This n8n workflow creates a sophisticated system for providing personalized tour package recommendations leveraging AI and a user-friendly web UI, specifically using Lovable, an interactive form interface. The main goal is to enable users to input destination or activity preferences via a web form, then utilize AI models to generate, refine, and deliver tailored travel suggestions.
The process begins with a Webhook node that receives user input from the Lovable UI. This input triggers the ‘Tour Recommendation AI Agent,’ an AI-powered assistant that analyzes the destination or activities provided. It communicates with OpenAI’s GPT-4 model and a vector database (Pinecone), which contains pre-vectorized tour packages, to assess suitable options.
The workflow uses the ‘Embeddings OpenAI’ node to generate embeddings of user data, which are stored in the Pinecone vector database for fast similarity searches. Using the trained vector store, the workflow matches user preferences with existing tour packages and retrieves the most relevant options.
Subsequently, the ‘Answer questions with a vector store’ node, aided by a specialized prompt, helps the AI agent retrieve and synthesize the best tour suggestions by querying the vector database. The final recommendations are parsed in a structured JSON format by the ‘Structured Output Parser’, which formats the data into a detailed itinerary.
The instructions emphasize creating itineraries with day-by-day activities, optimizing for user preferences, and presenting the output clearly. The results are sent back as a JSON response via the ‘Respond to Webhook’ node, which displays personalized travel plans directly to the user through the Lovable interface.
This workflow is ideal for travel agencies or tour operators seeking to streamline custom tour package creation with AI assistance and enhance customer experience through dynamic, personalized travel suggestions delivered via a web interface.
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