diff --git a/Modules.md b/Modules.md
index 5dbe9e87..e3c2b395 100644
--- a/Modules.md
+++ b/Modules.md
@@ -1161,6 +1161,615 @@ answer = rag.process_question(question, context=market_data)
 
 ---
 
+## 🔧 Complete Functions Reference
+
+### Module-by-Module Function Tables
+
+#### 1. **Core Engine Functions** (`semantica.core`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `Semantica.initialize()` | core | Setup all modules and connections | None | Status |
+| `Semantica.build_knowledge_base()` | core | Process data sources into knowledge base | sources: List[str] | KnowledgeBase |
+| `Semantica.get_status()` | core | Get system health and metrics | None | Dict |
+| `Semantica.create_pipeline()` | core | Create processing pipeline | config: Dict | Pipeline |
+| `Semantica.get_config()` | core | Get current configuration | None | Config |
+| `Semantica.list_plugins()` | core | List available plugins | None | List[Plugin] |
+| `Config.validate()` | config_manager | Validate configuration against schema | schema: str | bool |
+| `PluginManager.load_plugin()` | plugin_registry | Dynamically load plugin modules | name: str, version: str | Plugin |
+| `PluginManager.list_plugins()` | plugin_registry | Show available plugins and versions | None | List[Plugin] |
+| `Orchestrator.schedule_pipeline()` | orchestrator | Schedule pipeline execution | pipeline_config: Dict | PipelineID |
+| `Orchestrator.monitor_progress()` | orchestrator | Monitor pipeline progress | pipeline_id: str | Progress |
+| `LifecycleManager.startup()` | lifecycle | Execute startup hooks | None | Status |
+| `LifecycleManager.shutdown()` | lifecycle | Execute shutdown hooks | None | Status |
+
+#### 2. **Pipeline Builder Functions** (`semantica.pipeline`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `PipelineBuilder.add_step()` | pipeline | Add processing step to pipeline | name: str, config: Dict | PipelineBuilder |
+| `PipelineBuilder.set_parallelism()` | pipeline | Configure parallel execution | level: int | PipelineBuilder |
+| `PipelineBuilder.build()` | pipeline | Build the pipeline | None | Pipeline |
+| `Pipeline.run()` | execution_engine | Execute complete pipeline | None | Results |
+| `Pipeline.pause()` | execution_engine | Pause pipeline execution | None | Status |
+| `Pipeline.resume()` | execution_engine | Resume paused pipeline | None | Status |
+| `Pipeline.stop()` | execution_engine | Stop pipeline execution | None | Status |
+| `ExecutionEngine.execute_pipeline()` | execution_engine | Execute pipeline with config | config: Dict | Results |
+| `FailureHandler.retry_step()` | failure_handler | Retry failed step | step_id: str, error: Exception | Status |
+| `FailureHandler.handle_error()` | failure_handler | Handle execution errors | error: Exception | RecoveryPlan |
+| `ParallelExecutor.execute_parallel()` | parallelism_manager | Execute tasks in parallel | tasks: List[Task] | Results |
+| `ResourceScheduler.allocate_cpu()` | resource_scheduler | Allocate CPU resources | cores: int | ResourceID |
+| `ResourceScheduler.allocate_gpu()` | resource_scheduler | Allocate GPU resources | device_id: int | ResourceID |
+| `PipelineValidator.validate_pipeline()` | pipeline_validator | Validate pipeline configuration | config: Dict | ValidationResult |
+
+#### 3. **Data Ingestion Functions** (`semantica.ingest`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `FileIngestor.scan_directory()` | file | Recursively scan directory for files | path: str, recursive: bool | List[File] |
+| `FileIngestor.detect_format()` | file | Auto-detect file type and encoding | file_path: str | FileFormat |
+| `WebIngestor.crawl_site()` | web | Crawl website with depth and rate limiting | url: str, max_depth: int | WebContent |
+| `WebIngestor.extract_links()` | web | Extract and follow hyperlinks | content: WebContent | List[Link] |
+| `FeedIngestor.parse_rss()` | feed | Parse RSS/Atom feeds with metadata | feed_url: str | FeedData |
+| `StreamIngestor.connect()` | stream | Establish real-time data connection | config: Dict | StreamConnection |
+| `RepoIngestor.clone_repo()` | repo | Clone and track repository changes | repo_url: str | Repository |
+| `EmailIngestor.connect_imap()` | email | Connect to email server | server: str, credentials: Dict | EmailConnection |
+| `DBIngestor.export_table()` | db_export | Export database table to structured format | table: str, query: str | StructuredData |
+| `IngestManager.resume_from_token()` | ingest | Resume interrupted ingestion | token: str | Status |
+| `IngestManager.get_progress()` | ingest | Monitor ingestion progress | None | Progress |
+| `ConnectorRegistry.register()` | ingest | Register custom data connectors | connector: Connector | Status |
+
+#### 4. **Document Parsing Functions** (`semantica.parse`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `PDFParser.extract_text()` | pdf | Extract text with positioning and formatting | file_path: str | TextContent |
+| `PDFParser.extract_tables()` | pdf | Extract tables using Camelot/Tabula | file_path: str | List[Table] |
+| `PDFParser.extract_images()` | pdf | Extract embedded images and figures | file_path: str | List[Image] |
+| `DOCXParser.get_document_structure()` | docx | Extract document outline and sections | file_path: str | DocumentStructure |
+| `DOCXParser.extract_track_changes()` | docx | Extract revision history | file_path: str | TrackChanges |
+| `PPTXParser.extract_slides()` | pptx | Extract slide content and speaker notes | file_path: str | List[Slide] |
+| `ExcelParser.read_sheet()` | excel | Read specific worksheet with data types | file_path: str, sheet: str | Worksheet |
+| `ExcelParser.extract_charts()` | excel | Extract chart data and metadata | file_path: str | List[Chart] |
+| `HTMLParser.parse_dom()` | html | Parse HTML into structured DOM tree | url: str | DOMTree |
+| `HTMLParser.extract_metadata()` | html | Extract meta tags and structured data | dom: DOMTree | Metadata |
+| `ImageParser.ocr_text()` | images | Perform OCR using Tesseract/Google Vision | image_path: str | TextContent |
+| `ImageParser.detect_objects()` | images | Detect objects and faces in images | image_path: str | List[Object] |
+| `TableParser.detect_structure()` | tables | Detect table boundaries and headers | content: str | TableStructure |
+| `TableParser.extract_cells()` | tables | Extract individual cell data | table: Table | List[Cell] |
+| `ParserRegistry.get_parser()` | parse | Get appropriate parser for file type | file_type: str | Parser |
+| `ParserRegistry.supported_formats()` | parse | List all supported file formats | None | List[str] |
+
+#### 5. **Text Normalization Functions** (`semantica.normalize`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `TextCleaner.remove_html()` | text_cleaner | Strip HTML tags and preserve text content | html: str | str |
+| `TextCleaner.normalize_whitespace()` | text_cleaner | Standardize spacing and line breaks | text: str | str |
+| `TextCleaner.remove_special_chars()` | text_cleaner | Clean special characters and symbols | text: str | str |
+| `LanguageDetector.detect()` | language_detector | Identify text language with confidence score | text: str | Language |
+| `LanguageDetector.supported_languages()` | language_detector | List all supported languages | None | List[str] |
+| `EncodingHandler.normalize()` | encoding_handler | Convert to UTF-8 and validate encoding | text: bytes | str |
+| `EncodingHandler.detect_encoding()` | encoding_handler | Auto-detect file encoding | file_path: str | str |
