semantica/docs/installation.md

Installation

Get Semantica up and running in minutes.

!!! success "Now Available on PyPI!" Semantica is officially published on PyPI! Install it with a single command: pip install semantica

!!! note "System Requirements" Semantica requires Python 3.8 or higher. For best performance, we recommend Python 3.10+.

Prerequisites

Before installing Semantica, ensure you have:

• Python 3.8 or higher - Check your version:

  python --version
  

• pip - Python package installer (usually comes with Python)

Basic Installation

Install Semantica from PyPI:

pip install semantica

This installs Semantica with all core dependencies.

!!! tip "Virtual Environment" We recommend installing Semantica in a virtual environment to avoid dependency conflicts. Use python -m venv venv to create one, then activate it before installing.

Verify Installation

Verify that Semantica is installed correctly:

python -c "import semantica; print(semantica.__version__)"

Expected output:

0.0.1

You can also check the installation:

pip show semantica

Development Installation

To install Semantica in development mode (for contributing):

# Clone the repository
git clone https://github.com/Hawksight-AI/semantica.git
cd semantica

# Install in editable mode
pip install -e .

# Or install with development dependencies
pip install -e ".[dev]"

Optional Dependencies

Semantica supports optional features that can be installed separately:

GPU Support

For GPU-accelerated operations:

pip install semantica[gpu]

This includes:

• PyTorch with CUDA support
• FAISS GPU
• CuPy

Visualization

For enhanced visualization capabilities:

pip install semantica[viz]

Includes:

• PyVis for interactive graphs
• Graphviz for static diagrams
• UMAP for dimensionality reduction

LLM Providers

Install all LLM provider integrations:

pip install semantica[llm-all]

Or install specific providers:

# OpenAI
pip install semantica[llm-openai]

# Anthropic
pip install semantica[llm-anthropic]

# Google Gemini
pip install semantica[llm-gemini]

# Groq
pip install semantica[llm-groq]

# Ollama
pip install semantica[llm-ollama]

Cloud Integrations

For cloud storage and deployment:

pip install semantica[cloud]

Includes:

• AWS S3 (boto3)
• Azure Blob Storage
• Google Cloud Storage
• Kubernetes support

All Optional Features

Install everything:

pip install semantica[all]

Virtual Environment (Recommended)

It's recommended to use a virtual environment:

=== "venv"

```bash
# Create virtual environment
python -m venv venv

# Activate (Windows)
venv\Scripts\activate

# Activate (Linux/Mac)
source venv/bin/activate

# Install Semantica
pip install semantica
```

=== "conda"

```bash
# Create conda environment
conda create -n semantica python=3.11
conda activate semantica

# Install Semantica
pip install semantica
```

Troubleshooting

Common Issues

ModuleNotFoundError

Error: ModuleNotFoundError: No module named 'semantica'

Solutions:

• Make sure you've activated the correct Python environment
• Verify installation: pip list | grep semantica
• Reinstall: pip install --upgrade semantica

Installation Fails

Error: Installation fails with dependency errors

Solutions:

• Upgrade pip: pip install --upgrade pip
• Install build tools: pip install build wheel
• Try installing without optional dependencies first: pip install semantica --no-deps

GPU Dependencies Fail

Error: GPU dependencies fail to install

Solutions:

• Install CPU-only version first: pip install semantica
• Then add GPU support: pip install semantica[gpu]
• Check CUDA compatibility for your system

Permission Errors

Error: Permission denied during installation

Solutions:

• Use --user flag: pip install --user semantica
• Use virtual environment (recommended)
• On Linux/Mac, avoid using sudo with pip

System Requirements

Component	Minimum	Recommended
Python	3.8	3.11+
RAM	Moderate	Ample for your dataset
Disk Space	Sufficient for data	Generous storage
OS	Windows/Linux/Mac	Linux/Mac

Next Steps

Now that Semantica is installed:

1. Quick Start Guide - Build your first knowledge graph
2. Examples - See real-world use cases
3. **API Reference - Explore the full API
4. Cookbook - Interactive tutorials

Getting Help

If you encounter issues:

• Check the troubleshooting section above
• Review GitHub Issues
• Ask questions in discussions