Added the final readme.md / finishing of the project

Author: Ananddd06

README.md

@@ -150,6 +150,7 @@ Runs the full pipeline on every push:
 - 🔐 Add role-based access control for logs
 - 📊 Grafana + Prometheus monitoring
 - ☁️ Deploy to AWS Sagemaker or GCP AI Platform
+- ✨ CICD Pipeline
 
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@@ -161,7 +162,7 @@ If you liked this project, please consider giving it a ⭐️ and sharing with o
 
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-## 🧰 Project Extensions You Can Use
+<!-- ## 🧰 Project Extensions You Can Use
 
 Would you like me to now generate:
 
@@ -171,7 +172,7 @@ Would you like me to now generate:
 - 📊 mlflow_tracking.py – script to log parameters, metrics, and models to MLflow
 - 🖥️ Streamlit or Flask app – for serving your trained model via an interactive web app or API
 
----
+--- -->
 
 ## 🖥️ Model Deployment Options
 

networksecurity/pipeline/training_pipeline.py

@@ -77,4 +77,16 @@ def start_model_trainer(self, data_transformation_artifact: DataTransformationAr
             logger.info("✅ Model training completed successfully.")
             logger.info(f"📦 Model Trainer Artifact: {model_trainer_artifact}")
         except Exception as e:
-            raise CustomException(e, sys) from e
+            raise CustomException(e, sys) from e
+    
+    def run_pipeline(self):
+        try:
+            logger.info("🚀 Starting the training pipeline...")
+            data_ingestion_artifact = self.start_data_ingestion()
+            data_validation_artifact = self.start_data_validation(data_ingestion_artifact)
+            data_transformation_artifact = self.start_data_transformation(data_validation_artifact)
+            model_trainer_artifact = self.start_model_trainer(data_transformation_artifact)
+            logger.info("✅ Training pipeline completed successfully.")
+            return model_trainer_artifact
+        except Exception as e:
+            raise CustomException(e, sys) from e