- Added executable Python code cells to all three getting started notebooks
- Improved markdown formatting with consistent header hierarchy
- Removed excessive comments from code cells for better readability
- Added markdown explanation cells between code sections
- Enhanced documentation structure and clarity
- Split graph_analyzer.py into separate modules:
- centrality_calculator.py: Centrality measures calculation
- community_detector.py: Community detection algorithms
- connectivity_analyzer.py: Connectivity analysis
- Add missing files from development roadmap:
- Utils module: validators.py, helpers.py, types.py
- Parse module: pdf_parser.py, docx_parser.py, pptx_parser.py, etc.
- Normalize module: text_cleaner.py, language_detector.py, encoding_handler.py
- Split module: sliding_window_chunker.py, semantic_chunker.py, etc.
- Semantic extract module: ner_extractor.py, relation_extractor.py, etc.
- Ontology module: class_inferrer.py, property_generator.py, etc.
- Triple store module: base_adapter.py, blazegraph_adapter.py, etc.
- KG module: graph_builder.py, entity_resolver.py, etc.
- Embeddings module: text_embedder.py, image_embedder.py, etc.
- Vector store module: base_adapter.py, pinecone_adapter.py, etc.
- Reasoning module: inference_engine.py, sparql_reasoner.py, etc.
- Pipeline module: execution_engine.py, failure_handler.py, etc.
- Streaming module: kafka_adapter.py, pulsar_adapter.py, etc.
- Monitoring module: analytics_dashboard.py, quality_assurance.py, etc.
- Export module: json_exporter.py, csv_exporter.py, etc.
- Cookbook examples and use cases
- Jupyter notebooks for tutorials and experiments
- All files include comprehensive docstrings and TODO comments
- Maintains modular design and separation of concerns
Mohd Kaif