🤖 ChatAPI - AI Chat Assistant

A modern, full-featured AI chat application powered by Google Gemini, Groq, Cerebras, and SambaNova. This application provides a unified interface to interact with cutting-edge models like Gemini 2.0 Flash, Llama 3.1, and Gemma 2, complete with user management, conversation history, and an admin dashboard.

🌟 Features

🎯 Core Capabilities

• Multi-Model Support: Seamlessly switch between:
  • Google: Gemini 2.0 Flash, Gemini 1.5 Flash
  • Groq: Llama 3.1 8B (Instant), Gemma 2 9B
  • Cerebras: Llama 3.1 8B (Super Fast)
  • SambaNova: Llama 3.1 8B (Balanced)
• Efficient Tier Selection: Optimized model selection for speed and reliability.
• Contextual Memory: Persistent conversation history stored in PostgreSQL.

🎨 User Experience

• Interactive Gallery: Feature showcase with a built-in Lightbox Image Viewer.
• Modern UI: Cyberpunk/Glassmorphism inspired design with dark/light theme support.
• Responsive Design: Fully optimized for Desktop and Mobile devices (including sidebar navigation).
• Customization: Adjustable font sizes, temperature controls, and theme settings.
• Rich Text: Markdown support for code blocks, tables, and lists in chat responses.

🔧 Admin & Control

• Admin Dashboard: Comprehensive panel to manage users and view system stats.
• User Management: Role-based access control (Admin/User).
• Message Limits: Configurable daily message quotas per user to manage API costs.
• Analytics: Monitor chat volume and user activity.

🚀 Quick Start

Prerequisites

• Node.js 18 or higher
• PostgreSQL database (Local or Cloud like Neon/Supabase)
• API Keys for the providers you wish to use (Google, Groq, etc.)

Installation

1. Clone the repository

   git clone https://github.com/MIbnEKhalid/ChatAPI.git
   cd ChatAPI

2. Install dependencies

   npm install

3. Set up environment variables Create a .env file in the root directory:

   cp .env.template .env

   See the Environment Variables section below.

4. Set up the database Run the SQL script to create the necessary tables:

   psql -U your_username -d your_database -f model/db.sql

5. Start the application

   npm start

6. Access the application

   • Main Application: http://localhost:3030
   • Admin Dashboard: http://localhost:3030/admin

🔧 Environment Variables

Configure the following in your example.env.template file: .env.template.

🗄️ Database Schema

The application uses PostgreSQL with the following main tables:

• ai_history_chatapi: Stores conversation threads, messages, and timestamps.
• user_message_logs_chatapi: Tracks daily message usage for rate limiting.
• users (or equivalent): User credentials and role management.

🛠️ Tech Stack

• Backend: Node.js, Express.js
• Database: PostgreSQL
• Frontend: Handlebars (HBS), Vanilla CSS/JS
• Authentication: Session-based (Custom/Passport)
• AI Integration: Official SDKs and REST APIs

📱 API Endpoints

Chat Operations

• GET /chatbot - Render the chat interface.
• POST /api/chat - Process user message and return AI response.
• GET /api/history - Fetch conversation history.
• DELETE /api/chat/:id - Delete a specific conversation.

Admin

• GET /admin/dashboard - View system statistics.
• GET /admin/users - Manage registered users.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the project
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

👨‍💻 Team

Name	Role	Links
Muhammad Bin Khalid	Lead Developer
Maaz Waheed	Developer

📝 License

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

Contact

For questions or contributions, please contact Muhammad Bin Khalid at mbktech.org/Support, support@mbktech.org , chmuhammadbinkhalid28.com and wwork4287@gmail.com.