OpenAI Chatbot Project

📋 Project Description

This project is an advanced chat application that leverages OpenAI's powerful language models to provide intelligent responses. Built with a modern tech stack, it combines a FastAPI backend with a responsive frontend, featuring load balancing, service discovery, and session management.

🎯 Purpose

• Create a scalable, intelligent chatbot interface using OpenAI's GPT models
• Provide fast and reliable responses through efficient API integration
• Implement vector-based search capabilities for improved response accuracy
• Enable real-time chat functionality with WebSocket support
• Ensure high availability through load balancing and service discovery

🛠️ Technologies Used

Backend (35%)

• FastAPI: High-performance Python web framework
• Python 3.11+: Core programming language
• OpenAI API: For natural language processing
• FAISS: Vector similarity search library
• Redis: Session management and caching
• Uvicorn: ASGI server implementation

Infrastructure (30%)

• Load Balancer: Custom implementation for request distribution
• Service Discovery: Automatic service registration and health checks
• Session Management: Redis-based session storage
• Task Queue: Asynchronous task processing

Frontend (25%)

• HTML/Jinja2: Template-based structure
• JavaScript: Client-side functionality and WebSocket handling
• CSS: Responsive design and styling

DevOps (10%)

• Docker: Containerization
• Docker Compose: Multi-container orchestration
• NGINX: Reverse proxy and load balancing

⭐ Key Features

1. High Availability Architecture

• Load balancing across multiple instances
• Automatic service discovery and registration
• Health monitoring and failover
• Scalable infrastructure

2. Intelligent Chat Processing

• Real-time message processing
• Context-aware responses
• Natural language understanding
• Message history management

3. Advanced Search & Memory

• FAISS-powered vector similarity search
• Efficient query processing
• Memory management for chat context
• Knowledge base integration

4. Robust API Layer

• RESTful API endpoints
• WebSocket support
• Rate limiting and caching
• Comprehensive error handling

5. Security & Performance

• Input validation and sanitization
• Performance monitoring and logging
• Rate limiting protection
• Secure session management

🔧 Technical Architecture

graph TD
    A[Client] -->|HTTP/WebSocket| B[Load Balancer]
    B -->|Request Distribution| C[FastAPI Instances]
    C -->|Service Discovery| D[Service Registry]
    C -->|Session Management| E[Redis Store]
    C -->|Chat Processing| F[OpenAI Service]
    C -->|Vector Search| G[FAISS Index]
    C -->|Cache| H[Redis Cache]
    C -->|Tasks| I[Task Queue]

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📂 Project Structure

OpenAI Chatbot Project/
├── app/
│   ├── __init__.py
│   ├── main.py
│   ├── error_handlers.py
│   ├── memory.py
│   ├── models/
│   │   ├── __init__.py
│   │   ├── message.py
│   ├── routers/
│   │   ├── __init__.py
│   │   └── chat.py
│   ├── handlers/
│   │   └── message_handler.py
│   ├── services/
│   │   ├── __init__.py
│   │   └── chat_service.py
│   └── exceptions.py
├── common/
│   ├── websocket_manager.py
├── services/
│   ├── __init__.py
│   └── openai_service.py
├── config/
│   ├── __init__.py
│   ├── logging_config.py
│   ├── faiss_config.py
│   └── settings.py
├── load_balancer/
│   ├── __init__.py
│   └── balancer.py
├── middleware/
│   ├── __init__.py
│   └── error_logging.py
├── scripts/
│   ├── __init__.py
│   └── vectorization.py
├── service_discovery/
│   ├── __init__.py
│   └── discovery.py
├── session/
│   ├── __init__.py
│   └── redis_store.py
├── templates/
│   └── index.html
├── static/
│   ├── css/
│   └── js/
├── utils/
│   ├── __init__.py
│   ├── helpers.py
│   ├── cache_manager.py
│   ├── decorators.py
│   ├── health_check.py
│   ├── performance_logger.py
│   ├── rate_limiter.py
│   ├── task_queue.py
│   └── backup_manager.py
├── tests/
│   ├── __init__.py
│   ├── test_exceptions.py
│   ├── test_helpers.py
│   ├── test_main.py
│   ├── test_openai_services.py
│   └── test_vector_store.py
├── .coverage
├── .coveragerc
├── .env
├── Dockerfile
├── docker-compose.yml
├── nginx.conf
├── pytest.ini
├── requirements.txt
├── setup.py
└── README.md

🚀 Getting Started

Prerequisites

• Python 3.11+
• Docker
• Docker Compose
• Redis
• OpenAI API Key

Installation

Clone the repository:

git clone https://github.com/zehraacer/Enterprise-Grade_OpenAI_Chatbot_Platform.git
cd Enterprise-Grade_OpenAI_Chatbot_Platform

Create and activate a virtual environment:

python3 -m venv venv
source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Set up environment variables: Create a .env file in the root directory and add your configuration:

OPENAI_API_KEY=your_openai_api_key
REDIS_URL=redis://localhost:6379/0

Run the application:

python -m uvicorn app.main:app --reload

Using Docker

Build and run the Docker containers:

docker-compose up --build

🧪 Running Tests

To run the tests, use the following command:

pytest

🤝 Contribution

Contributions are welcome! Please fork the repository and create a pull request. For major changes, please open an issue first to discuss what you would like to change.

📄 License

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

📧 Contact

For any inquiries or support, please contact zehraacer.