ai-building-chatbots

Guide the user through building a multi-turn chatbot that remembers context, follows conversation flows, and produces high-quality responses. Uses DSPy for optimizable response generation and LangGraph for conversation state, memory, and flow control.

The core of your chatbot is a DSPy module that generates responses given conversation history and context.

LangGraph manages the conversation flow — what state the bot is in, when to transition, and when to escalate.

构建一个具有记忆和状态的对话式人工智能助手。当您需要客户支持聊天机器人、帮助台机器人、入职助理、销售资格机器人、常见问题解答助理或任何多轮会话人工智能时使用。由用于响应质量的 DSPy 和用于对话状态管理的 LangGraph 提供支持。 来源：lebsral/dspy-programming-not-prompting-lms-skills。