🤖 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.
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💬 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.
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🧠 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.
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🔀 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
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📚 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.
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🛍️ 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.
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🗣️ 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.
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🏁 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.