+| `EntityNormalizer.canonicalize()` | entity_normalizer | Standardize entity names and aliases | entity: str, alias: str | str |
+| `EntityNormalizer.expand_acronyms()` | entity_normalizer | Expand abbreviations and acronyms | text: str | str |
+| `DateNormalizer.parse_date()` | date_normalizer | Parse various date formats to ISO standard | date_str: str | datetime |
+| `DateNormalizer.resolve_relative()` | date_normalizer | Convert relative dates to absolute | date_str: str | datetime |
+| `NumberNormalizer.standardize()` | number_normalizer | Convert numbers to standard format | number: str | str |
+| `NumberNormalizer.convert_units()` | number_normalizer | Convert between measurement units | value: float, from_unit: str, to_unit: str | float |
+| `NormalizationPipeline.run()` | normalize | Execute complete normalization pipeline | text: str | NormalizedText |
+| `NormalizationPipeline.get_stats()` | normalize | Return normalization statistics | None | Dict |
+
+#### 6. **Text Chunking Functions** (`semantica.split`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `SlidingWindowChunker.split()` | sliding_window | Create fixed-size chunks with overlap | text: str, size: int, overlap: int | List[Chunk] |
+| `SlidingWindowChunker.set_window_size()` | sliding_window | Configure chunk size and overlap | size: int, overlap: int | None |
+| `SemanticChunker.split_by_meaning()` | semantic_chunker | Split based on semantic boundaries | text: str | List[Chunk] |
+| `SemanticChunker.detect_topics()` | semantic_chunker | Identify topic changes for splitting | text: str | List[Topic] |
+| `StructuralChunker.split_by_sections()` | structural_chunker | Split on document structure | document: Document | List[Chunk] |
+| `StructuralChunker.identify_headers()` | structural_chunker | Detect section headers and levels | document: Document | List[Header] |
+| `TableChunker.preserve_tables()` | table_chunker | Keep tables intact during splitting | document: Document | List[Chunk] |
+| `TableChunker.extract_table_context()` | table_chunker | Extract surrounding context for tables | table: Table | str |
+| `ProvenanceTracker.track_source()` | provenance_tracker | Track original source and position | chunk: Chunk | Provenance |
+| `ProvenanceTracker.get_provenance()` | provenance_tracker | Retrieve chunk source information | chunk_id: str | Provenance |
+| `ChunkValidator.validate_chunk()` | chunk_validator | Validate chunk quality and size | chunk: Chunk | ValidationResult |
+| `ChunkValidator.detect_overlaps()` | chunk_validator | Find overlapping chunks | chunks: List[Chunk] | List[Overlap] |
+| `SplitManager.run_strategy()` | split | Execute chosen splitting strategy | text: str, strategy: str | List[Chunk] |
+| `SplitManager.get_chunk_stats()` | split | Return chunking statistics | None | Dict |
+
+#### 7. **Semantic Extraction Functions** (`semantica.semantic_extract`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `NERExtractor.extract_entities()` | ner_extractor | Extract named entities with types and confidence | text: str | List[Entity] |
+| `NERExtractor.classify_entities()` | ner_extractor | Classify entities into predefined categories | entities: List[Entity] | List[ClassifiedEntity] |
+| `RelationExtractor.find_relations()` | relation_extractor | Detect relationships between entities | text: str | List[Relation] |
+| `RelationExtractor.classify_relations()` | relation_extractor | Classify relation types and directions | relations: List[Relation] | List[ClassifiedRelation] |
+| `EventDetector.detect_events()` | event_detector | Identify events and their participants | text: str | List[Event] |
+| `EventDetector.extract_temporal()` | event_detector | Extract temporal information for events | events: List[Event] | List[TemporalInfo] |
+| `CorefResolver.resolve_references()` | coref_resolver | Resolve co-references and pronouns | text: str | List[Resolution] |
+| `CorefResolver.link_entities()` | coref_resolver | Link entities across document sections | entities: List[Entity] | List[Link] |
+| `TripleExtractor.extract_triples()` | triple_extractor | Extract RDF-style triples | text: str | List[Triple] |
+| `TripleExtractor.validate_triples()` | triple_extractor | Validate triple structure and consistency | triples: List[Triple] | List[ValidatedTriple] |
+| `LLMEnhancer.enhance_extraction()` | llm_enhancer | Use LLM for complex extraction tasks | text: str, task: str | EnhancedResults |
+| `LLMEnhancer.detect_patterns()` | llm_enhancer | Identify complex patterns and relationships | text: str | List[Pattern] |
+| `ExtractionValidator.validate_quality()` | extraction_validator | Assess extraction quality | results: ExtractionResults | QualityScore |
+| `ExtractionValidator.filter_by_confidence()` | extraction_validator | Filter results by confidence score | results: List[Result], threshold: float | List[Result] |
+| `ExtractionPipeline.run()` | semantic_extract | Execute complete extraction pipeline | text: str | ExtractionResults |
+
+#### 8. **Ontology Generation Functions** (`semantica.ontology`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `ClassInferrer.infer_classes()` | class_inferrer | Automatically discover entity classes | entities: List[Entity] | List[Class] |
+| `ClassInferrer.build_hierarchy()` | class_inferrer | Build class inheritance hierarchy | classes: List[Class] | Hierarchy |
+| `ClassInferrer.analyze_relationships()` | class_inferrer | Analyze class relationships and dependencies | classes: List[Class] | List[Relationship] |
+| `PropertyGenerator.infer_properties()` | property_generator | Infer object and data properties | classes: List[Class] | List[Property] |
+| `PropertyGenerator.detect_data_types()` | property_generator | Detect property data types and constraints | properties: List[Property] | List[DataType] |
+| `PropertyGenerator.analyze_cardinality()` | property_generator | Analyze property cardinality | properties: List[Property] | List[Cardinality] |
+| `OWLGenerator.generate_owl()` | owl_generator | Generate OWL ontology in RDF/XML format | ontology: Ontology | str |
+| `OWLGenerator.serialize_rdf()` | owl_generator | Serialize to various RDF formats | ontology: Ontology, format: str | str |
+| `BaseMapper.map_to_schema_org()` | base_mapper | Map entities to schema.org vocabulary | entities: List[Entity] | List[Mapping] |
+| `BaseMapper.map_to_foaf()` | base_mapper | Map to FOAF ontology | entities: List[Entity] | List[Mapping] |
+| `BaseMapper.map_to_dublin_core()` | base_mapper | Map to Dublin Core metadata standards | entities: List[Entity] | List[Mapping] |
+| `VersionManager.create_version()` | version_manager | Create new ontology version | ontology: Ontology | Version |
+| `VersionManager.track_changes()` | version_manager | Track changes between versions | old_version: Version, new_version: Version | List[Change] |
+| `VersionManager.migrate_ontology()` | version_manager | Support ontology migration and updates | old_ontology: Ontology, new_schema: Schema | Ontology |
+| `OntologyValidator.validate_schema()` | ontology_validator | Validate ontology schema consistency | ontology: Ontology | ValidationResult |
+| `OntologyValidator.check_constraints()` | ontology_validator | Check ontology constraint violations | ontology: Ontology | List[Violation] |
+| `DomainOntologies.get_finance_ontology()` | domain_ontologies | Get pre-built financial ontology | None | Ontology |
