🗨️Ollama Chat
Engage in interactive conversations with a local large language model directly from your n8n workflows using the Ollama Chat template. This workflow automates the process of receiving a chat message, processing it with a foundational LLM chain, and generating a structured response from an Ollama model. When a chat message is received via the "When chat message received" trigger, the "Basic LLM Chain" node processes the input, which then feeds into the "Ollama Model" to generate an AI-powered response. This allows for rapid prototyping of AI assistants, internal knowledge base querying, or even personalized customer support interactions without relying on external cloud-based LLMs. Businesses can leverage this to build private, secure AI applications, reducing API costs and ensuring data privacy by keeping LLM interactions within their own infrastructure, ultimately saving time on development and operational expenses.
Workflow JSON
{"id": "Telr6HU0ltH7s9f7", "meta": {"instanceId": "31e69f7f4a77bf465b805824e303232f0227212ae922d12133a0f96ffeab4fef"}, "name": "\ud83d\udde8\ufe0fOllama Chat", "tags": [], "nodes": [{"id": "9560e89b-ea08-49dc-924e-ec8b83477340", "name": "When chat message received", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [280, 60], "webhookId": "4d06a912-2920-489c-a33c-0e3ea0b66745", "parameters": {"options": {}}, "typeVersion": 1.1}, {"id": "c7919677-233f-4c48-ba01-ae923aef511e", "name": "Basic LLM Chain", "type": "@n8n/n8n-nodes-langchain.chainLlm", "onError": "continueErrorOutput", "position": [640, 60], "parameters": {"text": "=Provide the users prompt and response as a JSON object with two fields:\n- Prompt\n- Response\n\nAvoid any preample or further explanation.\n\nThis is the question: {{ $json.chatInput }}", "promptType": "define"}, "typeVersion": 1.5}, {"id": "b9676a8b-f790-4661-b8b9-3056c969bdf5", "name": "Ollama Model", "type": "@n8n/n8n-nodes-langchain.lmOllama", "position": [740, 340], "parameters": {"model": "llama3.2:latest", "options": {}}, "credentials": {"ollamaApi": {"id": "", "name": "[Your ollamaApi]"}}, "typeVersion": 1}, {"id": "61dfcda5-083c-43ff-8451-b2417f1e4be4", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [-380, -380], "parameters": {"color": 4, "width": 520, "height": 860, "content": "# \ud83e\udd99 Ollama Chat Workflow\n\nA simple N8N workflow that integrates Ollama LLM for chat message processing and returns a structured JSON object.\n\n## Overview\nThis workflow creates a chat interface that processes messages using the Llama 3.2 model through Ollama. When a chat message is received, it gets processed through a basic LLM chain and returns a response.\n\n## Components\n- **Trigger Node**\n- **Processing Node**\n- **Model Node**\n- **JSON to Object Node**\n- **Structured Response Node**\n- **Error Response Node**\n\n## Workflow Structure\n1. The chat trigger node receives incoming messages\n2. Messages are passed to the Basic LLM Chain\n3. The Ollama Model processes the input using Llama 3.2\n4. Responses are returned through the chain\n\n## Prerequisites\n- N8N installation\n- Ollama setup with Llama 3.2 model\n- Valid Ollama API credentials\n\n## Configuration\n1. Set up the Ollama API credentials in N8N\n2. Ensure the Llama 3.2 model is available in your Ollama installation\n\n"}, "typeVersion": 1}, {"id": "64f60ee1-7870-461e-8fac-994c9c08b3f9", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [340, 280], "parameters": {"width": 560, "height": 200, "content": "## Model Node\n- Name: Ollama Model\n- Type: LangChain Ollama Integration\n- Model: llama3.2:latest\n- Purpose: Provides the language model capabilities"}, "typeVersion": 1}, {"id": "bb46210d-450c-405b-a451-42458b3af4ae", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [200, -160], "parameters": {"color": 6, "width": 280, "height": 400, "content": "## Trigger Node\n- Name: When chat message received\n- Type: Chat Trigger\n- Purpose: Initiates the workflow when a new chat message arrives"}, "typeVersion": 1}, {"id": "7f21b9e6-6831-4117-a2e2-9c9fb6edc492", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [520, -380], "parameters": {"color": 3, "width": 500, "height": 620, "content": "## Processing Node\n- Name: Basic LLM Chain\n- Type: LangChain LLM Chain\n- Purpose: Handles the processing of messages through the language model and returns a structured JSON object.