LLM workspace

by Olivér Falvai
5
4
3
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Score: 43/100

Description

Category: Learning & Knowledge Management

The LLM workspace plugin for Obsidian is a powerful tool that allows users to integrate Large Language Models (LLMs) into their note-taking workflow. This plugin focuses on manually created source sets, which provides a more accurate and flexible way of integrating AI into Obsidian compared to traditional RAG setups. With LLM Workspace, users can create custom workspaces for each project or topic, and engage in conversations with the model while having granular control over prompts and responses. The plugin also supports multiple models and providers, making it easy to experiment with different AI models and fine-tune their performance. Overall, LLM Workspace is an innovative tool that enables users to tap into the power of AI for more efficient and effective note-taking and knowledge management.

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Stats

80
stars
2,033
downloads
9
forks
526
days
0
days
328
days
111
total PRs
13
open PRs
51
closed PRs
47
merged PRs
8
total issues
5
open issues
3
closed issues
183
commits

Latest Version

a year ago

Changelog

1.3.0 (2025-06-15)

Features

Chore

README file from

Github

LLM Workspace plugin for Obsidian

Quick demo

https://github.com/user-attachments/assets/3e5d7515-5d7c-47c8-bc98-9eafe43e2fa4

The workspace view opens side-by-side to the notes. Let's index all information in the workspace. Behind the scenes, this creates the typical RAG setup by chunking documents and computing embeddings for them:

https://github.com/user-attachments/assets/8a3c73f6-5789-4573-83a3-b8f9a07ec02f

We can start a conversation right away, but it's also possible to generate exploratory questions:

https://github.com/user-attachments/assets/3b82909e-128e-4d1b-a180-dd01e0e241a7

A conversation is always grounded in the workspace sources and you can debug RAG pipeline:

https://github.com/user-attachments/assets/488f79b1-d928-4249-8a01-e79de9f5997a

You can also chat with a single note (without creating a workspace) and attach more context gradually:

https://github.com/user-attachments/assets/2f4c4e88-81a1-4cda-ae05-b88a0988bd8c

Why have another AI plugin for Obsidian?

  • This plugin focuses on a specific way of AI integration: manually created source sets that an LLM chat is grounded in. It's both cheaper, faster, and more accurate than doing RAG over an entire vault (and we organize our notes anyway, right?!).
  • I wanted something that is flexible, configurable, tweakable. AI progresses too fast anyway, I have no idea what's going to be the best setup tomorrow.
  • Because it's always fun to build tools for my own needs!

Goals

  • Integrate LLMs into the Obsidian vault, not the other way around (copy-pasting snippets in and out of ChatGPT)
  • Enable granular control, tweaking and transparency: choose from multiple models and LLM providers, customize prompts, and debug responses.
  • Native to Obsidian, not just a ChatGPT clone inside the Obsidian window
  • Great UX, efficient multitasking.

Get started

This is a bring your own API key kind of integration. The first step is to add an API key in the plugin settings and choose a model.

This page details the supported LLM providers and the various details of each integration.

The main plugin panel can be launched from the context menu entries, but the following commands are also available:

  • Open active note as LLM workspace
  • Chat with active note
  • Open existing workspace
  • Open context panel

The following plugins work well together with LLM workspace and make the experience even better:

  • Folder notes: blurs the line between a folder and a note in the file tree. A note can have child notes like in Notion and similar tools. Combined with this plugin, an LLM workspace can be a folder with notes inside.
  • Waypoint: generates a table of contents with links to other notes. Combined with Folder notes and LLM workspace, it maintains links to notes in the LLM workspace folder.

Advanced use

Click here for a list of advanced features and use cases.

Current limitations

  • The plugin only handles Markdown files for now. There is no support for images, PDFs or canvases.
  • The chunking of notes is pretty naive and there is no token count validation (but models have huge context windows nowadays)

Additional details

  • This plugin makes network requests to external LLM APIs. You can view the API-related code here
  • You can review all LLM prompts here
  • The RAG implementation is here

Roadmap

  • Change models and model parameters mid-conversation
  • Tool use
  • Chat history
  • Better query understanding and planning
  • Footnotes in LLM response
  • More advanced ways for including notes in a workspace (Dataview integration maybe?)
  • API cost estimation before heavy actions

Prior work and inspiration

Built with

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