semantica/docs/cookbook.md

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Cookbook	Interactive Jupyter notebooks covering everything from your first knowledge graph to production GraphRAG systems.	flask

**Where to start:** - **New to Semantica** — begin with [Core Tutorials](#core-tutorials) - **Building an application** — see [Advanced Concepts](#advanced-concepts) or [Industry Use Cases](#industry-use-cases) - **Need installation help** — see the [Installation Guide](installation) Prerequisites: Python 3.8+, Jupyter, and an API key for your preferred LLM provider.

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Featured Recipes

Go from raw text to a queryable knowledge graph in 20 minutes.

**Topics:** Extraction, Graph Construction, Visualization · **Difficulty:** Beginner

Build a production-ready Graph Retrieval Augmented Generation system with hybrid retrieval and logical inference.

**Topics:** RAG, LLMs, Vector Search, Graph Traversal · **Difficulty:** Advanced

Side-by-side benchmark of standard RAG vs. GraphRAG on real-world data.

**Topics:** RAG, GraphRAG, Benchmarking · **Difficulty:** Intermediate

Detect anomalies in streaming data using dynamic knowledge graphs.

**Topics:** Streaming, Security, Dynamic Graphs · **Difficulty:** Advanced

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Core Tutorials

Essential guides to master the Semantica framework.

An interactive introduction to the framework's core philosophy and all modules.

**Topics:** Framework Overview, Architecture · **Difficulty:** Beginner

Loading data from files, web, databases, streams, feeds, repositories, email, and MCP.

**Topics:** FileIngestor, WebIngestor, DBIngestor, Streams · **Difficulty:** Beginner

Extracting clean text from complex formats like PDF, DOCX, and HTML.

**Topics:** OCR, PDF Parsing, Text Extraction · **Difficulty:** Beginner

Pipelines for cleaning, normalizing, and preparing text.

**Topics:** Text Cleaning, Unicode, Formatting · **Difficulty:** Beginner

Using NER to identify people, organizations, and custom entities.

**Topics:** NER, spaCy, LLM Extraction · **Difficulty:** Beginner

Discovering and classifying relationships between entities.

**Topics:** Relation Classification, Dependency Parsing · **Difficulty:** Beginner

Creating and managing vector embeddings for semantic search.

**Topics:** Embeddings, OpenAI, HuggingFace · **Difficulty:** Intermediate

Setting up vector stores for similarity search and retrieval.

**Difficulty:** Intermediate

Persisting knowledge graphs in Neo4j or FalkorDB.

**Topics:** Neo4j, Cypher, Persistence · **Difficulty:** Intermediate

Defining domain schemas and ontologies to structure your data.

**Topics:** OWL, RDF, Schema Design · **Difficulty:** Intermediate

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Advanced Concepts

Deep dive into advanced features, customization, and complex workflows.

Custom extractors, LLM-based extraction, and complex pattern matching.

**Topics:** Custom Models, Regex, LLMs · **Difficulty:** Advanced

Centrality, community detection, and pathfinding algorithms.

**Topics:** PageRank, Louvain, Shortest Path · **Difficulty:** Advanced

Production-grade memory system for AI agents using FAISS and Neo4j.

**Topics:** Agent Memory, GraphRAG, Entity Injection · **Difficulty:** Advanced

Interactive, publication-ready visualizations of your graphs.

**Topics:** PyVis, NetworkX, D3.js · **Difficulty:** Intermediate

Strategies for handling contradictory information from multiple sources.

**Topics:** Truth Discovery, Voting, Confidence · **Difficulty:** Advanced

Exporting to RDF, OWL, JSON-LD, and NetworkX formats.

**Topics:** Serialization, Interoperability · **Difficulty:** Intermediate

Merging data from disparate sources into a unified graph.

**Topics:** Entity Resolution, Merging, Fusion · **Difficulty:** Advanced

Building robust, automated data processing pipelines.

**Topics:** Workflows, Automation, Error Handling · **Difficulty:** Advanced

Using logical reasoning to infer new knowledge from existing facts.

**Topics:** Logic Rules, Inference Engines · **Difficulty:** Advanced

Modeling and querying data that changes over time.

**Topics:** Time Series, Temporal Logic, Allen Algebra · **Difficulty:** Advanced

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Industry Use Cases

Biomedical

Accelerating drug discovery by connecting genes, proteins, and drugs using PubMed RSS feeds, entity-aware chunking, GraphRAG, and vector similarity search.

**Topics:** Bioinformatics, KG Construction, GraphRAG · **Difficulty:** Advanced

Analyzing genomic variants and their implications using bioRxiv RSS feeds, temporal KGs, deduplication, and pathway analysis.

**Topics:** Genomics, Temporal KGs, Graph Analytics · **Difficulty:** Advanced

Finance

Merging financial data from Alpha Vantage API, MCP servers, RSS feeds, and market feeds.

**Topics:** Finance, Data Fusion, MCP Integration · **Difficulty:** Intermediate

Identifying fraudulent activities in transaction networks using temporal KGs, conflict detection, and pattern recognition.

**Topics:** Anomaly Detection, Graph Mining, Temporal Analysis · **Difficulty:** Advanced

Blockchain

Analyzing decentralized finance protocols and transaction flows using CoinDesk RSS feeds, ontology-aware chunking, and conflict detection.

**Topics:** Blockchain, DeFi, Smart Contracts, Ontology · **Difficulty:** Advanced

Mapping and analyzing blockchain transaction networks using deduplication and network pattern detection.

**Topics:** Blockchain Analytics, Network Analysis · **Difficulty:** Advanced

Cybersecurity

Detecting anomalies in real-time network traffic streams using CVE RSS feeds, Kafka streams, and temporal KGs.

**Topics:** Network Security, Streaming, Temporal KGs · **Difficulty:** Advanced

Combining enhanced GraphRAG with threat intelligence for security insights.

**Topics:** Threat Intelligence, GraphRAG, Hybrid Retrieval · **Difficulty:** Advanced

Intelligence

Analyze criminal networks with graph analytics and key player detection using OSINT RSS feeds and network centrality analysis.

**Topics:** Forensics, Social Network Analysis · **Difficulty:** Advanced

Comprehensive intelligence analysis using pipeline orchestrator with multiple RSS feeds and multi-source integration.

**Topics:** Intelligence Analysis, Pipeline Orchestration · **Difficulty:** Advanced

Renewable Energy & Supply Chain

Analyzing trends and pricing in the renewable energy market using EIA API, temporal KGs, and TemporalPatternDetector.

**Topics:** Energy, Time Series, Temporal Analysis · **Difficulty:** Intermediate

Integrating supply chain data to optimize logistics and reduce risk.

**Topics:** Logistics, Risk Management, Deduplication · **Difficulty:** Advanced

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How to Run

```bash pip install semantica[all] pip install jupyter ``` ```bash git clone https://github.com/Hawksight-AI/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 hawksight/semantica-cookbook