makaronz/PatChat

PatChat - AI Chat Application

PatChat is a simple and intuitive chat application that enables users to have conversations with AI models and save their chat history for future reference.

Features

• —🤖 AI Chat Interface: Chat with OpenAI models (GPT-3.5, GPT-4, GPT-4o, GPT-4o-mini, GPT-4o-mini-high, GPT-4o3)
• —🎯 System Prompt Customization: Choose from predefined prompts or create custom ones
• —💾 Conversation History: Save and manage all your conversations
• —📱 Responsive Design: Works on desktop and mobile devices
• —🚀 Easy Deployment: Deploy on Hugging Face Spaces with Docker
• —💰 Free Database: Uses free cloud database options
• —💡 Model Information: See descriptions and costs for each AI model

System Prompts

PatChat comes with several predefined system prompts:

• —Default: General helpful assistant
• —Creative: Imaginative and innovative responses
• —Professional: Business-appropriate responses
• —Educational: Learning-focused explanations
• —Coding: Programming and technical assistance
• —Writing: Writing and editing help
• —Custom: Your own custom prompt

Quick Start

Prerequisites

• —Python 3.11+
• —OpenAI API key
• —Free database (Supabase recommended)

Local Development

1. 1.Clone the repository

   git clone <repository-url>
   cd PatChat

1. 1.Install dependencies

   pip install -r requirements.txt

1. 1.Set up environment variables

   cp env.example .env
   # Edit .env with your OpenAI API key and database URL

1. 1.Run the application

   python app.py

1. 1.Open your browser

   http://localhost:5000

Database Setup

Option 1: SQLite (Development)

# No setup required - SQLite file will be created automatically

Option 2: Supabase (Recommended for Production)

1. 1.Create a free account at supabase.com
2. 2.Create a new project
3. 3.Get your database connection string
4. 4.Update your .env file:

   DATABASE_URL=postgresql://postgres:[password]@[host]:5432/postgres

Deployment

Hugging Face Spaces

1. 1.Fork this repository
2. 2.Create a new Space on Hugging Face
3. 3.Set environment variables in Space settings:
4. 4.OPENAI_API_KEY: Your OpenAI API key
5. 5.DATABASE_URL: Your database connection string
6. 6.SECRET_KEY: A secure random string
7. 7.Deploy - Hugging Face will automatically build and deploy your app

Docker Deployment

1. 1.Build the image

   docker build -t patchat .

1. 1.Run the container

   docker run -p 5000:5000 \
     -e OPENAI_API_KEY=your-key \
     -e DATABASE_URL=your-db-url \
     -e SECRET_KEY=your-secret \
     patchat

API Endpoints

Web Routes

• —GET / - Main chat interface
• —GET /history - Conversation history
• —GET /conversation/:id - View specific conversation
• —POST /send_message - Send message to AI
• —POST /new_conversation - Start new conversation
• —DELETE /conversation/:id - Delete conversation
• —GET /system_prompts - Get available system prompts
• —GET /health - Health check

Example API Usage

// Send a message
const response = await fetch('/send_message', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
        conversation_id: 1,
        content: 'Hello AI!',
        model_type: 'gpt-4',
        system_prompt: 'You are a helpful assistant.'
    })
});

// Create new conversation
const newConv = await fetch('/new_conversation', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
        model_type: 'gpt-3.5-turbo',
        system_prompt: 'You are a coding assistant.'
    })
});

Project Structure

PatChat/
├── app.py                 # Main Flask application
├── requirements.txt       # Python dependencies
├── Dockerfile            # Docker configuration
├── env.example           # Environment variables template
├── templates/            # HTML templates
│   ├── base.html         # Base template
│   ├── chat.html         # Chat interface
│   └── history.html      # Conversation history
└── README.md             # This file

Database Schema

Conversations Table

CREATE TABLE conversations (
    id SERIAL PRIMARY KEY,
    title VARCHAR(255) DEFAULT 'New Conversation',
    model_type VARCHAR(50) DEFAULT 'gpt-3.5-turbo',
    system_prompt TEXT DEFAULT 'You are a helpful AI assistant.',
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

Messages Table

CREATE TABLE messages (
    id SERIAL PRIMARY KEY,
    conversation_id INTEGER REFERENCES conversations(id) ON DELETE CASCADE,
    content TEXT NOT NULL,
    role VARCHAR(20) NOT NULL, -- 'user' or 'assistant'
    model_type VARCHAR(50),
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

Configuration

Environment Variables

Supported AI Models

Contributing

1. 1.Fork the repository
2. 2.Create a feature branch
3. 3.Make your changes
4. 4.Add tests if applicable
5. 5.Submit a pull request

License

This project is open source and available under the MIT License.

Support

If you encounter any issues or have questions:

1. 1.Check the Issues page
2. 2.Create a new issue with detailed information
3. 3.Include your environment details and error messages

Roadmap

• —[ ] User authentication
• —[ ] Conversation sharing
• —[ ] Export conversations
• —[ ] Voice input/output
• —[ ] Multiple AI providers
• —[ ] Advanced prompt templates
• —[ ] Conversation search
• —[ ] Mobile app

Made with ❤️ for the AI community