refactoring: add initial pipeline configuration and model classes

research/model_registry.py

@@ -0,0 +1,44 @@
+from typing import List
+
+from research.base_model import BaseModel
+from research.experiment import ExperimentConfig
+from research.models.bigru_model import BiGRUModel
+from research.models.cnn_model import CNNModel
+from research.models.ensemble_model import EnsembleModel
+from research.models.lightgbm_model import LightGBMModel
+from research.models.logistic_regression_model import LogisticRegressionModel
+from research.models.lstm_model import LSTMModel
+from research.models.naive_bayes_model import NaiveBayesModel
+from research.models.random_forest_model import RandomForestModel
+from research.models.svm_model import SVMModel
+from research.models.transformer_model import TransformerModel
+from research.models.xgboost_model import XGBoostModel
+
+MODEL_REGISTRY = {
+    "bigru": BiGRUModel,
+    "cnn": CNNModel,
+    "ensemble": EnsembleModel,
+    "lightgbm": LightGBMModel,
+    "logistic_regression": LogisticRegressionModel,
+    "lstm": LSTMModel,
+    "naive_bayes": NaiveBayesModel,
+    "random_forest": RandomForestModel,
+    "svm": SVMModel,
+    "transformer": TransformerModel,
+    "xgboost": XGBoostModel,
+}
+
+
+def create_model(config: ExperimentConfig) -> BaseModel:
+    """Factory function to create models"""
+    model_class = MODEL_REGISTRY.get(config.model_type)
+
+    if model_class is None:
+        raise ValueError(f"Unknown model type: {config.model_type}")
+
+    return model_class(config)
+
+
+def list_available_models() -> List[str]:
+    """List all available model types"""
+    return list(MODEL_REGISTRY.keys())