🤖🛒 Smart E-commerce AI Agent API

This API powers an AI-driven shopping assistant that thinks, adapts, and interacts like a human sales professional.

📋 Table of Contents

1. 📘 Introduction
2. ⚙️ Tech Stack
3. ⭐ Features
4. 🚀 Quick Start
5. 📡 API Endpoints
6. 📸 Demo
7. 🔗 Links
8. 📝 License

📘 Introduction

Smart E-commerce AI Agent API is a powerful, AI-driven shopping assistant designed to enhance the online shopping experience. It understands user queries and offers personalized recommendations using multi-step reasoning. Moreover, it interacts naturally with customers just like a human sales associate.

⚙️ Tech Stack

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⭐ Features

🧠 Intelligent Decision Making: The AI agent makes decisions autonomously, understands context, and performs multi-step reasoning to assist users effectively.

🔍 Advanced Search Capabilities: Provides accurate results using vector-based semantic search, and real-time inventory checks.

💬 Natural Conversations: Remembers past conversations, keeps thread-based context, and interacts naturally for a smooth user experience.

🚀 Quick Start

Prerequisites

• Git
• Node.js
• npm
• MongoDB

Clone the repository

git clone https://github.com/Sumit-531/ecommerce-ai-agent.git

cd ecommerce-ai-agent

Installation

Install the project dependencies using npm:

npm install

Set Up Environment Variables

Create a file named .env.local inside the /server directory and add the required environment variables as shown below:

# PORT
PORT=3001

# ENVIRONMENT
NODE_ENV=development

# DATABASE
DB_URI=

# GOOGLE
GOOGLE_API_KEY=

Seed the Database

npm run seed

Running the Project

npm run dev

Test the API

After starting the server, the API will be accessible at: http://localhost:3001 Requests can be made through a web browser or any HTTP client (e.g., Insomnia, Postman) to verify the endpoints.

📡 API Endpoints

Base URL : http://localhost:3001/api/v1

Method	Endpoint	Description	Example
POST	/chat	Initiates a new conversation	Returns a new threadId along with the agent's response
POST	/chat/:threadId	Continues an existing conversation	Returns a context-aware response based on conversation history

📸 Demo

Initial Chat Example

Example response returned by the API when sending a message to the Smart E-commerce AI Agent.

Product Inquiry Example

Example response returned by the API when asking about product variations.

Follow-up Chat Example

Example response returned by the API after a user thanks the Smart E-commerce AI Agent.

🔗 Links

• Node.js - https://nodejs.org/en
• MongoDB - https://www.mongodb.com/
• LangGraph - https://www.langchain.com/langgraph

📝 License

This project is licensed under the MIT License. See the LICENSE file for full details.