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feat: update ML pipeline with preprocessing module and string-based inputs
- Replace integer-encoded fields (genre, heure_supplementaires, frequence_deplacement) with human-readable Literal/String types in schema and DB models - Add departement and niveau_hierarchique_poste fields to schema and DB models - Extract feature engineering from predict route into ml_model/preprocessing.py - Update best_pipeline.pkl to include preprocessing stepsf67b60a
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fix: lazy-initialize DB engine to prevent CI import crash
Move create_engine and SessionLocal inside get_db so the database connection is only created when actually needed. Fixes ImportError during pytest when DB environment variables are not set.36fe10e
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feat: log predictions to database after each inference
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feat: add PostgreSQL database layer with SQLAlchemy ORM
- Add Employee and Prediction SQLAlchemy models (app/db/models.py) - Add database session/engine configuration from env vars (app/db/session.py) - Add script to create database and tables if not exists (scripts/create_db.py) - Add docker-compose with PostgreSQL + pgAdmin services - Update .env.example with DB_* connection variables - Add psycopg2-binary, SQLAlchemy, greenlet to requirements.txt - Document database schema, UML diagram and column constraints in READMEa194bc8
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init: project structure and base configuration
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