# Frequently Asked Questions Common questions and answers about Semantica. !!! tip "Can't find your question?" Browse existing questions or [ask a new question on GitHub Issues](https://github.com/Hawksight-AI/semantica/issues/new) --- ## General Questions ### What is Semantica? Semantica is an open-source framework for building semantic layers and knowledge graphs from unstructured data. It transforms raw data into structured, queryable knowledge that powers AI applications. ### What can I use Semantica for? - Building knowledge graphs from documents - Creating semantic layers for AI applications - Extracting entities and relationships - Powering GraphRAG systems - Integrating multi-source data - Building AI agent memory ### Is Semantica free? Yes! Semantica is 100% open source and free to use under the MIT License. ### What makes Semantica different? - **Modular**: Use only what you need - **Extensible**: Plug in custom models - **Production-ready**: Built for scale - **Open source**: Fully transparent --- ## Installation & Setup ### How do I install Semantica? ```bash pip install semantica ``` See the [Installation Guide](installation.md) for details. ### What Python version do I need? Python 3.8 or higher. Python 3.11+ is recommended for best performance. ### Do I need a GPU? No, GPU is optional. Semantica works on CPU, but GPU acceleration is available for faster processing. ### How do I get started? 1. Install: `pip install semantica` 2. Follow the [Quick Start Guide](quickstart.md) 3. Try the [Examples](examples.md) --- ## Knowledge Graphs ### What is a knowledge graph? A structured representation where entities (nodes) are connected by relationships (edges). It captures semantic meaning and relationships in data. ### How do I build a knowledge graph? ```python from semantica.ingest import FileIngestor from semantica.parse import DocumentParser from semantica.semantic_extract import NERExtractor, RelationExtractor from semantica.kg import GraphBuilder # Use individual modules ingestor = FileIngestor() parser = DocumentParser() ner = NERExtractor() rel_extractor = RelationExtractor() doc = ingestor.ingest_file("document.pdf") parsed = parser.parse_document("document.pdf") text = parsed.get("full_text", "") entities = ner.extract_entities(text) relationships = rel_extractor.extract_relations(text, entities=entities) builder = GraphBuilder() kg = builder.build_graph(entities=entities, relationships=relationships) ``` ### Can I merge multiple knowledge graphs? Yes! Use the `merge` method: ```python merged = semantica.kg.merge([kg1, kg2, kg3]) ``` ### How do I visualize a knowledge graph? ```python semantica.kg.visualize(kg, output_path="graph.html") ``` --- ## Usage & Features ### Can I process PDF files? Yes! Semantica supports PDF, DOCX, HTML, JSON, CSV, and many other formats. ### How do I extract entities from text? ```python from semantica.semantic_extract import NERExtractor # Use NER extractor directly ner = NERExtractor() entities = ner.extract_entities("Your text") ``` ### Can I use my own models? Yes, Semantica is extensible. You can plug in custom models for entity extraction, embeddings, and more. ### What export formats are supported? - RDF/XML - OWL (Ontology) - JSON - CSV - YAML - And more --- ## Conflict Resolution ### What is conflict resolution? When the same entity appears in multiple sources with different information, conflict resolution determines which information to use. ### What strategies are available? - **Voting**: Majority wins - **Credibility Weighted**: Weight by source credibility - **Most Recent**: Use latest information - **Highest Confidence**: Use highest confidence score ### How do I set a resolution strategy? ```python from semantica.conflicts import ConflictResolver resolver = ConflictResolver(default_strategy="voting") ``` --- ## Integration ### Can I use Semantica with other tools? Yes! Semantica exports to standard formats that work with: - Neo4j - Graph databases - RDF stores - Vector databases - Any tool that accepts RDF/JSON/CSV ### Does it work with LangChain? Yes, Semantica can be integrated with LangChain for RAG applications. ### Can I connect to databases? Yes, Semantica supports connections to Neo4j, FalkorDB, and other graph databases. --- ## Performance ### How fast is Semantica? Performance depends on: - Document size - Number of documents - Hardware (CPU/GPU) - Configuration options For typical documents, processing takes seconds to minutes. ### Can I process large datasets? Yes, but consider: - Processing in batches - Using GPU acceleration - Incremental building - Optimizing configuration ### How can I improve performance? - Enable GPU if available - Process in smaller batches - Use faster models - Optimize configuration - Cache embeddings --- ## Troubleshooting ### Installation fails - Upgrade pip: `pip install --upgrade pip` - Use virtual environment - Check Python version: `python --version` ### No entities extracted - Verify document contains text (not just images) - Check document format is supported - Review extraction configuration ### Memory errors - Process documents one at a time - Reduce batch sizes - Use smaller models - Increase available RAM ### Slow processing - Enable GPU if available - Process in smaller batches - Optimize configuration - Use faster models --- ## Getting Help ### Where can I get help? - **Documentation**: This site - **GitHub Issues**: [Report bugs or ask questions](https://github.com/Hawksight-AI/semantica/issues) ### How do I report a bug? Open an issue on [GitHub](https://github.com/Hawksight-AI/semantica/issues) with: - Description of the problem - Steps to reproduce - Expected vs actual behavior - Environment details ### Can I contribute? Yes! We welcome contributions. See our [Contributing Guide](https://github.com/Hawksight-AI/semantica/blob/main/CONTRIBUTING.md). ### How do I request a feature? Open a feature request on [GitHub Issues](https://github.com/Hawksight-AI/semantica/issues) with: - Use case description - Proposed solution - Benefits to the community --- !!! question "Still have questions?" Check the [API Reference](reference/core.md), browse the [Cookbook](cookbook.md), or [ask on GitHub Issues](https://github.com/Hawksight-AI/semantica/issues/new)