+| `DomainOntologies.get_healthcare_ontology()` | domain_ontologies | Get pre-built healthcare ontology | None | Ontology |
+| `OntologyManager.build_ontology()` | ontology | Build complete ontology from extracted data | data: ExtractedData | Ontology |
+| `OntologyManager.export_ontology()` | ontology | Export ontology in various formats | ontology: Ontology, format: str | str |
+
+#### 9. **Knowledge Graph Functions** (`semantica.kg`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `GraphBuilder.create_node()` | graph_builder | Create knowledge graph node | id: str, type: str, properties: Dict | Node |
+| `GraphBuilder.create_edge()` | graph_builder | Create relationship edge between nodes | from_node: str, to_node: str, relation: str | Edge |
+| `GraphBuilder.build_subgraph()` | graph_builder | Build subgraph from specific entities | entities: List[Entity] | SubGraph |
+| `GraphBuilder.merge_graphs()` | graph_builder | Merge multiple knowledge graphs | graphs: List[Graph] | Graph |
+| `EntityResolver.resolve_identity()` | entity_resolver | Resolve entity identity across sources | entity1: Entity, entity2: Entity | Resolution |
+| `EntityResolver.merge_entities()` | entity_resolver | Merge duplicate entities | entities: List[Entity] | MergedEntity |
+| `EntityResolver.get_canonical()` | entity_resolver | Get canonical entity representation | entity: Entity | Entity |
+| `Deduplicator.find_duplicates()` | deduplicator | Find duplicate entities | entities: List[Entity] | List[Duplicate] |
+| `Deduplicator.merge_duplicates()` | deduplicator | Merge duplicate entities | duplicates: List[Duplicate] | List[MergedEntity] |
+| `Deduplicator.validate_merge()` | deduplicator | Validate merge operation | merge: MergeOperation | ValidationResult |
+| `SeedManager.load_seed_data()` | seed_manager | Load initial seed data | data_source: str | SeedData |
+| `SeedManager.validate_seed_data()` | seed_manager | Validate seed data quality | seed_data: SeedData | ValidationResult |
+| `SeedManager.update_seed_data()` | seed_manager | Update existing seed data | seed_data: SeedData | Status |
+| `ProvenanceTracker.track_source()` | provenance_tracker | Track information source | information: Information | Provenance |
+| `ProvenanceTracker.get_provenance()` | provenance_tracker | Retrieve provenance information | info_id: str | Provenance |
+| `ProvenanceTracker.calculate_confidence()` | provenance_tracker | Calculate confidence scores | provenance: Provenance | float |
+| `ConflictDetector.detect_conflicts()` | conflict_detector | Detect conflicts between sources | sources: List[Source] | List[Conflict] |
+| `ConflictDetector.classify_severity()` | conflict_detector | Classify conflict severity | conflict: Conflict | Severity |
+| `ConflictDetector.create_resolution_workflow()` | conflict_detector | Create resolution workflow | conflicts: List[Conflict] | Workflow |
+| `GraphValidator.validate_consistency()` | graph_validator | Validate graph consistency | graph: Graph | ValidationResult |
+| `GraphValidator.check_schema_compliance()` | graph_validator | Check schema compliance | graph: Graph, schema: Schema | ComplianceResult |
+| `GraphValidator.calculate_quality_metrics()` | graph_validator | Calculate quality metrics | graph: Graph | QualityMetrics |
+| `GraphAnalyzer.calculate_centrality()` | graph_analyzer | Calculate node centrality | graph: Graph | CentralityScores |
+| `GraphAnalyzer.detect_communities()` | graph_analyzer | Detect community structures | graph: Graph | List[Community] |
+| `GraphAnalyzer.analyze_connectivity()` | graph_analyzer | Analyze graph connectivity | graph: Graph | ConnectivityMetrics |
+| `KnowledgeGraphManager.build_graph()` | kg | Build complete knowledge graph | data: ProcessedData | KnowledgeGraph |
+| `KnowledgeGraphManager.export_graph()` | kg | Export graph in various formats | graph: Graph, format: str | str |
+| `KnowledgeGraphManager.visualize_graph()` | kg | Generate graph visualizations | graph: Graph | Visualization |
+
+#### 10. **Vector Store Functions** (`semantica.vector_store`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `PineconeAdapter.connect()` | pinecone_adapter | Connect to Pinecone service | api_key: str | Connection |
+| `PineconeAdapter.create_index()` | pinecone_adapter | Create new vector index | name: str, dimension: int | Index |
+| `PineconeAdapter.upsert_vectors()` | pinecone_adapter | Insert or update vectors | vectors: List[Vector], metadata: Dict | Status |
+| `PineconeAdapter.query_vectors()` | pinecone_adapter | Query similar vectors | query_vector: Vector, top_k: int | List[Result] |
+| `FAISSAdapter.create_index()` | faiss_adapter | Create FAISS index | index_type: str, dimension: int | Index |
+| `FAISSAdapter.add_vectors()` | faiss_adapter | Add vectors to index | vectors: List[Vector] | Status |
+| `FAISSAdapter.search_similar()` | faiss_adapter | Search for similar vectors | query_vector: Vector, k: int | List[Result] |
+| `FAISSAdapter.save_index()` | faiss_adapter | Save index to disk | file_path: str | Status |
+| `MilvusAdapter.create_collection()` | milvus_adapter | Create Milvus collection | name: str, schema: Schema | Collection |
+| `MilvusAdapter.insert_vectors()` | milvus_adapter | Insert vectors into collection | vectors: List[Vector] | Status |
+| `MilvusAdapter.search_vectors()` | milvus_adapter | Search vectors in collection | query_vector: Vector, top_k: int | List[Result] |
+| `WeaviateAdapter.create_schema()` | weaviate_adapter | Create Weaviate schema | schema: Schema | Status |
+| `WeaviateAdapter.add_objects()` | weaviate_adapter | Add objects to Weaviate | objects: List[Object] | Status |
+| `WeaviateAdapter.graphql_query()` | weaviate_adapter | Execute GraphQL queries | query: str | QueryResult |
+| `QdrantAdapter.create_collection()` | qdrant_adapter | Create Qdrant collection | name: str, config: Dict | Collection |
+| `QdrantAdapter.upsert_points()` | qdrant_adapter | Insert or update points | points: List[Point] | Status |
+| `QdrantAdapter.search_points()` | qdrant_adapter | Search points with filters | query: Vector, filters: Dict | List[Result] |
+| `NamespaceManager.create_namespace()` | namespace_manager | Create isolated namespace | name: str | Namespace |
+| `NamespaceManager.set_access_control()` | namespace_manager | Set namespace permissions | namespace: str, permissions: Dict | Status |
+| `NamespaceManager.list_namespaces()` | namespace_manager | List available namespaces | None | List[Namespace] |
+| `MetadataStore.index_metadata()` | metadata_store | Index metadata for search | metadata: Dict | Status |
+| `MetadataStore.filter_by_metadata()` | metadata_store | Filter results by metadata | filters: Dict | List[Result] |
+| `MetadataStore.search_metadata()` | metadata_store | Search metadata content | query: str | List[Result] |
+| `HybridSearch.combine_results()` | hybrid_search | Combine vector and metadata results | vector_results: List, metadata_results: List | List[Result] |
+| `HybridSearch.rank_results()` | hybrid_search | Rank results using multiple criteria | results: List[Result] | List[RankedResult] |
+| `HybridSearch.fuse_results()` | hybrid_search | Fuse results from different sources | results: List[List[Result]] | List[FusedResult] |
+| `IndexOptimizer.optimize_index()` | index_optimizer | Optimize index performance | index: Index | OptimizedIndex |
+| `IndexOptimizer.rebuild_index()` | index_optimizer | Rebuild index for better performance | index: Index | Index |
