Build a Conversational AI Chatbot

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.

Step 1: Define the conversation

Ask the user:

1. What does the bot do? (answer questions, resolve issues, qualify leads, guide onboarding?)
2. What states can the conversation be in? (greeting, gathering info, resolving, escalating, closing?)
3. When should the bot escalate to a human? (complex issues, angry users, sensitive topics?)
4. What docs or data should it draw from? (help articles, product docs, FAQs, database?)

Step 2: Build the response module (DSPy)

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