" by clicking on the gear icon then navigate to Community Plugins > Mini-RAG > Options. Here you can set the:

  • Ollama URL: If left unset, Ollama's default URL is used. The model list refreshes automatically when you change this.
  • Chat Model: Dropdown list of models installed in your local Ollama setup. Use the refresh button to reload the list.
  • Temperature: Higher temperatures give more creative responses; lower values give more focused and consistent ones.
  • Retrieved chunks (top-K): How many note excerpts are injected into each query (1–10). Higher values give the model more context but increase prompt size.
  • Enable context-free chats: Provides the option to chat with an LLM without the context of a note or folder.
  • Use a dedicated embedding model: When enabled, a separate Ollama model is used to generate embeddings instead of the chat model. Recommended if you want higher retrieval quality. If the selected embedding model is not yet installed, the settings panel shows the ollama pull <model> command to install it.

Using Mini-RAG

Opening a Mini-RAG Chat

You can open a chat from the right-click context menu, or via the Command Palette (Ctrl/Cmd+P → "Mini-RAG: Open chat panel"). You will see the Mini-RAG menu option when you:

  • Right-Click within a note
  • Right-Click a note in the sidebar
  • Right-Click a folder in the sidebar
  • Open a note's triple-dot menu

Responses

Responses stream in token-by-token as the model generates them. This is by design, to give a more responsive feel to the behaviour.

Copying Messages

Click any chat bubble (yours or the model's) to copy its text to the clipboard.

Saving Conversations

To save a Mini-RAG conversation, click the Save (disk) icon. If you continue the conversation after saving, click Save again to update the file.

To save under a custom name, click the chevron (▾) next to the Save button and choose Save as…

Summarizing

When a chat has context (opened from a file or folder), a Summarize (sparkles) button appears. Click it to ask the model to summarize the context file.


Privacy & Permissions

Network Usage

Mini-RAG communicates exclusively with your locally-running Ollama server (default: http://localhost:11434). No data is sent to any external server — all requests stay on your machine.

Clipboard Access

Mini-RAG writes to the clipboard when you click a Copy button (e.g. to copy a chat message, or to copy an ollama pull command from the settings panel). It never reads clipboard content.


Author

For more about the author visit JJWheatley.com

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