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https://github.com/n8n-io/self-hosted-ai-starter-kit
The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.
https://github.com/n8n-io/self-hosted-ai-starter-kit
ai ai-agents low-code self-hosted starter-kit
Last synced: 2 months ago
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The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.
- Host: GitHub
- URL: https://github.com/n8n-io/self-hosted-ai-starter-kit
- Owner: n8n-io
- License: apache-2.0
- Created: 2024-02-23T13:56:32.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-21T08:54:29.000Z (3 months ago)
- Last Synced: 2024-08-21T18:02:51.546Z (3 months ago)
- Topics: ai, ai-agents, low-code, self-hosted, starter-kit
- Homepage: https://n8n.io
- Size: 3.81 MB
- Stars: 85
- Watchers: 8
- Forks: 12
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Self-hosted AI starter kit
**Self-hosted AI Starter Kit** is an open, docker compose template that
quickly bootstraps a fully featured Local AI and Low Code development
environment.
Curated by , it combines the self-hosted n8n
platform with a curated list of compatible AI products and components to
quickly get started with building self-hosted AI workflows.
> [!TIP]
> [Read the announcement](https://blog.n8n.io/self-hosted-ai/)
### What’s included
✅ [**Self-hosted n8n**](https://n8n.io/) - Low-code platform with over 400
integrations and advanced AI components
✅ [**Ollama**](https://ollama.com/) - Cross-platform LLM platform to install
and run the latest local LLMs
✅ [**Qdrant**](https://qdrant.tech/) - Open-source, high performance vector
store with an comprehensive API
✅ [**PostgreSQL**](https://www.postgresql.org/) - Workhorse of the Data
Engineering world, handles large amounts of data safely.
### What you can build
⭐️ AI Agents which can schedule appointments
⭐️ Summarise company PDFs without leaking data
⭐️ Smarter slack bots for company comms and IT-ops
⭐️ Analyse financial documents privately and for little cost
## Installation
### For Nvidia GPU users
```
git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
docker compose --profile gpu-nvidia up
```
### For everyone else
```
git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git
cd self-hosted-ai-starter-kit
docker compose --profile cpu up
```
> [!TIP]
> If you’re using a Mac with an M1 or newer processor, you can run Ollama on
> your host machine for faster GPU inference. Unfortunately, you can’t expose
> the GPU to Docker instances. Check the
> [Ollama homepage](https://ollama.com/) for installation instructions, and
> use `http://host.docker.internal:11434/` as the Ollama host in your
> credentials.
## ⚡️ Quick start and usage
The main component of the self-hosted AI starter kit is a docker compose file
pre-configured with network and disk so there isn’t much else you need to
install. After completing the installation steps above, follow the steps below
to get started.
1. Open in your browser to set up n8n. You’ll only
have to do this once.
2. Open the included workflow:
3. Select **Test workflow** to start running the workflow.
4. If this is the first time you’re running the workflow, you may need to wait
until Ollama finishes downloading Llama3.1. You can inspect the docker
console logs to check on the progress.
To open n8n at any time, visit in your browser.
With your n8n instance, you’ll have access to over 400 integrations and a
suite of basic and advanced AI nodes such as
[AI Agent](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/),
[Text classifier](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.text-classifier/),
and [Information Extractor](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor/)
nodes. To keep everything local, just remember to use the Ollama node for your
language model and Qdrant as your vector store.
> [!NOTE]
> This starter kit is designed to help you get started with self-hosted AI
> workflows. While it’s not fully optimized for production environments, it
> combines robust components that work well together for proof-of-concept
> projects. You can customize it to meet your specific needs
## Upgrading
### For Nvidia GPU users
```
docker compose --profile gpu-nvidia pull
docker compose create && docker compose up
```
### For everyone else
```
docker compose --profile cpu pull
docker compose create && docker compose up
```
## 👓 Recommended reading
n8n is full of useful content for getting started quickly with its AI concepts
and nodes. If you run into an issue, go to [support](#support).
- [AI agents for developers: from theory to practice with n8n](https://blog.n8n.io/ai-agents/)
- [Tutorial: Build an AI workflow in n8n](https://docs.n8n.io/advanced-ai/intro-tutorial/)
- [Langchain Concepts in n8n](https://docs.n8n.io/advanced-ai/langchain/langchain-n8n/)
- [Demonstration of key differences between agents and chains](https://docs.n8n.io/advanced-ai/examples/agent-chain-comparison/)
- [What are vector databases?](https://docs.n8n.io/advanced-ai/examples/understand-vector-databases/)
## 🎥 Video walkthrough
- [Installing and using Local AI for n8n](https://www.youtube.com/watch?v=xz_X2N-hPg0)
## 🛍️ More AI templates
For more AI workflow ideas, visit the [**official n8n AI template
gallery**](https://n8n.io/workflows/?categories=AI). From each workflow,
select the **Use workflow** button to automatically import the workflow into
your local n8n instance.
### Learn AI key concepts
- [AI Agent Chat](https://n8n.io/workflows/1954-ai-agent-chat/)
- [AI chat with any data source (using the n8n workflow too)](https://n8n.io/workflows/2026-ai-chat-with-any-data-source-using-the-n8n-workflow-tool/)
- [Chat with OpenAI Assistant (by adding a memory)](https://n8n.io/workflows/2098-chat-with-openai-assistant-by-adding-a-memory/)
- [Use an open-source LLM (via HuggingFace)](https://n8n.io/workflows/1980-use-an-open-source-llm-via-huggingface/)
- [Chat with PDF docs using AI (quoting sources)](https://n8n.io/workflows/2165-chat-with-pdf-docs-using-ai-quoting-sources/)
- [AI agent that can scrape webpages](https://n8n.io/workflows/2006-ai-agent-that-can-scrape-webpages/)
### Local AI templates
- [Tax Code Assistant](https://n8n.io/workflows/2341-build-a-tax-code-assistant-with-qdrant-mistralai-and-openai/)
- [Breakdown Documents into Study Notes with MistralAI and Qdrant](https://n8n.io/workflows/2339-breakdown-documents-into-study-notes-using-templating-mistralai-and-qdrant/)
- [Financial Documents Assistant using Qdrant and](https://n8n.io/workflows/2335-build-a-financial-documents-assistant-using-qdrant-and-mistralai/) [Mistral.ai](http://mistral.ai/)
- [Recipe Recommendations with Qdrant and Mistral](https://n8n.io/workflows/2333-recipe-recommendations-with-qdrant-and-mistral/)
## Tips & tricks
### Accessing local files
The self-hosted AI starter kit will create a shared folder (by default,
located in the same directory) which is mounted to the n8n container and
allows n8n to access files on disk. This folder within the n8n container is
located at `/data/shared` -- this is the path you’ll need to use in nodes that
interact with the local filesystem.
**Nodes that interact with the local filesystem**
- [Read/Write Files from Disk](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.filesreadwrite/)
- [Local File Trigger](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.localfiletrigger/)
- [Execute Command](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.executecommand/)
## 📜 License
This project is licensed under the Apache License 2.0 - see the
[LICENSE](LICENSE) file for details.
## 💬 Support
Join the conversation in the [n8n Forum](https://community.n8n.io/), where you
can:
- **Share Your Work**: Show off what you’ve built with n8n and inspire others
in the community.
- **Ask Questions**: Whether you’re just getting started or you’re a seasoned
pro, the community and our team are ready to support with any challenges.
- **Propose Ideas**: Have an idea for a feature or improvement? Let us know!
We’re always eager to hear what you’d like to see next.