LLM-Wiki-for-n8n/templates/SUBMISSION.md

n8n Template Submission — LLM Wiki

Workflow file to submit: workflows/LLM_wiki.en.json

Submit at: https://n8n.io/creators/ → Submit a workflow (you must be signed in to your n8n.io creator account).

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Title

LLM Wiki: pre-compiled RAG with an AI editor, using Google Docs & Sheets

Short description (one-liner)

A different take on RAG: instead of embedding-and-retrieve, an LLM acts as a "wiki editor" that reads, rewrites and cross-links your documents into a structured knowledge base — then answers questions by looking things up in an index, like a human would.

Full description

This workflow implements Andrej Karpathy's LLM Wiki idea in n8n, using tools everyone already has — Google Docs for the wiki pages and Google Sheets as the index. No vector database required.

The idea — "pre-compile" instead of "embed-and-retrieve"

Traditional RAG shreds your documents into chunks, embeds them, and at query time pulls a few chunks for the LLM to read. The model only ever sees those fragments — it has no global view.

LLM Wiki does the opposite. It pre-compiles your raw material: the LLM reads everything and, like a Wikipedia editor, organizes, rewrites and cross-links it into clean wiki pages. To find an answer it first consults an index (just like a person looking something up), then reads the relevant page. The result is a curated knowledge base, not an ever-growing knowledge warehouse — similar material gets updated into existing pages rather than piled up as new chunks.

	Classic vector RAG	LLM Wiki (this template)
Ingestion	chunk → embed → store vectors	LLM reads → rewrites → wiki page
Retrieval	vector similarity	look up the index
Growth	unbounded (warehouse)	curated, updated in place (library)
Source docs	shredded directly	kept as single source of truth

What's inside

The workflow has two independent flows:

1. Ingest (write). A form upload (.md / .txt) feeds an AI Agent ("knowledge-writing assistant"). It always reads the index first, splits the upload into topics, then for each topic either appends to an existing Google Doc and updates the index, or creates a new Doc and adds an index row.
2. Query (read). A chat trigger feeds an AI Agent ("knowledge-query assistant") that browses the index, picks the most relevant page(s), reads them, and answers — read-only, grounded in the wiki.

Tools used by the agents

• get_indexs — read the index sheet (topic, doc_id, keywords, summary)
• create_wiki_page — create a new Google Doc (via an HTTP call to a tiny companion sub-workflow, because the Docs node can't create a file directly inside a target folder)
• write_wiki / update_wiki — append/update a wiki Doc
• write_index — add a new index row
• read_wiki — read a wiki Doc's full text

Companion sub-workflow. This template needs a small second workflow (create_wiki_page) that creates a Doc and moves it into your wiki folder, exposed as a webhook. It's included in the GitHub repo linked below.

Setup

1. Import the workflow.
2. Create a Google Sheet for the index with columns: topic, doc_id, keywords, summary, last_updated. Point the get_indexs / write_index nodes at it (replace the YOUR_INDEX_SHEET_ID placeholder).
3. Import the companion create_wiki_page sub-workflow and set its target folder; put its webhook URL into the create_wiki_page HTTP node (replace YOUR-N8N-HOST/...).
4. Attach your own credentials to the Google Sheets / Docs nodes and your LLM node (this template uses Google Gemini; swap in any chat model).
5. Activate, upload a doc, then ask a question in the chat trigger.

Notes & credits

• This burns more tokens than vector RAG (the LLM actually reads and rewrites your material) — but the curation quality is the point.
• Concept by Andrej Karpathy (original gist). This template just swaps Obsidian for Google Docs + Sheets so anyone can run it.
• Full repo, the companion sub-workflow, a sample index and a sample wiki page: https://github.com/uncle6me-web/LLM-Wiki-for-n8n

Suggested categories / tags

AI, RAG, Agent, Google Docs, Google Sheets, Knowledge Base, Gemini

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Pre-submission checklist

• All user-facing strings translated to English
• Credentials removed (importers attach their own)
• Personal Sheet ID replaced with YOUR_INDEX_SHEET_ID
• Personal n8n webhook URL replaced with YOUR-N8N-HOST/...
• Instance metadata (id, versionId, webhookId, tags, pinData) cleared
• Companion create_wiki_page sub-workflow imported & its webhook URL filled in
• Tested end-to-end on your own n8n before submitting