semantica/docs/cookbook.md at 0f9a6515270d196eea3e73b09f97b110bf866ebb

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Mohd Kaif 0f9a651527 remove: delete domain-specific use_cases cookbooks and docs (#647 )

Removes all notebooks, data files, and exports under cookbook/use_cases/
(advanced_rag, biomedical, blockchain, capability_gap_defense, cybersecurity,
finance, intelligence, renewable_energy, supply_chain) and the corresponding
docs/use-cases.md page.

Cleans up all references in docs/cookbook.md, docs/docs.json,
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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) - **Need installation help**: see the [Installation Guide](installation) Prerequisites: Python 3.8+, Jupyter, and an API key for your preferred LLM provider.

Featured Recipes

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

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

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

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

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 hawksight/semantica-cookbook

8.0 KiB Raw Blame History

Featured Recipes

Core Tutorials

Advanced Concepts

How to Run

8.0 KiB

Raw Blame History