added delete sagemaker script

.env.example

@@ -21,9 +21,9 @@ RAG_MODEL_DEVICE = "cpu"
 HUGGING_FACE_HUB_TOKEN="str"
 
 #SAGEMAKER
-SAGEMAKER_ENDPOINT_INFERENCE=llm-v1-llm-endpoint
+SAGEMAKER_ENDPOINT_INFERENCE=llm-v2-llm-endpoint
 SAGEMAKER_MODEL_INFERENCE=huggingface-pytorch-tgi-inference-2024-05-13-10-50-05-168
-SAGEMAKER_ENDPOINT_CONFIG_INFERENCE=llm-v1-llm-endpoint
+SAGEMAKER_ENDPOINT_CONFIG_INFERENCE=llm-v2-llm-endpoint
 SAGEMAKER_INFERENCE_COMPONENT_INFERENCE=None
 
 # SAGEMAKER EXECUTION ROLE

Makefile

@@ -1,12 +1,30 @@
-.PHONY: deploy-inference-endpoint
+export AWS_PROFILE=decodingml
 
+.PHONY: help create-sagemaker-role create-sagemaker-execution-role deploy-inference-endpoint delete-inference-endpoint
+
+help:
+	@echo "Available commands:"
+	@echo " create-sagemaker-role            Create the SageMaker role."
+	@echo " create-sagemaker-execution-role  Create the SageMaker execution role."
+	@echo " deploy-inference-endpoint        Deploy the inference endpoint."
+	@echo " delete-inference-endpoint        Delete the inference endpoint and config."
 
 create-sagemaker-role:
+	@echo "Creating the SageMaker role..."
 	poetry run python llm_engineering/core/aws/create_sagemaker_role.py
 
 create-sagemaker-execution-role:
+	@echo "Creating the SageMaker execution role..."
 	poetry run python llm_engineering/core/aws/create_sagemaker_execution_role.py
-	
+
 deploy-inference-endpoint:
+	@echo "Deploying the inference endpoint..."
 	poetry run python llm_engineering/model/deploy/huggingface/run.py
 
+delete-inference-endpoint:
+	@if [ -z "$(ENDPOINT_NAME)" ]; then \
+		echo "Error: ENDPOINT_NAME is not set. Usage: make delete-inference-endpoint ENDPOINT_NAME=<name>"; \
+		exit 1; \
+	fi
+	@echo "Deleting the inference endpoint and config..."
+	poetry run python llm_engineering/model/delete_inference_endpoint.py $(ENDPOINT_NAME)

llm_engineering/model/delete_inference_endpoint.py

@@ -0,0 +1,68 @@
+import logging
+import sys
+
+import boto3
+from botocore.exceptions import ClientError
+
+from llm_engineering.settings import settings
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+logger = logging.getLogger(__name__)
+
+
+def delete_endpoint_and_config(endpoint_name):
+    """
+    Deletes an AWS SageMaker endpoint and its associated configuration.
+    Args:
+    endpoint_name (str): The name of the SageMaker endpoint to delete.
+    Returns:
+    None
+    """
+    try:
+        sagemaker_client = boto3.client(
+            "sagemaker",
+            region_name="eu-central-1",
+            aws_access_key_id=settings.AWS_ACCESS_KEY,
+            aws_secret_access_key=settings.AWS_SECRET_KEY,
+        )
+    except Exception as e:
+        logger.error(f"Error creating SageMaker client: {e}")
+        return
+
+    # Delete the endpoint
+    try:
+        sagemaker_client.delete_endpoint(EndpointName=endpoint_name)
+        logger.info(f"Endpoint '{endpoint_name}' deletion initiated.")
+    except ClientError as e:
+        logger.error(f"Error deleting endpoint: {e}")
+        return
+
+    # Get the endpoint configuration name
+    try:
+        response = sagemaker_client.describe_endpoint(EndpointName=endpoint_name)
+        config_name = response["EndpointConfigName"]
+    except ClientError as e:
+        logger.error(f"Error getting endpoint configuration name: {e}")
+        return
+
+    # Delete the endpoint configuration
+    try:
+        sagemaker_client.delete_endpoint_config(EndpointConfigName=config_name)
+        logger.info(f"Endpoint configuration '{config_name}' deleted.")
+    except ClientError as e:
+        logger.error(f"Error deleting endpoint configuration: {e}")
+
+
+def run():
+    if len(sys.argv) != 2:
+        logger.error("Usage: python script_name.py <endpoint_name>")
+        sys.exit(1)
+
+    endpoint_name = sys.argv[1]
+    logger.info(f"Attempting to delete endpoint: {endpoint_name}")
+    delete_endpoint_and_config(endpoint_name)
+
+
+if __name__ == "__main__":
+    run()