bd0aa12004
## New Skill: transcript-fixer v1.0.0 Correct speech-to-text (ASR/STT) transcription errors through dictionary-based rules and AI-powered corrections with automatic pattern learning. **Features:** - Two-stage correction pipeline (dictionary + AI) - Automatic pattern detection and learning - Domain-specific dictionaries (general, embodied_ai, finance, medical) - SQLite-based correction repository - Team collaboration with import/export - GLM API integration for AI corrections - Cost optimization through dictionary promotion **Use cases:** - Correcting meeting notes, lecture recordings, or interview transcripts - Fixing Chinese/English homophone errors and technical terminology - Building domain-specific correction dictionaries - Improving transcript accuracy through iterative learning **Documentation:** - Complete workflow guides in references/ - SQL query templates - Troubleshooting guide - Team collaboration patterns - API setup instructions **Marketplace updates:** - Updated marketplace to v1.8.0 - Added transcript-fixer plugin (category: productivity) - Updated README.md with skill description and use cases - Updated CLAUDE.md with skill listing and counts 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
45 lines
1.6 KiB
Python
45 lines
1.6 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):
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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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from .ai_processor import AIProcessor
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return AIProcessor
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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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