Travel Planner with Multi-AI Agents

This study describes the creation of an AI-based travel planning system that implements multi-agent architecture to fully automate and customize a trip itinerary. Incorporating the Groq LLaMA language model for NLU and NLG, as well as real-time web search capabilities through SerpAPI, the system can issue evolving and up-to-theminute recommendations. Streamlit was used to build the application, which enables users to specify a travel destination, trip duration, budget, traveling style, and whether they would like to hire a local guide. Using these criteria, AI agents work together to provide a comprehensive itinerary complete with accommodation details, daily activities, meals, safety tips, and other relevant information on expenses. Having access to the local guides database improves the practicality of the solution. This project highlights the advances offered by multi-agent AI systems for real-life decision support problems and demonstrates how this technology can bolster intelligent travel planning systems designed for the relative ease of the customer.