felipepimentel/ddialog

DDialog: Intelligent Document-Based Conversation Platform

DDialog is an advanced, AI-powered conversation platform that enables meaningful interactions with your documents. It leverages OpenRouter API and FastAPI to provide intelligent responses based on your document context.

🌟 Features

• 🧠 Integration with OpenRouter API for advanced language model capabilities
• 🗂️ Workspace-based document organization
• 💬 Real-time chat interface with AI responses
• 📄 Support for document upload and management
• 🌓 Dark/Light theme toggle
• 🎨 Customizable chat interface (font size, color)
• 🚀 Built with modern technologies: React, TypeScript, FastAPI, and PostgreSQL

🏗️ Project Structure

The project consists of two main components:

1. Frontend (React + TypeScript + Vite)
2. Backend (FastAPI + SQLAlchemy + PostgreSQL)

🚀 Quick Start

Using Docker (Recommended)

1. Clone the repository:

   git clone https://github.com/yourusername/ddialog.git
   cd ddialog

2. Create a .env file in the backend directory and add your OpenRouter API key:

   OPENROUTER_API_KEY=your_api_key_here

3. Build and run the Docker containers:

   docker compose -f docker-compose.dev.yml up --build

4. Access the application at http://localhost:5173

Manual Setup

Backend

1. Navigate to the backend directory:

   cd backend

2. Install dependencies:

   pip install -r requirements.txt

3. Set up the database:

   alembic upgrade head

4. Run the FastAPI server:

   uvicorn src.main:app --reload --host 0.0.0.0 --port 8000

Frontend

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   pnpm install

3. Run the development server:

   pnpm run dev

4. Access the application at http://localhost:5173

📚 API Documentation

Once the backend is running, you can access the API documentation at http://localhost:8000/docs

🧪 Key Components

Backend

• main.py: FastAPI application setup and configuration
• routers/chat.py: API routes for conversation and message handling
• models.py: SQLAlchemy models for database tables
• schemas.py: Pydantic models for data validation
• services/llm_service.py: Handles communication with the OpenRouter API

Frontend

• src/features/Chat/ChatWindow.tsx: Main component for the chat interface
• src/features/Workspace/WorkspaceMenu.tsx: Component for managing workspaces
• src/services/api.ts: Axios setup for API communication

📝 Usage

1. Create a workspace
2. Upload documents to the workspace
3. Start a conversation in the chat window
4. The AI will provide responses based on the uploaded documents and conversation context

🛠️ Development

• The project uses Alembic for database migrations
• Frontend styling is done using Tailwind CSS and Shadcn UI
• The application supports both light and dark modes
• CORS is configured for local development

🔧 Configuration

• Frontend configuration files: vite.config.ts, tsconfig.json, tailwind.config.js, postcss.config.js
• Backend configuration: .env file for environment variables, alembic.ini for database migrations

🐳 Docker

The project includes Dockerfiles for both frontend and backend, as well as a docker-compose.dev.yml for easy development setup.

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a new branch: git checkout -b feature/your-feature-name
3. Make your changes and commit them: git commit -m 'Add some feature'
4. Push to the branch: git push origin feature/your-feature-name
5. Submit a pull request

Please ensure your code adheres to the project's coding standards and includes appropriate tests.

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🙏 Acknowledgements

• OpenRouter for their API
• FastAPI team for their excellent web framework
• React team for their powerful frontend library
• Tailwind CSS for the utility-first CSS framework
• Shadcn UI for the beautiful UI components

📞 Support

If you encounter any issues or have questions, please file an issue on the GitHub repository.

Happy chatting with DDialog! 🚀