ChatGPT Clone Application

A conversational AI application built with modern web technologies, featuring intelligent chat responses and weather information services.

Overview

This project implements a full-stack chatbot application that leverages OpenAI's language models to provide human-like conversations. The system includes user management, persistent chat storage, and integrated weather services.

Core Capabilities

The application provides several key functionalities:

• User authentication system with secure registration and login
• Intelligent conversation handling using OpenAI's GPT models
• Weather information retrieval for global cities
• Conversation history persistence across user sessions
• Real-time chat interface with responsive design

Technology Implementation

Backend Architecture

• FastAPI framework for REST API development
• SQLAlchemy ORM for database operations
• PostgreSQL for data persistence
• Alembic for database schema management

Frontend Development

• Streamlit framework for user interface
• Interactive chat components
• Real-time response handling

External Services

• OpenAI API for natural language processing
• OpenWeatherMap API for meteorological data

System Requirements

Before installation, ensure your development environment includes:

• Python version 3.8 or newer
• PostgreSQL database server (version 13 recommended)
• Active internet connection for API services
• Git version control system

API Credentials Setup

You will need to obtain API keys from the following services:

1. OpenAI Platform - Register at https://platform.openai.com for GPT access
2. OpenWeatherMap - Create account at https://openweathermap.org for weather data

Installation Process

Repository Setup

git clone <your-repository-url>
cd <project-directory>

Python Environment Configuration

python3 -m venv chatbot_env
source chatbot_env/bin/activate  # Linux/Mac
chatbot_env\Scripts\activate     # Windows
pip install -r requirements.txt

Database Initialization

Access your PostgreSQL instance and execute:

CREATE DATABASE chatbot_db;
CREATE USER app_user WITH PASSWORD 'secure_password';
GRANT ALL ON DATABASE chatbot_db TO app_user;

Environment Configuration

Create .env file with your credentials:

OPENAI_API_KEY=<your-openai-key>
WEATHER_API_KEY=<your-weather-key>
DATABASE_URL=postgresql://app_user:secure_password@localhost:5432/chatbot_db

Database Schema Setup

alembic upgrade head

Running the Application

Start Backend Service

cd app
uvicorn main:app --host 0.0.0.0 --port 8000

Launch Frontend Interface

streamlit run streamlit_app.py --server.port 8501

Access the application at http://localhost:8501

Application Usage

Getting Started

1. Navigate to the application URL
2. Create a new user account or sign in
3. Begin conversation by typing in the message field
4. Select conversation topics using the dropdown menu

Weather Queries

For weather information:

• Set topic to "weather"
• Enter city name in message field
• Receive current weather conditions

Conversation Management

• All conversations are automatically saved
• Previous chats can be continued in new sessions
• Context is maintained across message exchanges

Development Guidelines

Adding New Features

When extending functionality:

alembic revision --autogenerate -m "feature description"
alembic upgrade head

Code Organization

• Models: Database table definitions
• Routes: API endpoint implementations
• Services: External API integrations
• Schemas: Data validation structures

Troubleshooting Guide

Database Issues

• Verify PostgreSQL service is running
• Check connection string format
• Confirm user permissions are correct

API Problems

• Validate API key formats and activation
• Monitor usage quotas and limits
• Check network connectivity

Port Conflicts

• Modify FastAPI port: uvicorn main:app --port 8001
• Change Streamlit port: streamlit run app.py --server.port 8502

Project Architecture

The application follows a layered architecture pattern:

• Presentation Layer: Streamlit UI components
• API Layer: FastAPI route handlers
• Business Logic: Service implementations
• Data Layer: SQLAlchemy models and PostgreSQL

Contributing

To contribute to this project:

1. Fork the repository
2. Create feature branch from main
3. Implement changes with tests
4. Submit pull request with description

Support and Contact

For technical support or questions:

• Review troubleshooting section
• Check existing issues in repository
• Create new issue with detailed problem description

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Project maintained by Advay Parab
Last updated: $(date +%Y-%m-%d)