Using LLM for Dialogue Management

Short summary

LLMs can replace traditional dialogue management systems by reasoning over conversation history and available actions. This article examines four production patterns (end-to-end, structured state extraction, tool-augmented, hybrid classifier), prompt engineering best practices, and context window optimization. Includes a working Python example of an e-commerce support agent using OpenAI's SDK.

• •Four production dialogue management patterns for LLM-based systems
• •Prompt engineering strategies for state tracking and context management
• •Working code example: e-commerce support agent with function calling

Generated with AI, which can make mistakes.