This n8n workflow automates chat interactions by leveraging the Ollama LLM. It begins with a webhook trigger that captures incoming chat messages, which are then processed through a language model chain. The core component uses the Ollama Llama 3.2 model to generate context-aware responses, structured into a JSON object for clarity. In case of errors during processing, a fallback response ensures users receive feedback, maintaining a seamless conversational experience. This workflow is ideal for creating chatbot interfaces, customer support automation, or any scenario requiring intelligent, automated text responses.
Automated Chat Response with Ollama and n8n
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmOllama, set, stickyNote |
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