🔐🦙🤖 Private & local Ollama self-hosted AI assistant
Transform your local N8N instance into a powerful chat interface using any local & private Ollama model, with zero cloud dependencies ☁️. This workflow creates a structured chat experience that processes messages locally through a language model chain and returns formatted responses 💬.
How it works 🔄
- 💭 Chat messages trigger the workflow
- 🧠 Messages are processed through Llama 3.2 via Ollama (or any other Ollama compatible model)
- 📊 Responses are formatted as structured JSON
- ⚡ Error handling ensures robust operation
Set up steps 🛠️
- 📥 Install N8N and Ollama
- ⚙️ Download Ollama 3.2 model (or other model)
- 🔑 Configure Ollama API credentials
- ✨ Import and activate workflow
This template provides a foundation for building AI-powered chat applications while maintaining full control over your data and infrastructure 🚀.
n8n Local Ollama Self-Hosted AI Assistant
This n8n workflow provides a basic framework for interacting with a self-hosted AI model via Ollama, triggered by a chat message. It demonstrates how to receive a chat input, process it with an Ollama-powered Large Language Model (LLM) chain, and potentially prepare the output for further actions.
What it does
This workflow automates the following steps:
- Listens for Chat Messages: It waits for incoming chat messages to trigger the workflow.
- Prepares Input (Optional): An "Edit Fields (Set)" node is included, which can be used to transform or prepare the incoming chat message before it's sent to the LLM.
- Processes with Ollama LLM: It uses a "Basic LLM Chain" node, configured with an "Ollama Model" node, to process the input chat message. This allows you to leverage a local, self-hosted AI model (like Llama 2, Mistral, etc., running via Ollama) to generate responses or perform AI tasks.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n instance: A running instance of n8n.
- Ollama Installation: Ollama must be installed and running on a server accessible by your n8n instance.
- Ollama Model: At least one AI model (e.g.,
llama2,mistral) must be pulled and running in Ollama. - n8n LangChain Nodes: Ensure the
@n8n/n8n-nodes-langchainpackage is installed in your n8n instance.
Setup/Usage
- Import the workflow:
- Copy the provided JSON code.
- In your n8n instance, go to "Workflows" and click "New".
- Click the three dots in the top right corner and select "Import from JSON".
- Paste the JSON code and click "Import".
- Configure the Ollama Model:
- Locate the "Ollama Model" node.
- Configure its settings to point to your running Ollama instance (e.g.,
http://localhost:11434if it's on the same machine) and specify the model you want to use (e.g.,llama2).
- Configure the Basic LLM Chain:
- Review the "Basic LLM Chain" node. You might want to adjust the prompt or other chain parameters depending on your desired AI assistant behavior.
- Activate the Workflow:
- Once configured, activate the workflow by toggling the "Active" switch in the top right corner of the workflow editor.
Now, when a chat message is received by the "When chat message received" trigger, it will be processed by your local Ollama AI model. You would typically extend this workflow to send the AI's response back to the chat platform or another service.
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