This n8n workflow demonstrates how to integrate various language models, including OpenAI’s GPT, with custom scripts and Wikipedia queries for dynamic information retrieval and conversational AI. The workflow starts with a manual trigger, allowing users to initiate prompts such as telling a joke or asking about Einstein’s birth year. It includes nodes that set input prompts, invoke OpenAI language models, and execute custom JavaScript code for specialized tools like Wikipedia searches. The workflow’s design provides a flexible framework for building AI-powered chatbots or informational assistants, showcasing how to combine pre-built language models with custom tools for tailored responses. Practical applications include creating conversational agents for websites, educational tools, or information retrieval systems that require real-time, context-aware responses.
n8n Workflow for Language Model and Wikipedia Integration
Node Count | 6 – 10 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.code, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.lmOpenAi, manualTrigger, set, stickyNote |
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