#+title: RAGs — Private Learning Tool
#+author: df
#+date: 2026-04-19

* Overview

Two local RAG systems for a private learning tool with Anki export.

| Project  | Purpose                                          |
|----------+--------------------------------------------------|
| LightRAG | Graph-based RAG — ingest docs, query concepts    |
| Graphiti | Temporal knowledge graph — track what you learned and when |

Both run fully local via Ollama. No cloud, no API keys.

* Prerequisites

** Ollama

Install Ollama and pull the required models:

#+begin_src sh
ollama pull qwen3:0.6b
ollama pull qwen3-embedding:0.6b
#+end_src

Ollama must be running before starting either service.

** Nix

Flakes must be enabled. Add to your NixOS config or =~/.config/nix/nix.conf=:

#+begin_src
experimental-features = nix-command flakes
#+end_src

* Usage

** LightRAG

Ingest documents and query them as a knowledge graph.

#+begin_src sh
nix develop .#lightrag
lightrag-server
#+end_src

Server runs at =http://localhost:9621=.

Configure in =.env.lightrag=. Default storage is =./lightrag/rag_storage/=.

** Graphiti

Temporal memory graph — tracks concepts and when you learned them.

Start Neo4j first (in a separate terminal):

#+begin_src sh
nix run .#neo4j-start
#+end_src

Then enter the shell:

#+begin_src sh
nix develop .#graphiti
#+end_src

Configure in =.env.graphiti=.

** Neo4j Management

#+begin_src sh
nix run .#neo4j-start   # start daemon
nix run .#neo4j-stop    # stop daemon
#+end_src

Data persists in =./data/neo4j/=. Web UI at =http://localhost:7474=.

* Configuration

** .env.lightrag

| Variable             | Default              | Notes                    |
|----------------------+----------------------+--------------------------|
| =LLM_BINDING=        | =ollama=             |                          |
| =LLM_MODEL=          | =qwen3:0.6b=             | Change to any Ollama model |
| =EMBEDDING_MODEL=    | =qwen3-embedding:0.6b=   |                          |
| =EMBEDDING_DIM=      | =1024=                   | Must match model         |
| =RAG_DIR=            | =./rag_storage=      | Where graph data lives   |
| =PORT=               | =9621=               |                          |

** .env.graphiti

| Variable          | Default                      | Notes                         |
|-------------------+------------------------------+-------------------------------|
| =NEO4J_URI=       | =bolt://localhost:7687=      |                               |
| =OPENAI_BASE_URL= | =http://localhost:11434/v1=  | Ollama OpenAI-compatible API  |
| =OPENAI_API_KEY=  | =ollama=                     | Dummy value, required by SDK  |
| =MODEL_NAME=      | =qwen3:0.6b=                 |                               |
| =EMBEDDING_MODEL= | =qwen3-embedding:0.6b=       |                               |
| =EMBEDDING_DIM=   | =1024=                       | Must match model              |

* Structure

#+begin_src
rags/
├── flake.nix          — Nix devShells and neo4j apps
├── flake.lock
├── .env.lightrag      — LightRAG runtime config
├── .env.graphiti      — Graphiti runtime config
├── lightrag/          — submodule: hkuds/lightrag
├── graphiti/          — submodule: getzep/graphiti
├── data/
│   └── neo4j/         — Neo4j data (gitignored)
└── docs/
    └── setup.org      — How this was set up
#+end_src

* Submodules

#+begin_src sh
git submodule update --init --recursive
#+end_src