\n\n"}, "typeVersion": 1}, {"id": "871bac4e-002f-4a1d-b3f9-0b7d309db709", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [560, -200], "parameters": {"color": 7, "width": 420, "height": 200, "content": "### Prompt (Change this for your use case)\nProvide the users prompt and response as a JSON object with two fields:\n- Prompt\n- Response\n\n\nAvoid any preample or further explanation.\nThis is the question: {{ $json.chatInput }}"}, "typeVersion": 1}, {"id": "c9e1b2af-059b-4330-a194-45ae0161aa1c", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [1060, -280], "parameters": {"color": 5, "width": 420, "height": 520, "content": "## JSON to Object Node\n- Type: Set Node\n- Purpose: A node designed to transform and structure response data in a specific format before sending it through the workflow. It operates in manual mapping mode to allow precise control over the response format.\n\n**Key Features**\n- Manual field mapping capabilities\n- Object transformation and restructuring\n- Support for JSON data formatting\n- Field-to-field value mapping\n- Includes option to add additional input fields\n"}, "typeVersion": 1}, {"id": "3fb912b8-86ac-42f7-a19c-45e59898a62e", "name": "Sticky Note6", "type": "n8n-nodes-base.stickyNote", "position": [1520, -180], "parameters": {"color": 6, "width": 460, "height": 420, "content": "## Structured Response Node\n- Type: Set Node\n- Purpose: Controls how the workflow responds to users chat prompt.\n\n**Response Mode**\n- Manual Mapping: Allows custom formatting of response data\n- Fields to Set: Specify which data fields to include in response\n\n"}, "typeVersion": 1}, {"id": "fdfd1a5c-e1a6-4390-9807-ce665b96b9ae", "name": "Structured Response", "type": "n8n-nodes-base.set", "position": [1700, 60], "parameters": {"options": {}, "assignments": {"assignments": [{"id": "13c4058d-2d50-46b7-a5a6-c788828a1764", "name": "text", "type": "string", "value": "=Your prompt was: {{ $json.response.Prompt }}\n\nMy response is: {{ $json.response.Response }}\n\nThis is the JSON object:\n\n{{ $('Basic LLM Chain').item.json.text }}"}]}}, "typeVersion": 3.4}, {"id": "76baa6fc-72dd-41f9-aef9-4fd718b526df", "name": "Error Response", "type": "n8n-nodes-base.set", "position": [1460, 660], "parameters": {"options": {}, "assignments": {"assignments": [{"id": "13c4058d-2d50-46b7-a5a6-c788828a1764", "name": "text", "type": "string", "value": "=There was an error."}]}}, "typeVersion": 3.4}, {"id": "bde3b9df-af55-451b-b287-1b5038f9936c", "name": "Sticky Note7", "type": "n8n-nodes-base.stickyNote", "position": [1240, 280], "parameters": {"color": 2, "width": 540, "height": 560, "content": "## Error Response Node\n- Type: Set Node\n- Purpose: Handles error cases when the Basic LLM Chain fails to process the chat message properly. It provides a fallback response mechanism to ensure the workflow remains robust.\n\n**Key Features**\n- Provides default error messaging\n- Maintains consistent response structure\n- Connects to the error output branch of the LLM Chain\n- Ensures graceful failure handling\n\nThe Error Response node activates when the main processing chain encounters issues, ensuring users always receive feedback even when errors occur in the language model processing.\n"}, "typeVersion": 1}, {"id": "b9b2ab8d-9bea-457a-b7bf-51c8ef0de69f", "name": "JSON to Object", "type": "n8n-nodes-base.set", "position": [1220, 60], "parameters": {"options": {}, "assignments": {"assignments": [{"id": "12af1a54-62a2-44c3-9001-95bb0d7c769d", "name": "response", "type": "object", "value": "={{ $json.text }}"}]}}, "typeVersion": 3.4}], "active": false, "pinData": {}, "settings": {"executionOrder": "v1"}, "versionId": "5175454a-91b7-4c57-890d-629bd4e8d2fd", "connections": {"Ollama Model": {"ai_languageModel": [[{"node": "Basic LLM Chain", "type": "ai_languageModel", "index": 0}]]}, "JSON to Object": {"main": [[{"node": "Structured Response", "type": "main", "index": 0}]]}, "Basic LLM Chain": {"main": [[{"node": "JSON to Object", "type": "main", "index": 0}], [{"node": "Error Response", "type": "main", "index": 0}]]}, "When chat message received": {"main": [[{"node": "Basic 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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