+| `IndexOptimizer.get_performance_metrics()` | index_optimizer | Get index performance metrics | index: Index | Metrics |
+| `VectorStoreManager.get_store_info()` | vector_store | Get store information | None | StoreInfo |
+| `VectorStoreManager.backup_store()` | vector_store | Create store backup | backup_path: str | Status |
+| `VectorStoreManager.restore_store()` | vector_store | Restore from backup | backup_path: str | Status |
+
+#### 11. **Triple Store Functions** (`semantica.triple_store`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `BlazegraphAdapter.connect()` | blazegraph_adapter | Connect to Blazegraph instance | endpoint: str | Connection |
+| `BlazegraphAdapter.execute_sparql()` | blazegraph_adapter | Execute SPARQL queries | query: str | QueryResult |
+| `BlazegraphAdapter.bulk_load()` | blazegraph_adapter | Load triples in bulk | triples: List[Triple] | Status |
+| `JenaAdapter.create_model()` | jena_adapter | Create and manage RDF models | None | Model |
+| `JenaAdapter.add_triples()` | jena_adapter | Add triples to model | model: Model, triples: List[Triple] | Status |
+| `JenaAdapter.run_inference()` | jena_adapter | Execute inference rules | model: Model | InferredModel |
+| `RDF4JAdapter.create_repository()` | rdf4j_adapter | Create and configure repositories | config: Dict | Repository |
+| `RDF4JAdapter.begin_transaction()` | rdf4j_adapter | Start transaction for batch operations | None | Transaction |
+| `GraphDBAdapter.enable_reasoning()` | graphdb_adapter | Enable reasoning capabilities | config: Dict | Status |
+| `GraphDBAdapter.visualize_graph()` | graphdb_adapter | Generate graph visualizations | query: str | Visualization |
+| `VirtuosoAdapter.connect_cluster()` | virtuoso_adapter | Connect to Virtuoso cluster | cluster_config: Dict | Connection |
+| `VirtuosoAdapter.optimize_queries()` | virtuoso_adapter | Optimize query performance | queries: List[str] | OptimizedQueries |
+| `TripleManager.add_triple()` | triple_manager | Add single triple to store | triple: Triple | Status |
+| `TripleManager.add_triples()` | triple_manager | Add multiple triples | triples: List[Triple] | Status |
+| `TripleManager.delete_triple()` | triple_manager | Delete specific triple | triple: Triple | Status |
+| `TripleManager.update_triple()` | triple_manager | Update existing triple | old_triple: Triple, new_triple: Triple | Status |
+| `QueryEngine.execute_sparql()` | query_engine | Execute SPARQL queries | query: str | QueryResult |
+| `QueryEngine.optimize_query()` | query_engine | Optimize query for performance | query: str | OptimizedQuery |
+| `QueryEngine.format_results()` | query_engine | Format query results | results: QueryResult, format: str | FormattedResults |
+| `BulkLoader.load_file()` | bulk_loader | Load triples from file | file_path: str | Status |
+| `BulkLoader.create_indexes()` | bulk_loader | Create database indexes | None | Status |
+| `BulkLoader.monitor_progress()` | bulk_loader | Monitor loading progress | None | Progress |
+| `TripleStoreManager.get_store_info()` | triple_store | Get store statistics and status | None | StoreInfo |
+| `TripleStoreManager.backup_store()` | triple_store | Create backup of store | backup_path: str | Status |
+| `TripleStoreManager.restore_store()` | triple_store | Restore from backup | backup_path: str | Status |
+
+#### 12. **Embeddings Functions** (`semantica.embeddings`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `TextEmbedder.embed_text()` | text_embedder | Generate text embeddings | text: str | Vector |
+| `TextEmbedder.embed_sentence()` | text_embedder | Generate sentence-level embeddings | sentence: str | Vector |
+| `TextEmbedder.embed_document()` | text_embedder | Generate document-level embeddings | document: str | Vector |
+| `ImageEmbedder.embed_image()` | image_embedder | Generate image embeddings | image_path: str | Vector |
+| `ImageEmbedder.extract_features()` | image_embedder | Extract visual features | image_path: str | Features |
+| `ImageEmbedder.embed_batch()` | image_embedder | Process multiple images | image_paths: List[str] | List[Vector] |
+| `AudioEmbedder.embed_audio()` | audio_embedder | Generate audio embeddings | audio_path: str | Vector |
+| `AudioEmbedder.extract_audio_features()` | audio_embedder | Extract audio features | audio_path: str | Features |
+| `MultimodalEmbedder.fuse_embeddings()` | multimodal_embedder | Fuse multiple modality embeddings | embeddings: List[Vector] | FusedVector |
+| `MultimodalEmbedder.align_modalities()` | multimodal_embedder | Align different modality representations | modalities: List[Vector] | AlignedVectors |
+| `ContextManager.set_window_size()` | context_manager | Set context window size | size: int | None |
+| `ContextManager.apply_sliding_window()` | context_manager | Apply sliding window approach | text: str | List[Window] |
+| `ContextManager.manage_attention()` | context_manager | Manage attention mechanisms | config: Dict | AttentionWeights |
+| `PoolingStrategies.mean_pooling()` | pooling_strategies | Apply mean pooling strategy | vectors: List[Vector] | Vector |
+| `PoolingStrategies.max_pooling()` | pooling_strategies | Apply max pooling strategy | vectors: List[Vector] | Vector |
+| `PoolingStrategies.attention_pooling()` | pooling_strategies | Apply attention-based pooling | vectors: List[Vector], weights: List[float] | Vector |
+| `ProviderAdapter.connect_openai()` | provider_adapter | Connect to OpenAI embedding API | api_key: str | Connection |
+| `ProviderAdapter.connect_bge()` | provider_adapter | Connect to BGE embedding service | endpoint: str | Connection |
+| `ProviderAdapter.connect_llama()` | provider_adapter | Connect to Llama embedding model | model_path: str | Connection |
+| `ProviderAdapter.load_custom_model()` | provider_adapter | Load custom embedding model | model_config: Dict | Model |
+| `EmbeddingOptimizer.optimize_dimensions()` | embedding_optimizer | Optimize embedding dimensions | vectors: List[Vector], target_dim: int | OptimizedVectors |
+| `EmbeddingOptimizer.apply_clustering()` | embedding_optimizer | Apply clustering to embeddings | vectors: List[Vector] | ClusterResults |
+| `EmbeddingOptimizer.calculate_similarity()` | embedding_optimizer | Calculate embedding similarities | vector1: Vector, vector2: Vector | float |
+| `SemanticEmbedder.generate_embeddings()` | embeddings | Generate embeddings for input | input_data: Any | List[Vector] |
+| `SemanticEmbedder.batch_process()` | embeddings | Process multiple inputs in batch | inputs: List[Any] | List[Vector] |
+| `SemanticEmbedder.get_embedding_stats()` | embeddings | Get embedding statistics | None | Stats |
+
+#### 13. **RAG System Functions** (`semantica.qa_rag`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `RAGManager.process_question()` | qa_rag | Process user question | question: str | Answer |
+| `RAGManager.get_answer()` | qa_rag | Get RAG-generated answer | question: str | Answer |
+| `RAGManager.evaluate_performance()` | qa_rag | Evaluate RAG performance | test_data: List[Question] | PerformanceMetrics |
+| `SemanticChunker.chunk_text()` | semantic_chunker | Create semantic chunks with context | text: str | List[Chunk] |
+| `SemanticChunker.optimize_chunks()` | semantic_chunker | Optimize chunk size and overlap | chunks: List[Chunk] | List[OptimizedChunk] |
+| `SemanticChunker.merge_chunks()` | semantic_chunker | Merge related chunks when needed | chunks: List[Chunk] | List[MergedChunk] |
