- Fix infinite recursion in semantica/conflicts/methods.py by removing redundant registration
- Update 04_Conflict_Resolution_Strategies.ipynb to use correct API
- Add unit tests for conflicts module in tests/conflicts/test_conflicts.py
- Add __init__.py files to tests/ and tests/conflicts/ for package structure
- Enhanced docs/reference/vector_store.md (~575 lines)
- All 32 classes documented
- All 10 convenience functions
- Complete adapter documentation
- Updated cookbook/introduction/13_Vector_Store.ipynb
- 10-step comprehensive guide
- Created cookbook/advanced/Advanced_Vector_Store_and_Search.ipynb
- 4 focused parts (removed error handling per user request)
- Part 1: Index selection (Flat, HNSW, IVF)
- Part 2: Smart filtering with metadata
- Part 3: Result fusion (RRF, weighted)
- Part 4: Multi-tenant data isolation
- Beginner-friendly with clear examples
- Quick reference guide included
All vector_store documentation complete and production-ready.
BREAKING CHANGE: Removed build() convenience function from semantic_extract module
- Removed build() function from semantic_extract/__init__.py
- Updated __all__ exports to remove 'build'
- Resolved merge conflicts in named_entity_recognizer.py, relation_extractor.py, triple_extractor.py
- Updated semantic_extract_usage.md with class-based examples
- Updated docs/reference/semantic_extract.md with detailed parameter documentation
- Fixed 01_GraphRAG_Complete.ipynb to use individual extractor classes
- Enhanced 05_Entity_Extraction.ipynb with comprehensive examples (9 sections)
- Enhanced 06_Relation_Extraction.ipynb with complete pipeline examples (9 sections)
Users should now use individual classes (NERExtractor, RelationExtractor, TripleExtractor, etc.)
instead of the build() function for better control and flexibility.
Migration guide available in documentation.
- Remove ConflictDetector and Deduplicator from semantica.kg module
- Update all imports to use semantica.conflicts and semantica.deduplication
- Update all notebooks to use class-based API (no convenience functions)
- Fix method signatures: pass graph parameter to methods instead of constructor
- Update calculate_centrality calls to use specific methods (calculate_degree_centrality, etc.)
- Fix detect_communities and analyze_connectivity return value handling
- Update all documentation (kg_usage.md, docs/reference/kg.md)
- Remove conflict_detector.py and deduplicator.py from kg module
- Update registry.py to remove conflict and deduplicate task types
- Remove ConflictDetector and Deduplicator from semantica.kg module
- Update all imports to use dedicated semantica.conflicts and semantica.deduplication modules
- Update all cookbook notebooks to use class-based API instead of convenience functions
- Fix calculate_centrality calls to use specific methods (calculate_degree_centrality, calculate_betweenness_centrality)
- Update detect_communities and analyze_connectivity calls to pass graph parameter
- Update documentation (kg_usage.md, docs/reference/kg.md) to reflect changes
- Remove conflict and deduplicate task types from method registry
- Removed deprecated 'build' convenience function from semantica/ingest/__init__.py to resolve conflicts and promote class-based usage.
- Updated 'docs/reference/ingest.md' to include missing main classes: FeedIngestor, EmailIngestor, DBIngestor, and MCPIngestor.
- Added 'Stream Monitoring' usage example to 'semantica/ingest/ingest_usage.md'.
- Completely rewrote 'cookbook/introduction/02_Data_Ingestion.ipynb' to provide a comprehensive, runnable guide covering all ingestion submodules and helper classes.
