Building Conversational Commerce with Multi-Agent Swarms on GCP: A Working Prototype

Imagine ordering your weekly groceries as naturally as texting a friend:"Hey, we're out of milk and eggs. Can you also add some snacks for Friday movie night?" In our previous post, Building Conversational Commerce with Multi-Agent Swarms on GCP, we shared the architectural blueprint for conversational commerce—proposing a 3-layer decoupled design (Ingress, Memory, and Cognition) to solve messaging timeouts, state tracking, and response reliability. While blueprints establish the architecture on paper, production readiness demands working software. In this post, we take that blueprint and bring it to life with a functional prototype called HappyDelivery. Using LangGraph, Gemini, FastAPI, and Google Cloud, we'll walk through the code, the state machine, deterministic financial tools, and an automated verification suite that demonstrates how this multi-agent swarm operates in practice. 1. The Prototype Stack: 3 Layers, 3 Diagrams Let's examine how each layer functions in code with its own dedicated architecture. A frequent question when designing conversational commerce is: how does a message sent by a customer on their smartphone actually land in Layer 1, and can this architecture support messaging platforms beyond WhatsApp? End users do not communicate directly with…