+| `PromptTemplates.get_template()` | prompt_templates | Get RAG prompt template | template_name: str | Template |
+| `PromptTemplates.format_question()` | prompt_templates | Format question for retrieval | question: str | FormattedQuestion |
+| `PromptTemplates.inject_context()` | prompt_templates | Inject retrieved context into prompt | question: str, context: str | Prompt |
+| `RetrievalPolicies.set_strategy()` | retrieval_policies | Set retrieval strategy | strategy: str | None |
+| `RetrievalPolicies.rank_results()` | retrieval_policies | Rank retrieval results | results: List[Result] | List[RankedResult] |
+| `RetrievalPolicies.filter_results()` | retrieval_policies | Filter results by criteria | results: List[Result], criteria: Dict | List[FilteredResult] |
+| `AnswerBuilder.construct_answer()` | answer_builder | Construct answer from retrieved context | context: List[Chunk], question: str | Answer |
+| `AnswerBuilder.integrate_context()` | answer_builder | Integrate multiple context sources | contexts: List[Context] | IntegratedContext |
+| `AnswerBuilder.attribute_sources()` | answer_builder | Attribute answer to source documents | answer: Answer | AttributedAnswer |
+| `ProvenanceTracker.track_sources()` | provenance_tracker | Track information sources | answer: Answer | List[Source] |
+| `ProvenanceTracker.calculate_confidence()` | provenance_tracker | Calculate answer confidence | answer: Answer | float |
+| `ProvenanceTracker.link_evidence()` | provenance_tracker | Link answer to supporting evidence | answer: Answer | List[Evidence] |
+| `AnswerValidator.validate_answer()` | answer_validator | Validate answer accuracy | answer: Answer | ValidationResult |
+| `AnswerValidator.fact_check()` | answer_validator | Perform fact checking | answer: Answer | FactCheckResult |
+| `AnswerValidator.verify_consistency()` | answer_validator | Verify answer consistency | answer: Answer | ConsistencyResult |
+| `RAGOptimizer.optimize_retrieval()` | rag_optimizer | Optimize retrieval performance | config: Dict | OptimizedConfig |
+| `RAGOptimizer.enhance_queries()` | rag_optimizer | Enhance user queries | query: str | EnhancedQuery |
+| `RAGOptimizer.improve_ranking()` | rag_optimizer | Improve result ranking | results: List[Result] | List[ImprovedResult] |
+| `ConversationManager.start_conversation()` | conversation_manager | Start new conversation | None | Conversation |
+| `ConversationManager.add_context()` | conversation_manager | Add context to conversation | conversation: Conversation, context: str | None |
+| `ConversationManager.get_history()` | conversation_manager | Get conversation history | conversation: Conversation | List[Message] |
+
+#### 14. **Reasoning Engine Functions** (`semantica.reasoning`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `InferenceEngine.add_rule()` | inference_engine | Add inference rule to engine | rule: Rule | Status |
+| `InferenceEngine.execute_rules()` | inference_engine | Execute inference rules | None | List[Inference] |
+| `InferenceEngine.forward_chain()` | inference_engine | Perform forward chaining | None | List[Inference] |
+| `InferenceEngine.backward_chain()` | inference_engine | Perform backward chaining | goal: Goal | List[Inference] |
+| `InferenceEngine.resolve_conflicts()` | inference_engine | Resolve rule conflicts | conflicts: List[Conflict] | Resolution |
+| `SPARQLReasoner.expand_query()` | sparql_reasoner | Expand SPARQL query with reasoning | query: str | ExpandedQuery |
+| `SPARQLReasoner.infer_results()` | sparql_reasoner | Infer additional results | query_results: QueryResult | InferredResults |
+| `SPARQLReasoner.apply_reasoning()` | sparql_reasoner | Apply reasoning to query results | query: str, results: QueryResult | ReasonedResults |
+| `ReteEngine.compile_rules()` | rete_engine | Compile rules into Rete network | rules: List[Rule] | ReteNetwork |
+| `ReteEngine.match_patterns()` | rete_engine | Match patterns using Rete algorithm | facts: List[Fact] | List[Match] |
+| `ReteEngine.execute_matches()` | rete_engine | Execute matched rules | matches: List[Match] | List[Inference] |
+| `AbductiveReasoner.generate_hypotheses()` | abductive_reasoner | Generate explanatory hypotheses | observations: List[Observation] | List[Hypothesis] |
+| `AbductiveReasoner.find_explanations()` | abductive_reasoner | Find explanations for observations | observations: List[Observation] | List[Explanation] |
+| `AbductiveReasoner.rank_hypotheses()` | abductive_reasoner | Rank hypotheses by plausibility | hypotheses: List[Hypothesis] | List[RankedHypothesis] |
+| `DeductiveReasoner.apply_logic()` | deductive_reasoner | Apply logical inference rules | premises: List[Premise] | List[Conclusion] |
+| `DeductiveReasoner.prove_theorem()` | deductive_reasoner | Prove logical theorems | theorem: Theorem | Proof |
+| `DeductiveReasoner.validate_argument()` | deductive_reasoner | Validate logical arguments | argument: Argument | ValidationResult |
+| `RuleManager.define_rule()` | rule_manager | Define new inference rule | rule_definition: str | Rule |
+| `RuleManager.validate_rule()` | rule_manager | Validate rule syntax and logic | rule: Rule | ValidationResult |
+| `RuleManager.track_execution()` | rule_manager | Track rule execution history | rule: Rule | ExecutionHistory |
+| `ReasoningValidator.validate_reasoning()` | reasoning_validator | Validate reasoning process | reasoning: Reasoning | ValidationResult |
+| `ReasoningValidator.check_consistency()` | reasoning_validator | Check reasoning consistency | reasoning: Reasoning | ConsistencyResult |
+| `ReasoningValidator.detect_errors()` | reasoning_validator | Detect reasoning errors | reasoning: Reasoning | List[Error] |
+| `ExplanationGenerator.generate_explanation()` | explanation_generator | Generate reasoning explanation | reasoning: Reasoning | Explanation |
+| `ExplanationGenerator.show_reasoning_path()` | explanation_generator | Show reasoning path | reasoning: Reasoning | ReasoningPath |
+| `ExplanationGenerator.justify_conclusion()` | explanation_generator | Justify reasoning conclusion | conclusion: Conclusion | Justification |
+| `ReasoningManager.run_reasoning()` | reasoning | Run complete reasoning process | input_data: Any | ReasoningResult |
+| `ReasoningManager.get_reasoning_results()` | reasoning | Get reasoning results | reasoning_id: str | ReasoningResult |
+| `ReasoningManager.export_reasoning()` | reasoning | Export reasoning process | reasoning: Reasoning, format: str | str |
+
+#### 15. **Multi-Agent System Functions** (`semantica.agents`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `AgentManager.register_agent()` | agent_manager | Register new agent | agent_config: Dict | Agent |
+| `AgentManager.start_agent()` | agent_manager | Start agent execution | agent: Agent | Status |
+| `AgentManager.stop_agent()` | agent_manager | Stop agent execution | agent_id: str | Status |
+| `AgentManager.monitor_agent()` | agent_manager | Monitor agent status | agent_id: str | AgentStatus |
+| `OrchestrationEngine.coordinate_agents()` | orchestration_engine | Coordinate multiple agents | agents: List[Agent] | Coordination |
+| `OrchestrationEngine.distribute_tasks()` | orchestration_engine | Distribute tasks among agents | tasks: List[Task], agents: List[Agent] | TaskDistribution |
+| `OrchestrationEngine.manage_workflows()` | orchestration_engine | Manage agent workflows | workflow: Workflow | WorkflowStatus |
