Travel Agent based on Qwen2 RLHF is an open-source AI travel companion using reinforcement learning with human feedback to craft personalized itineraries. It integrates flight, hotel, and activity data to suggest optimized schedules. Users provide travel preferences through prompts and receive detailed plans, packing lists, maps, and real-time updates. Continuous feedback enhances recommendation accuracy over time.
Travel Agent based on Qwen2 RLHF is an open-source AI travel companion using reinforcement learning with human feedback to craft personalized itineraries. It integrates flight, hotel, and activity data to suggest optimized schedules. Users provide travel preferences through prompts and receive detailed plans, packing lists, maps, and real-time updates. Continuous feedback enhances recommendation accuracy over time.
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.