9b724f33e3
## New Skill: video-comparer v1.0.0 - Compare original and compressed videos with interactive HTML reports - Calculate quality metrics (PSNR, SSIM) for compression analysis - Generate frame-by-frame visual comparisons (slider, side-by-side, grid) - Extract video metadata (codec, resolution, bitrate, duration) - Multi-platform FFmpeg support with security features ## transcript-fixer Enhancements - Add async AI processor for parallel processing - Add connection pool management for database operations - Add concurrency manager and rate limiter - Add audit log retention and database migrations - Add health check and metrics monitoring - Add comprehensive test suite (8 new test files) - Enhance security with domain and path validators ## Marketplace Updates - Update marketplace version from 1.8.0 to 1.9.0 - Update skills count from 15 to 16 - Update documentation (README.md, CLAUDE.md, CHANGELOG.md) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
"""
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Core Module - Business Logic and Data Access
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This module contains the core business logic for transcript correction:
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- CorrectionRepository: Data access layer with ACID transactions
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- CorrectionService: Business logic layer with validation
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- DictionaryProcessor: Stage 1 dictionary-based corrections
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- AIProcessor: Stage 2 AI-powered corrections
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- LearningEngine: Pattern detection and learning
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"""
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# Core SQLite-based components (always available)
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from .correction_repository import CorrectionRepository, Correction, DatabaseError, ValidationError
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from .correction_service import CorrectionService, ValidationRules
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# Processing components (imported lazily to avoid dependency issues)
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def _lazy_import(name: str) -> object:
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"""Lazy import to avoid loading heavy dependencies."""
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if name == 'DictionaryProcessor':
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from .dictionary_processor import DictionaryProcessor
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return DictionaryProcessor
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elif name == 'AIProcessor':
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# Use async processor by default for 5-10x speedup on large files
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from .ai_processor_async import AIProcessorAsync
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return AIProcessorAsync
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elif name == 'LearningEngine':
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from .learning_engine import LearningEngine
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return LearningEngine
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raise ImportError(f"Unknown module: {name}")
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# Export main classes
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__all__ = [
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'CorrectionRepository',
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'CorrectionService',
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'Correction',
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'DatabaseError',
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'ValidationError',
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'ValidationRules',
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]
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# Make lazy imports available via __getattr__
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def __getattr__(name):
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if name in ['DictionaryProcessor', 'AIProcessor', 'LearningEngine']:
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return _lazy_import(name)
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raise AttributeError(f"module '{__name__}' has no attribute '{name}'")
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