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* docs(cookbook): tighten prose across notebook catalogue * Resolved comments --------- Co-authored-by: AutoHarness Bot <bot@autoharness.local> Co-authored-by: Sameer Kadam <sskadam6305@gmail.com>
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title, description, icon
| title | description | icon |
|---|---|---|
| Cookbook | Interactive Jupyter notebooks covering everything from your first knowledge graph to production GraphRAG systems. | flask |
Featured Recipe
- Your First Knowledge Graph: go from raw text to a queryable knowledge graph in 20 minutes. Topics: Extraction, Graph Construction, Visualization · Beginner
Core Tutorials
Essential guides to master the Semantica framework.
- Welcome to Semantica: interactive introduction to the framework's core philosophy and all modules. Topics: Framework Overview, Architecture · Beginner
- Data Ingestion: loading data from files, web, databases, streams, feeds, repositories, email, and MCP. Topics: FileIngestor, WebIngestor, DBIngestor · Beginner
- Document Parsing: extracting clean text from complex formats like PDF, DOCX, and HTML. Topics: OCR, PDF Parsing, Text Extraction · Beginner
- Data Normalization: pipelines for cleaning, normalizing, and preparing text. Topics: Text Cleaning, Unicode, Formatting · Beginner
- Entity Extraction: using NER to identify people, organizations, and custom entities. Topics: NER, spaCy, LLM Extraction · Beginner
- Relation Extraction: discovering and classifying relationships between entities. Topics: Relation Classification, Dependency Parsing · Beginner
- Embedding Generation: creating and managing vector embeddings for semantic search. Topics: Embeddings, OpenAI, HuggingFace · Intermediate
- Vector Store: setting up vector stores for similarity search and retrieval. Intermediate
- Graph Store: persisting knowledge graphs in Neo4j or FalkorDB. Topics: Neo4j, Cypher, Persistence · Intermediate
- Ontology: defining domain schemas and ontologies to structure your data. Topics: OWL, RDF, Schema Design · Intermediate
- Seed Data: bootstrapping a knowledge graph from trusted CSV, JSON, database, and API sources before extraction runs. Topics: SeedDataManager, Foundation Graphs · Intermediate
- Semantic Layer Basics: capstone tutorial that combines a knowledge graph, generated ontology, explicit mappings, ontology-aligned RDF, and a SPARQL query. Topics: Semantic Layer, Ontology Mapping, Oxigraph, SPARQL · Intermediate
Advanced Concepts
Deep dive into advanced features, customization, and complex workflows.
- Advanced Extraction: custom extractors, LLM-based extraction, and complex pattern matching. Topics: Custom Models, Regex, LLMs · Advanced
- Advanced Graph Analytics: centrality, community detection, and pathfinding algorithms. Topics: PageRank, Louvain, Shortest Path · Advanced
- Advanced Context Engineering: persistent memory system for AI agents using FAISS and Neo4j. Topics: Agent Memory, GraphRAG, Entity Injection · Advanced
- Complete Visualization Suite: interactive network, analytics, and temporal visualizations for graphs. Topics: PyVis, NetworkX, D3.js · Intermediate
- Conflict Resolution: strategies for handling contradictory information from multiple sources. Topics: Truth Discovery, Voting, Confidence · Advanced
- Multi-Format Export: exporting to RDF, OWL, JSON-LD, and NetworkX formats. Topics: Serialization, Interoperability · Intermediate
- Multi-Source Integration: merging data from disparate sources into a unified graph. Topics: Entity Resolution, Merging, Fusion · Advanced
- Reasoning and Inference: using logical reasoning to infer new knowledge from existing facts. Topics: Logic Rules, Inference Engines · Advanced
- Temporal Knowledge Graphs: modeling and querying data that changes over time. Topics: Time Series, Temporal Logic, Allen Algebra · Advanced
- Provenance Tracking: W3C PROV-O-aligned lineage tracking and checksum verification for entities, relationships, and chunks. Topics: PROV-O, Lineage, Checksums, Invalidation · Advanced
- Reasoning Module: deriving new knowledge from existing facts with forward chaining, backward chaining, and Datalog strategies. Topics: Reasoner, Datalog, Explanations · Advanced
- Change Management: versioning, audit trails, and data-integrity checks for knowledge graphs and ontologies. Topics: ChangeLogEntry, Version Storage, Data Integrity · Advanced
How to Run
```bash pip install semantica[all] pip install jupyter ``` ```bash git clone https://github.com/semantica-agi/semantica.git cd semantica pip install -e ".[all]" pip install jupyter ``` ```bash jupyter notebook ``` You can also run the cookbook using Docker:docker run -p 8888:8888 semantica/semantica-cookbook