Ollama Chat Integration with n8n
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Seamlessly integrate Ollama's powerful language models into your workflows with this n8n template. Process chat messages in real-time, generate structured JSON responses, and build intelligent conversational agents.
About This Workflow
This n8n workflow leverages the power of Ollama to create dynamic chat integrations. It begins by triggering on incoming chat messages, then processes the user's prompt using a LangChain LLM chain. The core of the intelligence comes from the Ollama Model node, specifically configured to use llama3.2:latest. The workflow is designed to return a structured JSON object containing both the original prompt and the LLM's response, ensuring data consistency and ease of further processing. Error handling is included to gracefully manage any issues during message processing. This template is ideal for developers looking to quickly deploy AI-powered chat functionalities.
Key Features
- Real-time Chat Trigger: Initiate workflows instantly upon receiving new chat messages.
- Ollama LLM Integration: Harness the capabilities of Ollama's advanced language models, including Llama 3.2.
- Structured JSON Output: Automatically format LLM responses into a predictable JSON object with 'Prompt' and 'Response' fields.
- Customizable Prompts: Easily adapt the LLM prompt to suit your specific conversational needs.
- Robust Error Handling: Includes a dedicated node to manage and report errors gracefully.
How To Use
- Connect Ollama: In n8n, navigate to 'Credentials' and set up your Ollama API credentials. Ensure the
ollamaApitype is selected and provide the necessary details. - Configure Trigger: The 'When chat message received' node is your starting point. Ensure it's correctly configured to receive your chat inputs (e.g., via a webhook).
- Customize LLM Prompt: Select the 'Basic LLM Chain' node. Modify the 'text' parameter to define how the LLM should process the input and format its output. The template
{{ $json.chatInput }}is used to insert the user's message. - Select Ollama Model: In the 'Ollama Model' node, confirm that 'llama3.2:latest' is the desired model. You can change this to any other model available in your Ollama installation.
- Define Response Structure: The 'Structured Response' node determines the final output to the user. Customize the 'text' field to display the processed prompt and response as needed. The JSON output from the LLM chain is available via
{{ $('Basic LLM Chain').item.json.text }}. - Handle Errors: The 'Error Response' node will be used if any part of the workflow fails. Customize its output to inform users about issues.
- Activate Workflow: Save and activate your n8n workflow.
Apps Used
Workflow JSON
{
"id": "a80fd8ae-7e4e-4357-afa3-613f7a6a6a0d",
"name": "Ollama Chat Integration with n8n",
"nodes": 17,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: a80fd8ae-7e4e...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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