deleting trash

Author: guipleite

src/scripts/Pipelines/model.joblib

@@ -1,32 +1,49 @@
 import sys
 import os
+import time
 import yaml
 from ibm_watson_machine_learning import APIClient
 
-# MODEL_PATH = os.path.abspath(sys.argv[1])
-CRED_PATH = os.path.abspath(sys.argv[1])
-# PROJ_PATH = os.path.abspath(sys.argv[3])
-# META_PATH = PROJ_PATH+"/metadata.yaml"
+"""
+    Usage:
+        python3 model_reploy_pipeline.py ./pickle_model ../path/to/project/ ../credentials.yaml
+
+"""
+
+MODEL_PATH = os.path.abspath(sys.argv[1])
+PROJ_PATH = os.path.abspath(sys.argv[2])
+CRED_PATH = os.path.abspath(sys.argv[3])
+META_PATH = PROJ_PATH + "/metadata.yaml"
 
 with open(CRED_PATH) as stream:
     try:
         credentials = yaml.safe_load(stream)
     except yaml.YAMLError as exc:
         print(exc)
 
+with open(META_PATH) as stream:
+        try:
+            metadata = yaml.safe_load(stream)
+        except yaml.YAMLError as exc:
+            print(exc)
 
 wml_credentials = {"url": credentials["url"], "apikey": credentials["apikey"]}
 
 client = APIClient(wml_credentials)
 client.spaces.list()
 
 SPACE_ID = credentials["space_id"]
-MODEL_GUID = input("MODEL GUID: ")
-DEPLOYMENT_UID = input("DEPLOYMENT UID: ")
+
+if "deployment_uid" in metadata.keys():
+    MODEL_GUID = metadata["model_uid"]
+    DEPLOYMENT_UID = metadata["deployment_uid"]
+    print("\nExtracting DEPLOYMENT UID and MODEL GUID from metadata file\n")
+
+else:
+    MODEL_GUID = input("MODEL GUID: ")
+    DEPLOYMENT_UID = input("DEPLOYMENT UID: ")  
 
 client.set.default_space(SPACE_ID)
-MODEL_GUID = "b065a8c6-01ec-461b-96cc-c3abdcc35405"
-DEPLOYMENT_UID = "560eed08-7d74-4ed8-8429-8d26b88cd8a3"
 
 client.repository.list_models_revisions(MODEL_GUID)
 
@@ -42,8 +59,6 @@
     deployment_uid=DEPLOYMENT_UID, changes=metadata
 )
 
-import time
-
 status = None
 while status not in ["ready", "failed"]:
     print(".", end=" ")