Human challenging career and future advice chatbot using RAG

Choosing the right career path is a crucial decision for students and job seekers, often influenced by a lack of proper guidance or access to reliable information. This paper presents a Career Guidance Chatbot that leverages Retrieval-Augmented Generation (RAG) and the Zephyr language model to provide personalized career advice in a conversational manner. The system retrieves relevant data from curated documents and integrates it with the chatbot’s natural language understanding to deliver meaningful suggestions. Built using Stream-Lit, the chatbot offers an interactive, user-friendly interface that simulates real-time conversations. This approach bridges the gap between static career counseling methods and dynamic AI-driven support, offering users a more engaging and accessible platform for decision-making. The chatbot not only simplifies complex career information but also tailor’s guidance based on user preferences and academic background. This solution demonstrates how AI can effectively assist in shaping informed career decisions.