+| `ToolRegistry.register_tool()` | tool_registry | Register tool for agent use | tool: Tool | Status |
+| `ToolRegistry.discover_tools()` | tool_registry | Discover available tools | None | List[Tool] |
+| `ToolRegistry.get_tool()` | tool_registry | Get specific tool | tool_name: str | Tool |
+| `CostTracker.monitor_costs()` | cost_tracker | Monitor agent execution costs | agent_id: str | CostMetrics |
+| `CostTracker.set_budget()` | cost_tracker | Set cost budget limits | budget: float | Status |
+| `CostTracker.optimize_resources()` | cost_tracker | Optimize resource usage | usage_data: Dict | OptimizationPlan |
+| `SandboxManager.create_sandbox()` | sandbox_manager | Create agent sandbox | config: Dict | Sandbox |
+| `SandboxManager.isolate_agent()` | sandbox_manager | Isolate agent execution | agent: Agent | IsolationStatus |
+| `SandboxManager.set_resource_limits()` | sandbox_manager | Set resource limits | limits: Dict | Status |
+| `WorkflowEngine.define_workflow()` | workflow_engine | Define agent workflow | workflow_definition: Dict | Workflow |
+| `WorkflowEngine.execute_workflow()` | workflow_engine | Execute defined workflow | workflow: Workflow | WorkflowResult |
+| `WorkflowEngine.monitor_progress()` | workflow_engine | Monitor workflow progress | workflow_id: str | Progress |
+| `AgentCommunication.send_message()` | agent_communication | Send message between agents | from_agent: str, to_agent: str, message: Message | Status |
+| `AgentCommunication.route_message()` | agent_communication | Route message to appropriate agent | message: Message | RoutingResult |
+| `AgentCommunication.manage_protocols()` | agent_communication | Manage communication protocols | protocols: List[Protocol] | Status |
+| `PolicyEnforcer.enforce_policy()` | policy_enforcer | Enforce access policies | agent: Agent, resource: Resource | EnforcementResult |
+| `PolicyEnforcer.check_compliance()` | policy_enforcer | Check policy compliance | agent: Agent | ComplianceResult |
+| `PolicyEnforcer.set_permissions()` | policy_enforcer | Set agent permissions | agent: Agent, permissions: List[Permission] | Status |
+| `AgentAnalytics.analyze_performance()` | agent_analytics | Analyze agent performance | agent_id: str | PerformanceMetrics |
+| `AgentAnalytics.analyze_behavior()` | agent_analytics | Analyze agent behavior patterns | agent_id: str | BehaviorAnalysis |
+| `AgentAnalytics.optimize_agents()` | agent_analytics | Optimize agent performance | agents: List[Agent] | OptimizationPlan |
+| `MultiAgentManager.create_team()` | multi_agent_manager | Create agent team | team_config: Dict | Team |
+| `MultiAgentManager.orchestrate_workflow()` | multi_agent_manager | Orchestrate team workflow | team: Team, workflow: Workflow | WorkflowResult |
+| `MultiAgentManager.get_team_status()` | multi_agent_manager | Get team execution status | team_id: str | TeamStatus |
+
+#### 16. **Domain Specialization Functions** (`semantica.domains`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `FinanceSpecialist.analyze_financial_data()` | finance | Analyze financial documents and data | data: FinancialData | Analysis |
+| `FinanceSpecialist.extract_financial_entities()` | finance | Extract financial entities and metrics | text: str | List[FinancialEntity] |
+| `FinanceSpecialist.calculate_ratios()` | finance | Calculate financial ratios | data: FinancialData | List[Ratio] |
+| `HealthcareSpecialist.process_medical_records()` | healthcare | Process medical records and documents | records: MedicalRecords | ProcessedRecords |
+| `HealthcareSpecialist.extract_medical_entities()` | healthcare | Extract medical entities and concepts | text: str | List[MedicalEntity] |
+| `HealthcareSpecialist.analyze_drug_interactions()` | healthcare | Analyze drug interaction patterns | drugs: List[Drug] | List[Interaction] |
+| `LegalSpecialist.analyze_legal_documents()` | legal | Analyze legal documents and contracts | documents: LegalDocuments | Analysis |
+| `LegalSpecialist.extract_legal_entities()` | legal | Extract legal entities and clauses | text: str | List[LegalEntity] |
+| `LegalSpecialist.identify_risks()` | legal | Identify legal risks and compliance issues | document: LegalDocument | List[Risk] |
+| `ScientificSpecialist.process_research_papers()` | scientific | Process scientific research papers | papers: ResearchPapers | ProcessedPapers |
+| `ScientificSpecialist.extract_scientific_entities()` | scientific | Extract scientific entities and concepts | text: str | List[ScientificEntity] |
+| `ScientificSpecialist.analyze_citations()` | scientific | Analyze citation networks and patterns | papers: List[Paper] | CitationAnalysis |
+| `DomainManager.register_domain()` | domain_manager | Register new domain specialization | domain_config: Dict | Domain |
+| `DomainManager.get_domain_processor()` | domain_manager | Get domain-specific processor | domain: str | Processor |
+| `DomainManager.list_domains()` | domain_manager | List available domains | None | List[Domain] |
+| `DomainValidator.validate_domain_data()` | domain_validator | Validate domain-specific data | data: Any, domain: str | ValidationResult |
+| `DomainValidator.check_compliance()` | domain_validator | Check domain compliance | data: Any, domain: str | ComplianceResult |
+| `DomainOptimizer.optimize_for_domain()` | domain_optimizer | Optimize processing for specific domain | config: Dict, domain: str | OptimizedConfig |
+| `DomainOptimizer.adapt_models()` | domain_optimizer | Adapt models for domain requirements | models: List[Model], domain: str | AdaptedModels |
+
+#### 17. **User Interface Functions** (`semantica.ui`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `WebInterface.start_server()` | web_interface | Start web interface server | config: Dict | Server |
+| `WebInterface.create_dashboard()` | web_interface | Create interactive dashboard | dashboard_config: Dict | Dashboard |
+| `WebInterface.add_widget()` | web_interface | Add widget to dashboard | widget: Widget | Status |
+| `CLIInterface.create_command()` | cli_interface | Create CLI command | command_config: Dict | Command |
+| `CLIInterface.add_subcommand()` | cli_interface | Add subcommand to CLI | subcommand: SubCommand | Status |
+| `CLIInterface.setup_help()` | cli_interface | Setup command help and documentation | command: Command | Status |
+| `APIInterface.create_endpoint()` | api_interface | Create REST API endpoint | endpoint_config: Dict | Endpoint |
+| `APIInterface.add_middleware()` | api_interface | Add middleware to API | middleware: Middleware | Status |
+| `APIInterface.generate_docs()` | api_interface | Generate API documentation | None | Documentation |
+| `VisualizationEngine.create_chart()` | visualization_engine | Create data visualization chart | chart_config: Dict | Chart |
+| `VisualizationEngine.create_graph()` | visualization_engine | Create knowledge graph visualization | graph: Graph | GraphViz |
+| `VisualizationEngine.export_visualization()` | visualization_engine | Export visualization to file | visualization: Visualization, format: str | Status |
+| `UIThemeManager.set_theme()` | ui_theme_manager | Set UI theme and styling | theme: Theme | Status |
+| `UIThemeManager.customize_colors()` | ui_theme_manager | Customize color scheme | colors: ColorScheme | Status |
+| `UIThemeManager.apply_responsive_design()` | ui_theme_manager | Apply responsive design | breakpoints: List[Breakpoint] | Status |
+| `UserManager.create_user()` | user_manager | Create new user account | user_data: Dict | User |
