Welcome to SwiftShop, your one-stop e-commerce solution! SwiftShop offers a seamless and personalized shopping experience, enabling users to browse, purchase, and review products with ease.
- Suggesting products based on items in your cart and past orders.
- Sentence Transformers to generate embeddings.
- Cosine Similarity to find distances between embeddings.
- Write and submit reviews for products you’ve ordered.
- Rate products to help other customers make informed decisions.
- View reviews (and summarized analysis of reviews) from other users for better insights.
- Using NLTK Sentiment Intensity Analyzer Model to summarize sentiments.
- Real-time chat powered by Websockets.
- Sellers can view in-depth statistics about their sales performance.
- Secure email verification using Nodemailer and Gmail.
- Past searches are cached and recommended as the user types a query.
- Products are recommended dynamically as the user types (using string matching).
- Powered by Gemini Pro with custom context tailored for e-commerce.
- Verify email using OTP during registration.
- See recommended products.
- Search for products.
- Buy products (Stripe integration).
- Add products to the cart.
- Chat with sellers.
- Receive notifications for incoming messages.
- Submit product reviews.
- View profile (addresses, order history, cart items, notifications).
- Use the AI chatbot for queries (Gemini).
- Enjoy Dark Mode for a comfortable shopping experience.
- Add products.
- Modify product details.
- View detailed sales statistics.
- MongoDB for the database.
- Next.js for the frontend.
- Redux for state management across pages and components.
- Gemini Pro for the chatbot.
- Flask for recommendations and review analysis models.
- Nodemailer for email verification.
- Redis for caching searches.
Thank you for choosing SwiftShop! Happy shopping! 🛒✨
git clone <your-forked-repo-link>
Make sure you have Docker and Docker Compose installed and set up.
-
Build and start the containers
docker-compose up --build
-
Access the services:
- Frontend: http://localhost:3000
- Backend: http://localhost:5000
- Flask Server: http://localhost:8000
- Stop the containers
docker-compose down
cd server
npm install
npm run dev
cd client
npm install
npm run dev
cd model
pip install -r requirements.txt
python run.py