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- Add complete libs/semantica framework with 20+ production-ready modules - Implement core orchestration, configuration, and plugin management - Add comprehensive data ingestion (files, web, streams, databases, emails) - Implement parsing for documents, web content, structured data, code, media - Add data normalization (text, entities, dates, numbers, quality) - Implement semantic extraction (NER, relations, events, coreference, triples) - Add ontology management and knowledge graph construction - Implement graph analytics (centrality, community detection, connectivity) - Add embeddings generation and vector store management - Implement pipeline orchestration and streaming processing - Add security (access control, data masking, PII redaction) - Implement quality assurance and validation systems - Add export capabilities (RDF, JSON, CSV, graph formats) - Create comprehensive cookbook with examples and use cases - Add basic examples (document processing, web scraping, knowledge graphs) - Add advanced examples (multi-modal processing, real-time analytics) - Implement detailed bullet-point comments throughout - Follow SDK best practices and Python-only implementation - Add comprehensive pyproject.toml with dependencies and configuration - Include detailed README with usage examples and documentation This commit establishes the complete foundation for the Semantica semantic layer and knowledge engineering framework.
19 lines
783 B
Python
19 lines
783 B
Python
"""
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Advanced Examples
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This module contains advanced usage examples for the Semantica framework.
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Examples:
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- multi_modal_processing: Process multi-modal data (text, images, audio)
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- real_time_analytics: Real-time data processing and analytics
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- federated_knowledge: Federated knowledge graph construction
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- streaming_processing: Stream processing and real-time updates
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- distributed_processing: Distributed processing across multiple nodes
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"""
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# from .multi_modal_processing import MultiModalProcessingExample
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# from .real_time_analytics import RealTimeAnalyticsExample
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# from .federated_knowledge import FederatedKnowledgeExample
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# from .streaming_processing import StreamingProcessingExample
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# from .distributed_processing import DistributedProcessingExample
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