8c73f25537
- PROJECT_BLUEPRINT.md: Full architecture with LightGBM, Qwen3, structured embeddings - RESEARCH_FINDINGS.md: 2024 benchmarks, competition analysis, validation - BUILD_INSTRUCTIONS.md: Step-by-step implementation guide - README.md: User-friendly overview and quick start - Research-backed hybrid ML/LLM email classifier - 94-96% accuracy target, 17min for 80k emails - Privacy-first, local processing, distributable wheel - Modular architecture with tiered dependencies - LLM optional (graceful degradation) - OpenAI-compatible API support
63 lines
546 B
Plaintext
63 lines
546 B
Plaintext
# Python
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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.Python
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env/
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venv/
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*.egg-info/
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dist/
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build/
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# Data and Models
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data/training/
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src/models/pretrained/*.pkl
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src/models/pretrained/*.joblib
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*.h5
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*.joblib
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# Credentials
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.env
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credentials/
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*.json
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!config/*.json
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!config/*.yaml
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# Logs
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logs/*.log
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*.log
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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# OS
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.DS_Store
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Thumbs.db
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# Checkpoints
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checkpoints/
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*.checkpoint
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# Results
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results/
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output/
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# Pytest
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.pytest_cache/
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.coverage
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htmlcov/
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# MyPy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Temporary files
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*.tmp
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*.bak
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*~
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