Multi-Turn Conversation
Domain: LLM Concepts
🎯 Motivation
A conversation with multiple back-and-forth exchanges. Each turn depends on previous turns, requiring the model to track context.
📋 Concrete Example
Turn 1: User asks about Python lists. Turn 2: Follow-up about dictionaries. Turn 3: ‘How do they differ?’ The model must remember turns 1-2 to answer turn 3.
🔗 Analogy
A tennis rally - each shot (turn) depends on the previous one. You can’t play a shot without knowing where the ball came from. Multi-turn conversations are rallies of questions and answers.