Ollama Chatbot: Seamless AI Conversations with n8n
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Automate engaging AI-powered chat experiences using n8n and Ollama's Llama 3.2 model. This workflow triggers on chat messages, processes them with a powerful LLM, and returns structured JSON responses, enabling dynamic conversational AI integrations.
About This Workflow
This n8n workflow, named '🗨️Ollama Chat', is designed to create an intelligent chatbot that leverages the power of Ollama and the Llama 3.2 language model. It begins with a chat trigger that listens for incoming messages. Upon receiving a message, it enters a 'Basic LLM Chain' where the user's prompt is fed into the Ollama model. The workflow is configured to expect a structured JSON output, detailing the 'Prompt' and 'Response' from the LLM, ensuring clean data handling. A dedicated 'Ollama Model' node utilizes the 'llama3.2:latest' model, requiring valid Ollama API credentials. The output is then processed to provide a user-friendly response, while a separate error handling node ensures graceful failure. This setup allows for seamless integration of advanced conversational AI into your automated workflows.
Key Features
- Real-time Chat Trigger: Instantly processes incoming chat messages.
- Ollama LLM Integration: Leverages the advanced Llama 3.2 model for intelligent responses.
- Structured JSON Output: Ensures consistent and parseable data from the LLM.
- Customizable Prompting: Easily adapt the LLM's instructions for specific use cases.
- Robust Error Handling: Provides fallback responses when processing fails.
How To Use
- Set up Ollama: Ensure Ollama is installed and the 'llama3.2:latest' model is downloaded.
- Configure n8n Credentials: In n8n, add your Ollama API credentials under 'Credentials' > 'Ollama API'.
- Connect Trigger: Set up the 'When chat message received' node to your desired chat platform or webhook endpoint.
- Define LLM Prompt: Customize the 'Basic LLM Chain' node's 'text' parameter to guide the AI's responses, using
{{ $json.chatInput }}to insert the user's message. - Review Model Node: Verify the 'Ollama Model' node is correctly configured with your credentials and the 'llama3.2:latest' model.
- Map Response: Adjust the 'Structured Response' node to format the AI's output as desired before sending it back to the user.
- Test Workflow: Trigger the workflow with a chat message and observe the output.
Apps Used
Workflow JSON
{
"id": "4c623b39-c18f-4211-b1b4-6fc320dbf28a",
"name": "Ollama Chatbot: Seamless AI Conversations with n8n",
"nodes": 7,
"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.
Get This Workflow
ID: 4c623b39-c18f...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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