- Enhanced Graph Store notebook with comprehensive examples and clean formatting
- Fixed GraphStore API usage across all documentation files
- Updated examples to use keyword arguments (labels, properties, start_node_id, end_node_id, rel_type)
- Removed emojis and links from notebook for cleaner markdown
- Made summary section more concise
- Ensured consistency across cookbook notebooks, docs, and module code
- Enhanced introduction/15_Export.ipynb with complete module architecture documentation
- Enhanced advanced/05_Multi_Format_Export.ipynb with all export formats and classes
- Removed HTMLExporter references from intelligence notebooks (class doesn't exist)
- Fixed OWLExporter usage in healthcare notebook (removed invalid export_knowledge_graph call)
- Updated all notebooks to use only class imports, no convenience functions
- Added comprehensive documentation for all exporter classes and methods
- Improved markdown structure and learning objectives in both notebooks
- Update all notebooks to use generate_embeddings() instead of generate()
- Update docs/reference/embeddings.md to remove references to removed components
- All notebooks now use data_type='text' parameter for embedding generation
- Updated 11 notebooks across introduction, use_cases, and advanced directories
- Restructured 18_Deduplication.ipynb with comprehensive module overview
- Added detailed explanations of module capabilities and architecture
- Improved markdown formatting and removed emojis
- Reorganized content to focus on module capabilities rather than individual classes
- Added clear examples for all major features
- Updated documentation for consistency across all files
Resolved merge conflicts by:
- Removing statistics functionality from ConflictResolver and ConflictAnalyzer
- Removing detect_and_resolve convenience function
- Updating all documentation and examples
- Adding by_source analysis capability
- Updating method signatures to match new API
- Add PyPI installation instructions to all 72 cookbook notebooks
- Update module lists to include all 8 ingestion modules (FileIngestor, WebIngestor, FeedIngestor, StreamIngestor, DBIngestor, RepoIngestor, EmailIngestor, MCPIngestor)
- Reorder sections: Overview before Installation in all notebooks
- Remove duplicate content from introduction notebooks
- Update docs/cookbook.md with PyPI installation section and enhanced module descriptions
- Add numbering to all notebooks for better sorting
- Introduction: 01-19
- Advanced: 01-12
- Use cases: numbered within each category
- Add Google Colab badges to all 72 notebooks
- Clean up Welcome notebook with proper code cells
- Remove unnecessary print statements and verbose content
- Number all introduction notebooks (01-19)
- Number all advanced notebooks (01-12)
- Number all use case notebooks within each category
- Clean up Welcome notebook with proper code cells
- Remove unnecessary print statements
- Improve notebook organization and sorting
- Update mkdocs.yml navigation to use new cookbook index
- Create comprehensive docs/cookbook.md index
- Refactor Welcome_to_Semantica.ipynb to use Markdown cells
- Enhance markdown formatting in Your_First_Knowledge_Graph.ipynb and Financial_Data_Integration.ipynb
- Update custom.css and version-selector.js for better styling
- Populate modules.md, concepts.md, and getting-started.md with detailed content
- Added MCP ingestion as optional data source in Market Intelligence notebook
- Added MCP ingestion as optional data source in Clinical Reports Processing notebook
- Added MCP ingestion as optional data source in Threat Intelligence Hybrid RAG notebook
- Added MCP ingestion as optional data source in Drug Discovery Pipeline notebook
- Updated module lists and pipeline descriptions to include MCP
- Integrated MCP data merging with existing ingestion methods
- Healthcare GraphRAG System: Hybrid GraphRAG with materialized KGs and virtual EHRs
- Supply Chain Risk Management: Graph-based risk analysis with cascade effects
- Network Analysis Intelligence Reports: Graph analytics + AI for intelligence reporting
All notebooks use Semantica as the core framework and toolkit, demonstrating:
- End-to-end pipelines using Semantica modules
- Graph analytics, reasoning, and visualization
- Professional report generation
- Best practices and deployment recommendations
- Implemented all 25 use case notebooks across 5 domains (Trading, Healthcare, Finance, Cybersecurity, Renewable Energy)
- Added real data sources: APIs, RSS feeds, database connections, streaming sources
- Each notebook uses 20+ Semantica modules with complete end-to-end pipelines
- Multi-source ingestion with lists of URLs for feeds and APIs
- Complete workflows: ingestion → parsing → extraction → KG building → analysis → export → visualization
- All notebooks include realistic data structures and error handling
- Updated renewable energy notebooks: Environmental_Impact, Grid_Management, Resource_Optimization, Supply_Chain_Analysis
KaifAhmad1