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Shopify Support Agent

A multi-agent AI customer-support app for Shopify merchants. Handles pre-purchase (product discovery, recommendations) and post-purchase (order tracking, returns, delivery status) self-service through specialised agents with intent classification and entity extraction.

The design uses a Listen-Match-Solve framework: confirm the right order is identified before any action is taken.

Architecture

Service Stack Purpose
backend/ Node.js + Express + Prisma (SQLite) API, auth, chat orchestration, OpenAI calls
frontend/ React + Vite + Tailwind Storefront chat widget + admin views
eval-service/ Python + FastAPI + RAGAS Async evaluation of agent responses
knowledge-base/ Markdown Source-of-truth policies (returns, shipping, payments, escalation, FAQ, loyalty)
seed-data/ JSON Demo products and users for local development

Quick start

# 1. Backend
cd backend
cp .env.example .env       # fill in OPENAI_API_KEY + JWT_SECRET
npm install
npx prisma migrate dev
node prisma/seed.js
npm run dev                 # http://localhost:3002

# 2. Frontend
cd ../frontend
npm install
npm run dev                 # http://localhost:5173

# 3. Eval service (optional)
cd ../eval-service
python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt
uvicorn main:app --reload --port 8000

Notes

  • All secrets (OPENAI_API_KEY, JWT_SECRET) live in backend/.env — never commit
  • The SQLite DB at backend/prisma/dev.db is local-only and gitignored
  • Knowledge-base markdown is hot-reloaded; edit files in knowledge-base/ to update agent grounding

About

Multi-agent AI customer-support app for Shopify merchants. Listen-Match-Solve framework with intent classification, RAG over a markdown knowledge base, and async RAGAS evaluation.

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