An AI-powered chatbot for e-commerce platforms built using the Rasa framework. Handles customer queries related to order tracking, product information, and general support through natural language conversations.
- Order tracking with ID validation
- Product search and inventory checking
- Return and refund policy assistance
- Payment and shipping information
- Context-aware and intent-based conversation flows
- AI/NLP: Rasa Open Source 3.x, spaCy
- Frontend: React.js (18+)
- Backend: Node.js + Express
- Language: Python 3.8+
# Clone the repository
git clone <repo-url>
cd rasa-ecommerce-assistant
# Python environment
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
# Install Python dependencies
pip install -r requirements.txt
# Install frontend dependencies
cd src
npm install
cd ..
# Train and run the assistant
rasa train
rasa run --enable-api --port 5005 &
rasa run actions --port 5055 &
cd src
npm start
track_order
: Track orders by order IDreturn_policy
: Provide return/refund detailsproduct_search
: Discover available productsshipping_info
: Offer shipping and delivery detailspayment_methods
: List accepted payment options
- Order IDs
- Product names
- Shipping types
- Payment methods
rasa-ecommerce-assistant/
├── actions/ # Custom action code
├── data/ # NLU training data, stories, and rules
├── models/ # Trained Rasa models
├── src/ # React frontend
├── config.yml # Rasa pipeline and policies
├── domain.yml # Intents, entities, slots, responses
├── endpoints.yml # Action server and tracker store config
└── requirements.txt # Python dependencies
- Response latency: < 200ms
- Intent classification accuracy: 95%+
- Handles up to 50 concurrent users (test environment)
This project is licensed under the MIT License.