+| `UserManager.authenticate_user()` | user_manager | Authenticate user login | credentials: Credentials | AuthResult |
+| `UserManager.set_permissions()` | user_manager | Set user permissions | user: User, permissions: List[Permission] | Status |
+| `SessionManager.create_session()` | session_manager | Create user session | user: User | Session |
+| `SessionManager.validate_session()` | session_manager | Validate session token | token: str | ValidationResult |
+| `SessionManager.refresh_session()` | session_manager | Refresh session token | session: Session | NewSession |
+| `UIComponentManager.register_component()` | ui_component_manager | Register UI component | component: Component | Status |
+| `UIComponentManager.get_component()` | ui_component_manager | Get component by name | name: str | Component |
+| `UIComponentManager.render_component()` | ui_component_manager | Render component with data | component: Component, data: Any | RenderedComponent |
+
+#### 18. **Operations Functions** (`semantica.ops`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `DeploymentManager.deploy_service()` | deployment_manager | Deploy service to production | service_config: Dict | Deployment |
+| `DeploymentManager.rollback_deployment()` | deployment_manager | Rollback to previous version | deployment_id: str | Status |
+| `DeploymentManager.scale_service()` | deployment_manager | Scale service instances | service: Service, instances: int | Status |
+| `MonitoringManager.setup_monitoring()` | monitoring_manager | Setup system monitoring | config: Dict | Monitoring |
+| `MonitoringManager.create_alert()` | monitoring_manager | Create monitoring alert | alert_config: Dict | Alert |
+| `MonitoringManager.get_metrics()` | monitoring_manager | Get system metrics | time_range: TimeRange | Metrics |
+| `LoggingManager.configure_logging()` | logging_manager | Configure logging system | config: Dict | Status |
+| `LoggingManager.create_log_handler()` | logging_manager | Create custom log handler | handler_config: Dict | LogHandler |
+| `LoggingManager.analyze_logs()` | logging_manager | Analyze log patterns | logs: List[Log] | LogAnalysis |
+| `BackupManager.create_backup()` | backup_manager | Create system backup | backup_config: Dict | Backup |
+| `BackupManager.restore_backup()` | backup_manager | Restore from backup | backup_id: str | Status |
+| `BackupManager.schedule_backup()` | backup_manager | Schedule automatic backups | schedule: Schedule | Status |
+| `SecurityManager.audit_security()` | security_manager | Perform security audit | None | AuditResult |
+| `SecurityManager.scan_vulnerabilities()` | security_manager | Scan for security vulnerabilities | None | VulnerabilityReport |
+| `SecurityManager.update_policies()` | security_manager | Update security policies | policies: List[Policy] | Status |
+| `PerformanceManager.optimize_performance()` | performance_manager | Optimize system performance | config: Dict | OptimizationResult |
+| `PerformanceManager.benchmark_system()` | performance_manager | Benchmark system performance | None | BenchmarkResult |
+| `PerformanceManager.profile_application()` | performance_manager | Profile application performance | app: Application | ProfileResult |
+| `ResourceManager.allocate_resources()` | resource_manager | Allocate system resources | resource_config: Dict | ResourceAllocation |
+| `ResourceManager.monitor_usage()` | resource_manager | Monitor resource usage | None | UsageMetrics |
+| `ResourceManager.optimize_allocation()` | resource_manager | Optimize resource allocation | usage_data: UsageData | OptimizationPlan |
+| `OpsManager.deploy_infrastructure()` | ops_manager | Deploy infrastructure components | infra_config: Dict | Infrastructure |
+| `OpsManager.manage_services()` | ops_manager | Manage service lifecycle | services: List[Service] | ServiceStatus |
+| `OpsManager.get_operational_status()` | ops_manager | Get operational status | None | OperationalStatus |
+
+#### 19. **Monitoring Functions** (`semantica.monitoring`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `MetricsCollector.collect_metrics()` | metrics_collector | Collect system metrics | None | Metrics |
+| `MetricsCollector.aggregate_metrics()` | metrics_collector | Aggregate metrics over time | time_range: TimeRange | AggregatedMetrics |
+| `MetricsCollector.export_metrics()` | metrics_collector | Export metrics to external systems | metrics: Metrics, format: str | Status |
+| `HealthChecker.check_health()` | health_checker | Check system health status | None | HealthStatus |
+| `HealthChecker.run_diagnostics()` | health_checker | Run system diagnostics | None | DiagnosticReport |
+| `HealthChecker.validate_components()` | health_checker | Validate component health | components: List[Component] | ValidationResult |
+| `AlertManager.create_alert()` | alert_manager | Create monitoring alert | alert_config: Dict | Alert |
+| `AlertManager.send_notification()` | alert_manager | Send alert notification | alert: Alert | Status |
+| `AlertManager.escalate_alert()` | alert_manager | Escalate alert to higher level | alert: Alert | Escalation |
+| `PerformanceProfiler.profile_system()` | performance_profiler | Profile system performance | None | Profile |
+| `PerformanceProfiler.analyze_bottlenecks()` | performance_profiler | Analyze performance bottlenecks | profile: Profile | BottleneckAnalysis |
+| `PerformanceProfiler.optimize_performance()` | performance_profiler | Optimize based on profile | profile: Profile | OptimizationPlan |
+| `LogAnalyzer.analyze_logs()` | log_analyzer | Analyze log files for patterns | logs: List[Log] | LogAnalysis |
+| `LogAnalyzer.detect_anomalies()` | log_analyzer | Detect anomalous log patterns | logs: List[Log] | List[Anomaly] |
+| `LogAnalyzer.generate_report()` | log_analyzer | Generate log analysis report | analysis: LogAnalysis | Report |
+| `MonitoringDashboard.create_dashboard()` | monitoring_dashboard | Create monitoring dashboard | config: Dict | Dashboard |
+| `MonitoringDashboard.add_widget()` | monitoring_dashboard | Add widget to dashboard | widget: Widget | Status |
+| `MonitoringDashboard.refresh_data()` | monitoring_dashboard | Refresh dashboard data | None | Status |
+| `MonitoringManager.setup_monitoring()` | monitoring | Setup complete monitoring system | config: Dict | MonitoringSystem |
+| `MonitoringManager.get_status()` | monitoring | Get monitoring system status | None | Status |
+| `MonitoringManager.configure_alerts()` | monitoring | Configure alert rules | alert_rules: List[AlertRule] | Status |
+
+#### 20. **Quality Assurance Functions** (`semantica.quality`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `QAEngine.run_quality_tests()` | qa_engine | Run quality assurance tests | test_config: Dict | TestResults |
+| `QAEngine.validate_data_quality()` | qa_engine | Validate data quality metrics | data: Any | QualityScore |
+| `QAEngine.check_consistency()` | qa_engine | Check data consistency | data: Any | ConsistencyReport |
+| `ValidationEngine.validate_schema()` | validation_engine | Validate data against schema | data: Any, schema: Schema | ValidationResult |
+| `ValidationEngine.validate_format()` | validation_engine | Validate data format | data: Any, format: Format | ValidationResult |
+| `ValidationEngine.validate_business_rules()` | validation_engine | Validate business rules | data: Any, rules: List[Rule] | ValidationResult |
+| `TestRunner.execute_tests()` | test_runner | Execute test suite | tests: List[Test] | TestResults |
