Travel Agent AI leverages large language models and travel APIs to automate the process of trip planning and booking. Users input their travel dates, destinations, budget, and interests; the agent then produces a day-by-day itinerary with recommended flights, hotels, and local attractions. It uses real-time API calls to check flight schedules, hotel availability, and weather forecasts. Features include customizable itineraries, cost breakdowns, multi-city routing, and suggestions for dining and transportation. Designed for both casual travelers and travel professionals, Travel Agent AI reduces manual research, optimizes travel costs, and provides a comprehensive travel plan in minutes.

Travel Agent based on Qwen2 RLHF is an AI-driven travel assistant that harnesses reinforcement learning from human feedback to optimize every aspect of trip planning. Combining real-time flight and hotel availability, local attraction databases, and user-defined preferences, the agent curates daily schedules, dining recommendations, transportation routes, and budget breakdowns. It supports multi-destination trips, group travel coordination, and last-minute changes, adjusting itineraries on the fly. Through a conversational interface, travelers input budget, dates, interests, and accommodation standards, receiving detailed plans including maps and packing checklists. Continuous interaction and feedback enable the model to learn individual tastes, improving relevance over time and delivering tailored, seamless travel experiences.