# Frequently Asked Questions

**Common questions about Semantica and how to use it.**

---

## General

### What is Semantica?
Semantica is an open-source framework for building knowledge graphs from unstructured data. It transforms documents, web pages, and databases into structured, queryable knowledge.

### What can I do with Semantica?
- **Build knowledge graphs** from documents and data
- **Extract entities and relationships** automatically
- **Power AI applications** with structured knowledge
- **Create semantic search** and GraphRAG systems
- **Integrate multiple data sources** into unified graphs

### Is Semantica free?
Yes! Semantica is open source under the MIT License.

### What makes Semantica different?
- **Modular architecture** - Use only what you need
- **Production-ready** - Built for scale and reliability
- **Extensible** - Add custom models and components
- **Open source** - Transparent and community-driven

---

## Installation

### How do I install Semantica?
```bash
pip install semantica
```

### What Python version do I need?
Python 3.8 or higher. Python 3.11+ is recommended.

### What are the system requirements?
- Python 3.8+
- 4GB+ RAM for basic use
- Optional GPU for embeddings and ML models

---

## Getting Started

### How do I start using Semantica?
```python
from semantica.semantic_extract import NERExtractor
from semantica.kg import GraphBuilder

# Extract entities
ner = NERExtractor()
entities = ner.extract("Apple Inc. was founded by Steve Jobs.")

# Build knowledge graph
kg = GraphBuilder().build({"entities": entities})
```

### Where can I find examples?
- **[Getting Started Guide](getting-started.md)** - Quick introduction
- **[Cookbook](cookbook.md)** - Practical examples
- **[GitHub Examples](https://github.com/Hawksight-AI/semantica/tree/main/examples)** - Code samples

---

## Features

### What data sources does Semantica support?
- **Files**: PDF, DOCX, TXT, JSON, CSV
- **Web**: Websites, RSS feeds, APIs
- **Databases**: PostgreSQL, MySQL, Snowflake, MongoDB
- **Streams**: Kafka, RabbitMQ, real-time data

### Can I use custom models?
Yes! Semantica supports custom:
- **Entity extraction models**
- **Embedding models**
- **Language models**
- **Custom processors**

### Does Semantica support GPUs?
Yes, Semantica automatically uses GPUs when available for:
- **Embedding generation**
- **ML model inference**
- **Vector operations**

---

## Technical

### How does Semantica handle large datasets?
- **Batching** - Process data in chunks
- **Streaming** - Handle real-time data
- **Parallel processing** - Use multiple cores
- **Memory management** - Efficient resource usage

### Can I deploy Semantica in production?
Yes! Semantica is production-ready with:
- **Scalable architecture**
- **Error handling**
- **Monitoring support**
- **Container deployment**

### How do I customize Semantica?
- **Custom processors** - Add new extraction logic
- **Custom models** - Use your own ML models
- **Plugins** - Extend functionality
- **Configuration** - Adjust behavior

---

## Troubleshooting

### Installation issues
- **Python version**: Ensure Python 3.8+
- **Dependencies**: Install with `pip install -e .[dev]`
- **Permissions**: Use virtual environments

### Performance issues
- **Memory**: Increase available RAM
- **GPU**: Install CUDA for GPU acceleration
- **Batching**: Use smaller chunk sizes

### Common errors
- **Import errors**: Check installation path
- **Model loading**: Verify model availability
- **Memory errors**: Reduce batch sizes

---

## Support

### Where can I get help?
- **[GitHub Issues](https://github.com/Hawksight-AI/semantica/issues)** - Report problems
- **[Discussions](https://github.com/Hawksight-AI/semantica/discussions)** - Ask questions
- **[Documentation](index.md)** - Browse guides and references

### How do I report bugs?
1. **Search** existing issues first
2. **Create** a new issue with details
3. **Include** reproduction steps
4. **Add** environment information

### Can I contribute?
Yes! See the [Contributing Guide](contributing.md) for details on how to help improve Semantica.