Restaurant Complaint Management System

This Streamlit application provides a platform for managing restaurant complaints and feedback. It offers functionalities for both customers to submit reviews and restaurant owners to analyze complaint data.

Features

For Customers:

• Submit reviews/complaints
• Automatic sentiment analysis of reviews
• Multi-label categorization of complaints
• Generation of auto-responses based on the complaint

For Restaurant Owners:

• View complaint statistics for a specified number of days
• Analyze complaint categories and their frequencies
• Access detailed review information

Technologies Used

• Python
• Streamlit
• Pandas
• TensorFlow
• Transformers (BERT)
• TextBlob
• MySQL

Setup and Installation

1. Clone the repository

2. Install the required packages:

3. Set up a MySQL database named 'restaurant_review'

4. Update the database connection details in the script

Running the Application

Run the Streamlit app using:

$:streamlit run main.py

Usage

1. Select user type (Customer or Restaurant Owner) from the sidebar
2. For Customers:
   • Enter your review in the text area
   • Click 'Submit Review' to process and save your feedback
3. For Restaurant Owners:
   • Enter the number of days for which you want to view complaint data
   • Click 'Get Complaint Info' to view statistics and detailed review information

Model and Data

• The application uses a pre-trained BERT model for multi-label classification
• Ensure that the model weights ('tf_model.h5') and the dataset ('last.csv') are present in the same directory as the script

Note

• The sentiment analysis and categorization are performed automatically
• The application connects to a MySQL database to store and retrieve review data

Future Improvements

• Implement user authentication
• Add more detailed analytics for restaurant owners
• Enhance the auto-response generation system