Sentiment Analysis Chatbot

This project features a sentiment analysis chatbot that processes user messages and returns the sentiment of the message along with a simulated chatbot response. The application uses FastAPI for the backend and React.js for the frontend. Below are the picture of the demo(The product is not ready yet):

Table of Contents

• Overview
• Backend Setup
• Frontend Setup
• Running the Application
• Technologies Used
• License

Overview

This project includes:

• Backend (FastAPI): Provides endpoints to analyze the sentiment of user input and simulate chatbot responses.
• Frontend (React.js): Displays a chat interface where users can type a message and receive a sentiment analysis from the bot.

The application allows users to interact with a chatbot where the sentiment of their message is analyzed and the response is displayed on the chat interface.

Backend Setup

Requirements

• Python 3.7+
• FastAPI
• Uvicorn
• psycopg2-binary

Installation

1. Clone the repository:

   git clone https://github.com/aashish-thapa/Sentiment-Chatbot.git
   cd Sentiment-Chatbot

2. Install the required dependencies:

   pip install -r requirements.txt

3. Start the FastAPI server:

   uvicorn app.main:app --reload

   This will start the server on http://127.0.0.1:8000.

4. Ensure your database is set up correctly and the necessary tables (like messages) exist. If using PostgreSQL or MySQL, ensure the user has proper permissions.

Frontend Setup

Requirements

• Node.js
• npm (or yarn)

Installation

1. Navigate to the frontend directory:

   cd frontend

2. Install the dependencies:

   npm install

3. Start the React development server:

   npm start

   This will start the frontend on http://localhost:3000.

Running the Application

1. Ensure both the backend and frontend servers are running.
2. Navigate to http://localhost:3000 in your browser.
3. Start chatting with the bot. Type a message and the sentiment will be analyzed and displayed in the chat.

Technologies Used

• Backend: FastAPI, SQLAlchemy (or your preferred database)
• Frontend: React.js, Axios for API requests, React hooks for state management
• Sentiment Analysis: Custom sentiment analysis model (integrated with the backend)
• Styling: Basic CSS/Inline styles for chat interface

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Feel free to update this with specific details related to your project, like database setup instructions or any extra tools or libraries used.