Chat with local LLMs using n8n and Ollama
Engage in interactive conversations with local large language models (LLMs) running on Ollama. This workflow receives a chat message, passes it to the Ollama Chat Model, and returns the LLM's response. Developers can test local LLMs, researchers can experiment with model outputs, and individuals can explore AI capabilities without cloud dependencies. This saves time and resources by enabling local LLM interaction.
Workflow JSON
{"id": "af8RV5b2TWB2LclA", "meta": {"instanceId": "95f2ab28b3dabb8da5d47aa5145b95fe3845f47b20d6343dd5256b6a28ba8fab", "templateCredsSetupCompleted": true}, "name": "Chat with local LLMs using n8n and Ollama", "tags": [], "nodes": [{"id": "475385fa-28f3-45c4-bd1a-10dde79f74f2", "name": "When chat message received", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [700, 460], "webhookId": "ebdeba3f-6b4f-49f3-ba0a-8253dd226161", "parameters": {"options": {}}, "typeVersion": 1.1}, {"id": "61133dc6-dcd9-44ff-85f2-5d8cc2ce813e", "name": "Ollama Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOllama", "position": [900, 680], "parameters": {"options": {}}, "credentials": {"ollamaApi": {"id": "", "name": "[Your ollamaApi]"}}, "typeVersion": 1}, {"id": "3e89571f-7c87-44c6-8cfd-4903d5e1cdc5", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [160, 80], "parameters": {"width": 485, "height": 473, "content": "## Chat with local LLMs using n8n and Ollama\nThis n8n workflow allows you to seamlessly interact with your self-hosted Large Language Models (LLMs) through a user-friendly chat interface. By connecting to Ollama, a powerful tool for managing local LLMs, you can send prompts and receive AI-generated responses directly within n8n.\n\n### How it works\n1. When chat message received: Captures the user's input from the chat interface.\n2. Chat LLM Chain: Sends the input to the Ollama server and receives the AI-generated response.\n3. Delivers the LLM's response back to the chat interface.\n\n### Set up steps\n* Make sure Ollama is installed and running on your machine before executing this workflow.\n* Edit the Ollama address if different from the default.\n"}, "typeVersion": 1}, {"id": "9345cadf-a72e-4d3d-b9f0-d670744065fe", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [1040, 660], "parameters": {"color": 6, "width": 368, "height": 258, "content": "## Ollama setup\n* Connect to your local Ollama, usually on http://localhost:11434\n* If running in Docker, make sure that the n8n container has access to the host's network in order to connect to Ollama. You can do this by passing `--net=host` option when starting the n8n Docker container"}, "typeVersion": 1}, {"id": "eeffdd4e-6795-4ebc-84f7-87b5ac4167d9", "name": "Chat LLM Chain", "type": "@n8n/n8n-nodes-langchain.chainLlm", "position": [920, 460], "parameters": {}, "typeVersion": 1.4}], "active": false, "pinData": {}, "settings": {"executionOrder": "v1"}, "versionId": "3af03daa-e085-4774-8676-41578a4cba2d", "connections": {"Ollama Chat Model": {"ai_languageModel": [[{"node": "Chat LLM Chain", "type": "ai_languageModel", "index": 0}]]}, "When chat message received": {"main": [[{"node": "Chat LLM Chain", "type": "main", "index": 0}]]}}}How to Import This Workflow
- 1Copy the workflow JSON above using the Copy Workflow JSON button.
- 2Open your n8n instance and go to Workflows.
- 3Click Import from JSON and paste the copied workflow.
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