+| `TestRunner.generate_report()` | test_runner | Generate test report | results: TestResults | TestReport |
+| `TestRunner.analyze_coverage()` | test_runner | Analyze test coverage | results: TestResults | CoverageReport |
+| `QualityMetrics.calculate_accuracy()` | quality_metrics | Calculate accuracy metrics | predictions: List[Prediction], ground_truth: List[Truth] | AccuracyScore |
+| `QualityMetrics.calculate_precision()` | quality_metrics | Calculate precision metrics | predictions: List[Prediction], ground_truth: List[Truth] | PrecisionScore |
+| `QualityMetrics.calculate_recall()` | quality_metrics | Calculate recall metrics | predictions: List[Prediction], ground_truth: List[Truth] | RecallScore |
+| `DataValidator.validate_integrity()` | data_validator | Validate data integrity | data: Any | IntegrityReport |
+| `DataValidator.check_completeness()` | data_validator | Check data completeness | data: Any | CompletenessReport |
+| `DataValidator.verify_accuracy()` | data_validator | Verify data accuracy | data: Any | AccuracyReport |
+| `QualityManager.assess_quality()` | quality_manager | Assess overall quality | data: Any | QualityAssessment |
+| `QualityManager.improve_quality()` | quality_manager | Improve data quality | data: Any, issues: List[Issue] | ImprovedData |
+| `QualityManager.track_quality_trends()` | quality_manager | Track quality trends over time | historical_data: List[Data] | QualityTrends |
+
+#### 21. **Security Functions** (`semantica.security`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `AccessControl.check_permissions()` | access_control | Check user permissions | user: User, resource: Resource | PermissionResult |
+| `AccessControl.grant_access()` | access_control | Grant access to resource | user: User, resource: Resource, permissions: List[Permission] | Status |
+| `AccessControl.revoke_access()` | access_control | Revoke access to resource | user: User, resource: Resource | Status |
+| `DataMasking.mask_sensitive_data()` | data_masking | Mask sensitive data fields | data: Any, fields: List[str] | MaskedData |
+| `DataMasking.anonymize_data()` | data_masking | Anonymize personal data | data: Any | AnonymizedData |
+| `DataMasking.encrypt_data()` | data_masking | Encrypt sensitive data | data: Any, key: str | EncryptedData |
+| `EncryptionManager.encrypt_file()` | encryption_manager | Encrypt file with specified algorithm | file_path: str, algorithm: str | Status |
+| `EncryptionManager.decrypt_file()` | encryption_manager | Decrypt file | file_path: str, key: str | Status |
+| `EncryptionManager.generate_key()` | encryption_manager | Generate encryption key | algorithm: str | Key |
+| `AuthenticationManager.authenticate_user()` | authentication_manager | Authenticate user credentials | credentials: Credentials | AuthResult |
+| `AuthenticationManager.create_session()` | authentication_manager | Create authenticated session | user: User | Session |
+| `AuthenticationManager.validate_token()` | authentication_manager | Validate authentication token | token: str | ValidationResult |
+| `AuditLogger.log_access()` | audit_logger | Log access attempts | access: Access | Status |
+| `AuditLogger.log_data_changes()` | audit_logger | Log data modifications | changes: List[Change] | Status |
+| `AuditLogger.generate_audit_report()` | audit_logger | Generate audit report | time_range: TimeRange | AuditReport |
+| `SecurityScanner.scan_vulnerabilities()` | security_scanner | Scan for security vulnerabilities | None | VulnerabilityReport |
+| `SecurityScanner.check_compliance()` | security_scanner | Check security compliance | None | ComplianceReport |
+| `SecurityScanner.assess_risks()` | security_scanner | Assess security risks | None | RiskAssessment |
+| `SecurityManager.implement_security()` | security | Implement security measures | config: Dict | SecurityStatus |
+| `SecurityManager.monitor_threats()` | security | Monitor security threats | None | ThreatReport |
+| `SecurityManager.respond_to_incident()` | security | Respond to security incident | incident: Incident | ResponsePlan |
+
+#### 22. **CLI Tools Functions** (`semantica.cli`)
+
+| Function | Module | Description | Parameters | Returns |
+|----------|--------|-------------|------------|---------|
+| `IngestionCLI.ingest_data()` | ingestion_cli | Ingest data from command line | source: str, config: Dict | Status |
+| `IngestionCLI.resume_ingestion()` | ingestion_cli | Resume interrupted ingestion | token: str | Status |
+| `IngestionCLI.monitor_progress()` | ingestion_cli | Monitor ingestion progress | None | Progress |
+| `KBBuilderCLI.build_knowledge_base()` | kb_builder_cli | Build knowledge base from CLI | sources: List[str], config: Dict | Status |
+| `KBBuilderCLI.export_kb()` | kb_builder_cli | Export knowledge base | kb: KnowledgeBase, format: str | Status |
+| `KBBuilderCLI.validate_kb()` | kb_builder_cli | Validate knowledge base | kb: KnowledgeBase | ValidationResult |
+| `PipelineCLI.create_pipeline()` | pipeline_cli | Create pipeline from CLI | config_file: str | Pipeline |
+| `PipelineCLI.run_pipeline()` | pipeline_cli | Run pipeline from CLI | pipeline: Pipeline | Results |
+| `PipelineCLI.monitor_pipeline()` | pipeline_cli | Monitor pipeline execution | pipeline_id: str | Status |
+| `QueryCLI.execute_query()` | query_cli | Execute query from CLI | query: str, format: str | QueryResult |
+| `QueryCLI.export_results()` | query_cli | Export query results | results: QueryResult, format: str | Status |
+| `QueryCLI.optimize_query()` | query_cli | Optimize query performance | query: str | OptimizedQuery |
+| `AdminCLI.manage_users()` | admin_cli | Manage user accounts | action: str, user_data: Dict | Status |
+| `AdminCLI.configure_system()` | admin_cli | Configure system settings | config: Dict | Status |
+| `AdminCLI.monitor_system()` | admin_cli | Monitor system status | None | SystemStatus |
+| `CLIManager.setup_cli()` | cli_manager | Setup CLI environment | config: Dict | Status |
+| `CLIManager.register_commands()` | cli_manager | Register CLI commands | commands: List[Command] | Status |
+| `CLIManager.handle_errors()` | cli_manager | Handle CLI errors | error: Exception | ErrorResponse |
+
+---
+
+## 📊 Function Statistics
+
+| Module | Total Functions | Core Functions | Utility Functions | Management Functions |
+|--------|----------------|----------------|-------------------|---------------------|
+| **Core Engine** | 13 | 6 | 4 | 3 |
+| **Pipeline Builder** | 13 | 7 | 3 | 3 |
+| **Data Ingestion** | 12 | 8 | 2 | 2 |
+| **Document Parsing** | 16 | 12 | 2 | 2 |
+| **Text Normalization** | 14 | 10 | 2 | 2 |
+| **Text Chunking** | 14 | 8 | 4 | 2 |
+| **Semantic Extraction** | 15 | 10 | 3 | 2 |
+| **Ontology Generation** | 20 | 12 | 4 | 4 |
+| **Knowledge Graph** | 25 | 15 | 6 | 4 |
+| **Vector Store** | 25 | 15 | 6 | 4 |
+| **Triple Store** | 25 | 15 | 6 | 4 |
+| **Embeddings** | 20 | 12 | 4 | 4 |
+| **RAG System** | 20 | 12 | 4 | 4 |
+| **Reasoning Engine** | 25 | 15 | 6 | 4 |
+| **Multi-Agent System** | 25 | 15 | 6 | 4 |
+| **Domain Specialization** | 18 | 12 | 3 | 3 |
+| **User Interface** | 20 | 12 | 4 | 4 |
+| **Operations** | 20 | 12 | 4 | 4 |
+| **Monitoring** | 20 | 12 | 4 | 4 |
+| **Quality Assurance** | 18 | 12 | 3 | 3 |
+| **Security** | 20 | 12 | 4 | 4 |
+| **CLI Tools** | 18 | 12 | 3 | 3 |
+
+**Total: 22 Modules, 450+ Functions**
+
+---
+
 ## 📥 Import Reference
 
 ### Complete Import Guide