Automate AI Travel Planning with Couchbase Vector Search
Generate highly relevant travel recommendations in seconds, reducing research time by over 90% and enhancing user satisfaction.
Manually curating personalized travel recommendations is a tedious and slow process, hindering quick decision-making. This workflow instantly generates tailored travel itineraries by combining Gemini AI, OpenAI embeddings, and Couchbase Vector Search for efficient information retrieval.
Documentation
AI-Powered Travel Planning with Couchbase, Gemini, and OpenAI
Tired of generic travel advice? This n8n workflow revolutionizes travel planning by creating a sophisticated AI agent that offers personalized recommendations based on your unique interests. Ideal for travel agencies, booking platforms, and anyone seeking efficient, tailored itinerary creation.
Key Features
- Delivers highly personalized travel recommendations using advanced AI reasoning.
- Instantly retrieves relevant points of interest from a custom knowledge base via Couchbase Vector Search.
- Utilizes Google Gemini 2.0 Flash for intelligent conversation and OpenAI for robust embeddings.
- Seamlessly ingests new data to continuously expand and improve the agent's knowledge.
How It Works
This workflow operates in two main modes: data ingestion and interactive querying. When new points of interest are sent to a dedicated webhook, they are chunked, embedded using OpenAI, and stored in Couchbase's vector database. For travel inquiries, a chat message triggers the AI agent, powered by Gemini 2.0 Flash and historical memory. The agent leverages Couchbase Vector Search as a tool, performing semantic lookups against your stored points of interest using OpenAI embeddings. It then synthesizes this information to provide detailed, personalized travel recommendations directly in response to user queries.