Chatbot Web App

A Flask-based AI chatbot web application with a modern, responsive frontend, chat history, FAQ support, and OpenAI integration.

Features

• Interactive chat interface with real-time messages
• FAQ matching for common user questions
• Persistent user chat history saved in a local SQLite database
• Session-based user tracking through cookies
• REST API endpoints for chat, history, and TTS integration
• Styled single-page frontend with history, stats, and settings panels

Tech stack

• Python 3.x
• Flask
• OpenAI API
• HTML/CSS/JavaScript frontend
• SQLite for local history storage

Prerequisites

• Python 3.10+ installed
• pip package manager
• OpenAI API key

Installation

1. Clone the repository:

git clone https://github.com/<your-username>/<repo-name>.git
cd chatbot

2. Install dependencies:

pip install -r requirements.txt

Configuration

Create a .env file in the project root with the following values:

OPENAI_API_KEY=your_openai_api_key
SECRET_KEY=your-secret-key
FLASK_ENV=development
FLASK_DEBUG=True
FLASK_HOST=127.0.0.1
FLASK_PORT=5000
DATABASE_PATH=chat_history.db

Notes:

• OPENAI_API_KEY is required for chat responses when no FAQ match is found.
• DATABASE_PATH defaults to chat_history.db if not set.

Run the application

python app.py

Open your browser at:

http://127.0.0.1:5000/

API Endpoints

• POST /api/chat - Send a chat message and receive a response
• GET /api/history - Retrieve the current user's chat history
• DELETE /api/history/clear - Clear the current user's chat history
• GET /api/history/stats - Retrieve usage statistics for the current user
• POST /api/tts - Placeholder TTS endpoint for future integration

Project structure

• app/ - Flask application package
  • api/ - Blueprint routes for chat, history, TTS, and health checks
  • models/ - Database models and persistence logic
  • services/ - Chat processing, FAQ matching, and context management
  • templates/ - HTML templates
  • static/ - Frontend assets (CSS, JS)
  • utils/ - Session and input validation helpers
• app.py - Application entry point
• config.py - Environment-based configuration
• requirements.txt - Python dependencies for development
• requirements-prod.txt - Production dependency list
• Dockerfile - Container build instructions
• docker-compose.yml - Service definition for local deployment
• Procfile - Deployment process entry for platforms like Heroku
• runtime.txt - Python runtime version for platform deployment
• wsgi.py - WSGI application entrypoint for production servers
• tests/ - Automated test suite

Notes

• The app currently includes a placeholder TTS route; you can extend it with any speech service.
• Frontend assets are served from app/templates/static via Flask's static file routing.

License

This project is available under the terms of the LICENSE file.