# Sync documentation vectors from GitHub with Ollama and Qdrant: n8n workflow

> Started by a clock, and works across Qdrant. 14 steps: a working afternoon to understand properly.

Source: https://millionrounds.com/workflow/sync-documentation-vectors-from-github-with-ollama-and-qdran (Millionrounds; every figure on the page links to its filing or article)

[Automation library](https://millionrounds.com/workflows) · [Documents and files](https://millionrounds.com/workflows?category=Documents+and+files#library)

# Sync documentation vectors from GitHub with Ollama and Qdrant

Started by a clock, and works across Qdrant. 14 steps: a working afternoon to understand properly.

Medium Retrieval

[Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fsync-documentation-vectors-from-github-with-ollama-and-qdran)

**14 steps** Medium: a working afternoon

**0** Branches: places the flow splits

**0** Loops or waits

**1** Service it connects to

## The flow

Starts it 1 Model 3 Logic 4 Service 6

The steps in the order they run, from what starts it.

- 1 **Embeddings Ollama** Embeddings Ollama *Model*
- 2 **Schedule Trigger** Schedule trigger *Starts it*
- 3 **Default Data Loader** Document Default Data Loader *Model*
- 4 **Qdrant Vector Store** Vector Store Qdrant *Model*
- 5 **Fetch Latest Commit SHA** Http Request *Service*
- 6 **Prepare State Payload** Code *Logic*
- 7 **Fetch Qdrant State SHA** Http Request *Service*
- 8 **Write n8n Docs SHA** Http Request *Service*
- 9 **Check Commit SHA Change** Code *Logic*
- 10 **Delete n8n Docs Qdrant Vector Store** Http Request *Service*
- 11 **Fetch n8n Docs Tree** Http Request *Service*
- 12 **Parse Doc File List** Code *Logic*
- 13 **Fetch Raw Markdown** Http Request *Service*
- 14 **Markdown Section Chunker** Code *Logic*

## How it's built

- **Starts on:** A clock
- **Steps:** 14
- **Size:** Medium: a working afternoon
- **Connects to:** Qdrant
- **Model:** None. This is plumbing, not judgement
- **Retrieval:** Answers are drawn from documents you supply, not from the model alone

## Questions

What does it need to run?

An n8n account, plus your own Qdrant account. You connect your own accounts after importing it; none are included.

What starts it?

It starts on a clock.

Does it use AI?

No. Every step is fixed logic or a call to a service, so it does the same thing every time.

How long does it take to set up?

Plan an afternoon. 14 steps is enough that you should read each one before running it.

How do I import it?

Copy the workflow, open a new workflow in n8n and paste. The steps appear on the canvas, ready for your own accounts.

**Before you run it**

Nothing here has been tested by us. It is somebody's working automation, read and described from its own steps. Treat the connections it wants as a list of accounts it will touch, and read the 14 steps before you point it at anything that matters.

## Run it in n8n

- **Create your n8n account** Free to start. n8n is where the workflow runs. [Create an n8n account ↗](https://millionrounds.com/n8n)
- **Download the workflow** Free with a Millionrounds account. [Download free](https://millionrounds.com/login?next=%2Fapp%2Fworkflow%2Fsync-documentation-vectors-from-github-with-ollama-and-qdran)
- **Paste it into n8n** Open a new workflow in n8n and paste. Then connect your own accounts.

Stored with the author's traces removed: canvas notes, instance identifiers, saved credential names and any live document they had left behind.

## Connects to

Each opens the other workflows that use it.

[Qdrant](https://millionrounds.com/workflows?service=Qdrant#library)

## Workflows like it

Also documents and files, with the same services where possible, closest in size first.

- [**Index and query financial documents with Qdrant and Mistral** 16 steps · Qdrant](https://millionrounds.com/workflow/index-and-query-financial-documents-with-qdrant-and-mistral)
- [**Automated document compliance validation with a local model** 17 steps · calls a model · Qdrant](https://millionrounds.com/workflow/automated-document-compliance-validation-with-a-local-model)
- [**Build a document-based AI chatbot with Google Drive and Llama** 11 steps · calls a model · Google Drive, Qdrant](https://millionrounds.com/workflow/build-a-document-based-ai-chatbot-with-google-drive-and-llam)
- [**Filter by keyword within given documents with OpenAI** 18 steps · calls a model · Qdrant](https://millionrounds.com/workflow/filter-by-keyword-within-given-documents-with-openai)
- [**Index local documents for RAG with Ollama and Qdrant** 7 steps · Qdrant](https://millionrounds.com/workflow/index-local-documents-for-rag-with-ollama-and-qdrant)
- [**Build a financial documents assistant with Qdrant and Mistral** 23 steps · calls a model · Qdrant](https://millionrounds.com/workflow/build-a-financial-documents-assistant-with-qdrant-and-mistra)