ai-building-chatbots
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:
- What does the bot do? (answer questions, resolve issues, qualify leads, guide onboarding?)
- What states can the conversation be in? (greeting, gathering info, resolving, escalating, closing?)
- When should the bot escalate to a human? (complex issues, angry users, sensitive topics?)
- 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.
lm = dspy.LM("openai/gpt-4o-mini") # or "anthropic/claude-sonnet-4-5-20250929", etc.
dspy.configure(lm=lm)
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