AI Tutoring RAG System

from rag.system import TutoringRAGSystem def knowledge_base_retrieval_interface( student_id: str, current_question: str, subject: str, topic: str, context_limit: int = 5, ) -> str: """ Generates a personalized response using the RAG system. Args: student_id: The unique identifier for the student. current_question: The question the student is currently asking. subject: The subject of the question (e.g., "Mathematics", "History"). topic: The specific topic within the subject (e.g., "Algebra", "World War II"). context_limit: The number of previous learning interactions to consider for context. Returns: A personalized and empathetic response from the AI tutor. """ rag_system = TutoringRAGSystem() return rag_system.generate_personalized_response( student_id=student_id, current_question=current_question, subject=subject, topic=topic, context_limit=context_limit, )