# Learning More

Additional resources, tutorials, and advanced learning materials for Semantica.

!!! info "About This Guide"
    This guide provides structured learning paths, quick references, troubleshooting guides, and advanced topics to help you master Semantica.

---

## Structured Learning Paths

<div class="grid cards" markdown>

-   :material-school: **Beginner Path**
    ---
    Perfect for those new to Semantica and knowledge graphs.
    

    
    [Start Path](#beginner-path-1-2-hours)

-   :material-compass: **Intermediate Path**
    ---
    For users comfortable with basics who want to build production applications.
    

    
    [Start Path](#intermediate-path-4-6-hours)

-   :material-rocket: **Advanced Path**
    ---
    For experienced users building enterprise applications.
    

    
    [Start Path](#advanced-path-8-hours)

</div>

---

### Beginner Path (1-2 hours)

1.  **Installation & Setup** (15 min)
    - [Installation Guide](installation.md)
    - [Welcome to Semantica](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/introduction/01_Welcome_to_Semantica.ipynb)

2.  **Core Concepts** (30 min)
    - [Core Concepts](concepts.md)
    - [Getting Started Guide](getting-started.md)

3.  **First Knowledge Graph** (30 min)
    - [Quickstart Tutorial](quickstart.md)
    - [Your First Knowledge Graph](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/introduction/08_Your_First_Knowledge_Graph.ipynb)

4.  **Basic Operations** (30 min)
    - [Examples](examples.md)
    - Extract entities and relationships

---

### Intermediate Path (4-6 hours)

1.  **Advanced Concepts** (1 hour)
    - [Modules Guide](modules.md)
    - Understand: Embeddings, GraphRAG, Ontologies

2.  **Use Cases** (1 hour)
    - [Use Cases Guide](use-cases.md)
    - Implement a complete use case

3.  **Advanced Examples** (1 hour)
    - [Examples](examples.md) - Conflict resolution, custom config

4.  **Quality & Optimization** (1 hour)
    - [Quality Assurance](concepts.md#8-quality-assurance)
    - [Performance Optimization](#performance-optimization)

---

### Advanced Path (8+ hours)

1.  **Advanced Architecture** (2 hours)
    - [Architecture Guide](architecture.md)
    - Plugin development

2.  **Production Deployment** (2 hours)
    - [Security Best Practices](#security-best-practices)
    - Scalability patterns

3.  **Customization** (2 hours)
    - Custom extractors and exporters
    - API extensions

---

## Quick Reference

### Common Operations

```python
from semantica import Semantica
semantica = Semantica()

# Build Knowledge Graph
result = semantica.build_knowledge_base(
    sources=["doc.pdf"],
    embeddings=True,
    graph=True
)

# Extract Entities
entities = semantica.semantic_extract.extract_entities(text)

# Query Graph
results = semantica.kg.query("MATCH (n) RETURN n LIMIT 10")
```

### Configuration Reference

| Setting | Environment Variable | Config File | Default |
| :--- | :--- | :--- | :--- |
| OpenAI API Key | `OPENAI_API_KEY` | `api_keys.openai` | `None` |
| Embedding Provider | `SEMANTICA_EMBEDDING_PROVIDER` | `embedding.provider` | `"openai"` |
| Graph Backend | `SEMANTICA_GRAPH_BACKEND` | `knowledge_graph.backend` | `"networkx"` |

---

## Troubleshooting Guide

<div class="grid cards" markdown>

-   :material-alert: **Import Errors**
    ---
    `ModuleNotFoundError`
    
    **Solution**: Verify installation (`pip list`) and Python version (3.8+).

-   :material-key: **API Key Errors**
    ---
    `AuthenticationError`
    
    **Solution**: Set `OPENAI_API_KEY` environment variable.

-   :material-memory: **Memory Errors**
    ---
    `MemoryError`
    
    **Solution**: Use batch processing and graph stores (Neo4j).

-   :material-speedometer: **Slow Processing**
    ---
    Long processing times
    
    **Solution**: Enable parallel processing and GPU acceleration.

</div>

---

## Performance Optimization

### 1. Batch Processing

Process multiple documents together for better throughput.

```python
sources = ["doc1.pdf", "doc2.pdf", ..., "doc100.pdf"]
result = semantica.build_knowledge_base(sources, batch_size=10)
```

### 2. Parallel Execution

Use parallel processing for independent operations.

```python
result = semantica.build_knowledge_base(
    sources=sources,
    parallel=True,
    max_workers=8
)
```

### 3. Backend Selection

| Operation | NetworkX | Neo4j |
| :--- | :--- | :--- |
| **Graph Construction** | ⚡⚡⚡ | ⚡⚡ |
| **Query Performance** | ⚡⚡ | ⚡⚡⚡ |
| **Scalability** | Low | High |

---

## Security Best Practices

### API Key Management

- **DO**: Use environment variables, rotate keys regularly.
- **DON'T**: Hardcode keys, commit to version control.

### Data Privacy

- **DO**: Encrypt sensitive data, use local models.
- **DON'T**: Send PII to external APIs without protection.

---

## FAQ

**Q: What is Semantica?**
A: A framework for building knowledge graphs and semantic applications.

**Q: Is Semantica free?**
A: Yes, it is open source. Some features (e.g., OpenAI) require paid APIs.

**Q: Can I use Semantica in production?**
A: Yes, it is designed for production with proper configuration.

---

## Next Steps

- **[Deep Dive](deep-dive.md)** - Advanced architecture
- **[API Reference](reference/core.md)** - Complete API documentation
- **[Cookbook](cookbook.md)** - Interactive tutorials

---

!!! info "Contribute"
    Have questions? [Open an issue](https://github.com/Hawksight-AI/semantica/issues) or [start a discussion](https://github.com/Hawksight-AI/semantica/discussions)!

**Last Updated**: 2024
