Planning a trip traditionally requires significant time and effort, as travellers must research destinations, accommodations, activities, and routes across multiple disconnected platforms. Existing travel systems provide generic, non-personalised suggestions that fail to address individual preferences such as travel mood, group type, and budget constraints. To address these challenges, this paper presents Travel Buddy, an AI-powered personalised trip planning and itinerary generation platform developed using Python (Django) as the backend framework, SQLite as the database, and the Groq API for AI-driven recommendations. The proposed system accepts user inputs including destination, travel duration, mood, group type, and budget, and generates comprehensive day-wise itineraries with activity suggestions, dining recommendations, accommodation options, and cost estimates. The platform includes features such as user authentication, trip customisation, hotel booking assistance, interactive map visualisation, and trip history management. The system was evaluated across multiple trip planning scenarios and demonstrated significant improvements in planning efficiency, personalisation quality, and user experience when compared to conventional travel platforms. Travel Buddy provides an accessible, scalable, and intelligent solution for modern travellers seeking customised trip planning without manual research overhead.

Keywords—AI Trip Planner, Personalised Itinerary, Groq API, Django, Travel Automation, Mood-Based Planning, Smart Tourism, Web Application.