[New Plugin] Neural Composer: Local Graph RAG made easy (LightRAG integration)

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TL;DR

I built Neural Composer because standard vector search plugins weren’t connecting the dots in my vault. It integrates LightRAG (a specific “flavor” of Graph RAG, faster and efficient) directly into Obsidian to give you answers based on relationships, not just keywords. It automatically manages a local LightRAG server for you (starts/stops with Obsidian), supports PDFs/DOCX, (and many others), and offers a hybrid search mode. Free and open source.

The “Why”

Hi everyone! :waving_hand:

I’ve been using Obsidian for years to manage engineering projects, research, and personal journal. Like many of you, I hit a wall: my vault grew huge, and finding specific notes was easy, but synthesizing concepts across different notes was hard.

I tried a Smart Composer plugin, which uses RAG (Retrieval Augmented Generation), and I used a lot. It is great, but rely on simple vector search. If I asked: “How does the methodology in Paper A contradict the results in Project B?”, the AI often failed because the text chunks weren’t mathematically similar, even though they were logically connected.

Recently I read about LightRAG and Knowledge Graphs and realized that was the missing piece. I wanted a graph that could “traverse” my notes to find those hidden connections.

What I Built

I’m an engineer, so I decided to build a solution (with the heavy assistance of my AI co-pilot). I forked the UI of Smart Composer (credits to glowingjade for the amazing base!) and completely re-engineered the backend.

“Neural Composer” is the result. It’s a client for running a local LightRAG server that:

  1. Builds a Knowledge Graph of your vault (Entities + Relationships).
  2. Manages the Server: I didn’t want to open a terminal every time I wanted to chat with my notes. The plugin auto-starts the LightRAG server when Obsidian opens and kills it when you close the app.
  3. Hybrid Retrieval: It combines local file reading (for precision) with global graph queries (for synthesis).

Who is this for?

I built this for my own needs, but I think it fits well if you are:

  • A Researcher: Trying to synthesize literature reviews from a lot of PDFs.
  • A DM/Writer: Needing to track complex lore and character relationships without manual wikis.
  • Privacy Conscious: You can run this 100% locally with Ollama if you have the hardware (I use it with a RTX 2070 and it flies).

How to try it

It requires a bit of setup (installing Python and the library), but I tried to make the rest as “plug-and-play” as possible.

  1. pip install "lightrag-hku[api]"
  2. Install Neural Composer (Manual install from GitHub releases for now. Also you can use BRAT).
  3. Point the plugin to your lightrag-server.exe file.
  4. Right-click your notes folder → “:brain: Ingest into Graph”.

It’s open source. I’m not selling anything, just sharing a tool that solved a big headache for me.

:backhand_index_pointing_right: Repository & Download: https://github.com/oscampo/obsidian-neural-composer

I’d love to hear if this helps your workflow or if you find any bugs (it’s a v1.0, so be gentle!).

Happy connecting! Oscar.