Installation

Requirements

  • Python 3.11 or higher

  • Git (for cloning the repository)

  • Dependencies listed in pyproject.toml

Quick Installation

On Windows

  1. Clone the repository:

    git clone https://github.com/AliElneklawy/DataVerse-ChatBot.git
cd DataVerse-ChatBot

  2. Run the installation script:

    install.bat

    This script will:

    • Create a virtual environment (if needed)

    • Install all dependencies from pyproject.toml

    • Set up environment configuration

Manual Installation

  1. Clone the repository:

    git clone https://github.com/AliElneklawy/DataVerse-ChatBot.git
cd DataVerse-ChatBot

  2. Create a virtual environment (recommended):

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

  3. Install dependencies using uv:

    pip install uv
uv pip install -e .

    Alternatively, use pip directly:

    pip install -e .

  4. Create and configure the .env file:

    cp .env.example .env
# Edit .env with your API keys and configuration

API Key Configuration

The system requires API keys from various LLM providers depending on which ones you plan to use. Edit your .env file to include the appropriate keys:

# OpenAI
OPENAI_API=your_openai_api_key

# Anthropic (Claude)
CLAUDE_API=your_claude_api_key

# Cohere
COHERE_API=your_cohere_api_key

# Google (Gemini)
GOOGLE_API=your_google_api_key

# Mistral
MISTRAL_API=your_mistral_api_key

# DeepSeek
DEEPSEEK_API=your_deepseek_api_key

# Grok (X.AI)
GROK_API=your_grok_api_key

# Email configuration for monitoring
GMAIL_APP_PASSWORD=your_gmail_app_password

Directory Structure

After installation, the following directory structure will be created:

DataVerse-ChatBot/
├── assets/              # Fonts and images
├── data/                # Data storage
│   ├── database/        # SQLite databases
│   ├── datasets/        # Training datasets
│   ├── indexes/         # FAISS vector indexes
│   ├── models/          # Trained models
│   ├── training_files/  # Files for training
│   ├── voices/          # Voice recordings
│   └── web_content/     # Extracted content
├── docs/                # Documentation
├── src/                 # Source code
│   ├── chatbot/         # Core chatbot functionality
│   │   ├── embeddings/  # Embedding implementations
│   │   ├── rag/         # RAG implementations
│   │   └── utils/       # Utility functions
│   ├── web/             # Web interfaces
│   └── *.py             # Bot implementations
└── tests/               # Test files