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E-Commerce Assistant for Shopify & WooCommerce with GPT-4o, Gemini & RAG

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Created by: Harsh Maniya || harshmaniya1

Harsh Maniya

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Last update 11 hours ago

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🤖 Universal E-Commerce AI Assistant (Shopify, WooCommerce & RAG)

This powerful n8n workflow deploys a sophisticated, multi-talented AI chatbot designed to streamline your e-commerce and customer support operations. The AI assistant can intelligently understand user queries and route them to the correct specialized agent, whether it's for Shopify, WooCommerce, or general knowledge questions answered by a Retrieval-Augmented Generation (RAG) system.

This template automates responses to a wide range of inquiries, from checking Shopify order statuses with GraphQL to fetching product lists from WooCommerce, and even answering general questions by looking up information in a Pinecone vector database.

How It Works ⚙️

The workflow operates in a series of logical steps, starting from the moment a user sends a message.

  1. 💬 Chat Trigger: The workflow activates when a user sends a message in the n8n chat interface. It captures the user's input and a unique session ID to track the conversation.

  2. 🧠 Intelligent Routing: The user's query is first sent to a Router Agent powered by GPT-4o-mini. This agent's sole purpose is to classify the intent of the message and output one of three keywords: SHOPIFY, WOOCOMMERCE, or None of them.

  3. 🔀 Conditional Branching: Based on the Router's output, a series of IF nodes direct the conversation down one of three paths:

    • General Queries Path
    • Shopify Path
    • WooCommerce Path

  4. 📚 General Queries (RAG): If the query is not about e-commerce, it's handled by a RAG agent.

    • Embedding: The user's question is converted into a vector embedding using AWS Bedrock.
    • Retrieval: The workflow searches a Pinecone Vector Store to find the most relevant information from your knowledge base.
    • Generation: A GPT-4o-mini agent receives the context from Pinecone and generates a comprehensive, helpful answer.

  5. 🛍️ E-Commerce Specialists: If the query is about Shopify or WooCommerce, it's passed to a dedicated agent.

    • Shopify Agent: This agent uses Google Gemini and has a suite of tools to manage Shopify tasks. It can Get Order info, Fetch All Products, or run complex queries using the powerful GraphQL tool.
    • WooCommerce Agent: This agent also uses Google Gemini and is equipped with tools to Fetch Order Details and Fetch All Products from a WooCommerce store.

  6. 🗣️ Conversation Memory: Each agent (Router, General, Shopify, WooCommerce) is connected to its own Memory node. This allows the chatbot to remember previous parts of the conversation for a more natural and context-aware interaction.

  7. 🏁 Merge & Respond: All three paths converge at a final Merge node. This ensures that no matter which agent handled the request, the final answer is streamlined into a single output and sent back to the user in the chat.

Nodes Used 🔗

  • Triggers:
    • Chat Trigger: Starts the workflow when a chat message is received.
  • AI & Agents:
    • AI Agent: Four separate agents for Routing, Shopify, WooCommerce, and General Queries.
    • OpenAI Chat Model: Uses GPT-4o-mini for the Router and General Queries agent.
    • Google Gemini Chat Model: Uses Google Gemini for the Shopify and WooCommerce agents.
  • Tools & Data:
    • Shopify Tool: To get products and order information from Shopify.
    • WooCommerce Tool: To get products and order information from WooCommerce.
    • GraphQL Tool: For advanced, custom queries to the Shopify API.
    • Pinecone Vector Store: To retrieve context for the RAG agent.
    • AWS Bedrock Embeddings: To create vector embeddings for Pinecone.
  • Logic & Memory:
    • IF Node: To conditionally route the workflow.
    • Merge Node: To consolidate the different branches before ending.
    • Window Buffer Memory: Four nodes to provide conversational memory to each agent.

Setup Guide 🛠️

To use this workflow, you'll need to configure several nodes with your own credentials and settings.

1. AI Model Credentials

  • OpenAI: Create an API key in your OpenAI Platform dashboard. Add this credential to the Router Model and GPT-4o-mini nodes.
  • Google Gemini: Create an API key in your Google AI Studio dashboard. Add this credential to the Shopify Chat Model and WooCommerce Chat Model nodes.

2. E-Commerce Platform Credentials

  • Shopify: You will need a Shopify Access Token. Follow the n8n documentation to generate one. Add the credential to the Fetch All Products and Get Order info nodes.
  • WooCommerce: Create API credentials from your WordPress dashboard. Add the credential to the Fetch All Products2 and Fetch Order Details nodes.

3. RAG System Credentials (Pinecone & AWS)

  • Pinecone:
    • Sign up for a Pinecone account and create an API key.
    • Add your Pinecone credentials in n8n.
    • In the Pinecone Vector Store node, set the pineconeIndex to the name of your index. You must have a pre-existing index with data for the RAG to work.
  • AWS:
    • Create an AWS account and an IAM user with programmatic access to Amazon Bedrock.
    • Add your AWS credentials in n8n.
    • Select your AWS credentials in the AWS Bedrock Embeddings node.

4. GraphQL Node Configuration

  • In the GraphQL node, you must update the endpoint URL. Replace the placeholder https://{subdomain}.myshopify.com/admin/api/2025-04/graphql.json with your own Shopify store's GraphQL API endpoint.