المساعد الذكي لمركز تجديد الطبي (Arabic AI Assistant)

A powerful Arabic chatbot application that answers questions based on text content loaded from files using Google's Gemini 1.5 Pro AI model.

🌟 Features

• Natural Arabic Conversation: Interactive chatbot with support for Egyptian Arabic dialect
• Context-Aware Responses: AI answers based solely on the loaded text content
• Beautiful UI/UX: Rich, responsive user interface with modern design elements
• Real-time Interaction: Dynamic conversation interface with typing indicators
• Conversation History: Save and load conversation sessions
• Optimized for Arabic: Full RTL (Right-to-Left) support and Arabic-optimized design

🚀 Live Demo

Check out the live demo: المساعد الذكي

💻 Tech Stack

Backend

• Python 3.9+
• Flask for API endpoints
• LangChain & LangGraph for AI conversation management
• Google Gemini 1.5 Pro AI model
• Python-dotenv for environment variable management

Frontend

• Pure HTML, CSS, and JavaScript
• Interactive particle system for dynamic background
• Responsive design for all device sizes
• Modern animations and UI effects

🔧 Setup

Prerequisites

• Python 3.9 or higher
• A Google API key for Gemini 1.5 Pro access

Installation

1. Clone the repository:

   git clone https://github.com/A11Veles/answerfrompdf.git
   cd answerfrompdf

2. Create a virtual environment and activate it:

   python -m venv venv
   # On Windows
   venv\Scripts\activate
   # On macOS/Linux
   source venv/bin/activate

3. Install the required packages:

   pip install -r requirements.txt

4. Create a .env file in the project root with your Google API key:

   GOOGLE_API_KEY=your_google_api_key_here
   

5. Create a directory for your Arabic text content:

   mkdir content_arabic

6. Add your text files (in UTF-8 encoding) to the content_arabic directory.

🎮 Usage

1. Start the Flask server:

   python api.py

2. Open your browser and navigate to:

   http://localhost:5000
   

3. Start chatting with the AI assistant in Arabic!

📁 Project Structure

answerfrompdf/
├── api.py              # Flask API for serving the frontend and handling requests
├── main.py             # Core chatbot logic with Gemini AI integration
├── index.html          # Frontend user interface
├── requirements.txt    # Python dependencies
├── .env                # Environment variables (not in repo)
└── content_arabic/     # Directory for text files to be processed

🔑 Environment Variables

• GOOGLE_API_KEY: Your Google API key for accessing Gemini 1.5 Pro

🛠️ Deployment

Deploying to Vercel

1. Fork this repository
2. Create a new project in Vercel
3. Link your GitHub repository
4. Set the following:
   • Build Command: pip install -r requirements.txt
   • Output Directory: ./
   • Install Command: pip install -r requirements.txt
5. Add your environment variables in the Vercel dashboard
6. Deploy!

📝 License

This project is provided as-is. Feel free to use and modify as needed.

👥 Contact

For any questions or feedback, please open an issue on GitHub.

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Built with ❤️ using Google Gemini 1.5 Pro