Welcome to the Chatbot for Food Delivery App project! This chatbot is designed to enhance the user experience of your food delivery application by providing a conversational interface powered by Dialogflow. With custom entity recognition for food names, a FastAPI backend, and MySQL database integration for orders and menu management, this project aims to streamline the ordering process for your users.
- Dialogflow Integration: Seamlessly interacts with users using Dialogflow's natural language processing capabilities.
- Custom Entity Recognition: Enhances accuracy in identifying food items through custom entities.
- FastAPI Backend: Provides a robust and high-performance backend solution.
- MySQL Database: Stores and manages orders, order tracking, and the food menu efficiently.
- Secure Tunneling with Ngrok: Enables secure communication by converting HTTP to HTTPS.
- Clone the repository:
git clone https://github.com/Aftabmallick/chatbot-for-food_delivery-app-using-dialogflow.git- Install dependencies:
cd chatbot-for-food_delivery-app-using-dialogflow
pip install -r requirements.txt-
Set up MySQL database:
- Create a MySQL database and update the database configuration in
config.py.
- Create a MySQL database and update the database configuration in
-
Run the FastAPI server:
uvicorn main:app --reload- Set up Ngrok for secure tunneling:
- Download and install Ngrok from https://ngrok.com/.
- Start Ngrok to expose your local server:
./ngrok config add-authtoken <authtoken>./ngrok http 8000- Update the Ngrok HTTPS URL in Dialogflow fulfillment settings.
- Integrate the chatbot into your food delivery application.
- Users can interact with the chatbot to place orders, track orders, and explore the menu.
- The chatbot utilizes custom entities to accurately recognize food names, providing relevant responses to user queries.
- Special thanks to the developers of Dialogflow, FastAPI, MySQL, and Ngrok for providing powerful tools and technologies for building this project.