diff --git a/mlmodel-cicd/ml_model.yaml b/mlmodel-cicd/ml_model.yaml
index 7f18f83..ab55623 100644
--- a/mlmodel-cicd/ml_model.yaml
+++ b/mlmodel-cicd/ml_model.yaml
@@ -7,31 +7,53 @@ description: |
 
 algorithm: XGBoost
 target: expected_time
-
+tags:
+  - tagFQN : PII.None
+    description: Tag None
+    labelType: Manual
+    state: Confirmed
+    source: Classification
+  - tagFQN: PersonalData.Personal
+    description: Personal Data Tag
+    labelType: Manual
+    state: Confirmed
+    source: Classification
+  - tagFQN: SmartMed.Average
+    description: Smartmed Tag
+    labelType: Manual
+    state: Confirmed
+    source: Classification
 mlFeatures:
   - name: last_update_bucket
     dataType: categorical
     featureAlgorithm: Bucketing
+    tags:
+      - tagFQN: PII.None
+        description: Tag None
+        labelType: Manual
+        state: Confirmed
+        source: Classification
+
     featureSources:
-      - name: orders
+      - name: last_update
         dataType: timestamp
-        dataSourceFqn: demo_pg.postgres.public.orders
+        dataSourceFqn: orders.postgres.public.orders
   - name: restaurant_dimension
     dataType: numerical
     featureAlgorithm: PCA
     featureSources:
       - name: rating
         dataType: integer
-        dataSourceFqn: demo_pg.postgres.public.restaurants
+        dataSourceFqn: orders.postgres.public.restaurants
       - name: average_price
         dataType: integer
-        dataSourceFqn: demo_pg.postgres.public.restaurants
+        dataSourceFqn: orders.postgres.public.restaurants
   - name: is_premium
     dataType: categorical
     featureSources:
       - name: premium
         dataType: boolean
-        dataSourceFqn: demo_pg.postgres.public.users
+        dataSourceFqn: orders.postgres.public.users
 
 mlHyperParameters:
   - name: regularisation
@@ -41,3 +63,4 @@ mlHyperParameters:
 mlStore:
   storage: s3://path-to-pickle
   imageRepository: https://docker.hub.com/image
+
diff --git a/mlmodel-cicd/mlmodel_cicd.py b/mlmodel-cicd/mlmodel_cicd.py
index 75511ac..3407b6c 100644
--- a/mlmodel-cicd/mlmodel_cicd.py
+++ b/mlmodel-cicd/mlmodel_cicd.py
@@ -36,11 +36,12 @@
 from metadata.generated.schema.security.client.openMetadataJWTClientConfig import (
     OpenMetadataJWTClientConfig,
 )
+from metadata.generated.schema.type.tagLabel import TagLabel
 from metadata.ingestion.ometa.ometa_api import OpenMetadata
 
 OM_HOST_PORT = "http://localhost:8585/api"
-OM_JWT_TOKEN = "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg"
-ML_MODEL_FILE = "ml_model.yaml"
+OM_JWT_TOKEN = "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJvcGVuLW1ldGFkYXRhLm9yZyIsInN1YiI6ImluZ2VzdGlvbi1ib3QiLCJlbWFpbCI6ImluZ2VzdGlvbi1ib3RAb3Blbm1ldGFkYXRhLm9yZyIsImlzQm90Ijp0cnVlLCJ0b2tlblR5cGUiOiJCT1QiLCJpYXQiOjE2ODM4MDIyNjUsImV4cCI6bnVsbH0.abHiU2KnFnrtF7QrnygHohPjeu6FGmtyBCLnTlFnf_p-7-Xq8NNz6aDWoFRJf13oAE6z8Tg_CwWmOEbTGqfG4GvWyNYCrxrGlS6RO9Td5QmVxDX6YZUdP4rn2RdvYzOdjQfAzeBTTsPe3VKEFGJB9HpEBy_Uux6QN1K7CQKewm-DrDejqwrkfG5lozPUuFxSx17BE60wJ7Z3TzhK8qAI94touRRodsGHwhFi48vL0fLcTu_tEG_cmJyy12Bzmv25pqHsFombb37lhiHwi-4mJMt_tV7dVCf-_YU13GDFC8pRTxHsi_Srf6hC1Pt4ZY7wA0p88kCRiPbjxLxqR-vgMA"
+ML_MODEL_FILE = "ml_model_tags.yaml"
 
 
 def read_ml_metadata(path: Path) -> dict:
@@ -127,19 +128,48 @@ def update_openmetadata(raw_meta: dict) -> None:
     if not metadata.health_check():
         raise RuntimeError("Error connecting to OpenMetadata")
 
+
+
+
+    #create tags getting info form yaml file
+    createTagClassificationRaw(metadata, raw_meta)
+
+
+
     print("Connected to OpenMetadata ✅")
     time.sleep(1)
-
+    print (raw_meta)
     create_ml_model = CreateMlModelRequest(
+
         name=raw_meta["name"],
         description=raw_meta["description"],
         algorithm=raw_meta["algorithm"],
         target=raw_meta["target"],
+        tags=[
+            TagLabel(
+                tagFQN=ml_tag["tagFQN"],
+                description=ml_tag["description"],
+                labelType=ml_tag["labelType"],
+                state=ml_tag["state"],
+                source=ml_tag["source"]
+            )
+            for ml_tag in raw_meta.get("tags") or []
+        ],
         mlFeatures=[
             MlFeature(
                 name=ml_feature["name"],
                 dataType=ml_feature["dataType"],
                 featureAlgorithm=ml_feature.get("featureAlgorithm"),
+                tags=[
+                    TagLabel(
+                        tagFQN=ml_tagFeature["tagFQN"],
+                        description=ml_tagFeature["description"],
+                        labelType=ml_tagFeature["labelType"],
+                        state=ml_tagFeature["state"],
+                        source=ml_tagFeature["source"]
+                    )
+                    for ml_tagFeature in ml_feature.get("tags") or []
+                ],
                 featureSources=[
                     FeatureSource(
                         name=feature_source["name"],
@@ -200,6 +230,45 @@ def run_workflow() -> None:
     update_openmetadata(raw_meta)
 
 
+def createTagClassificationRaw(metadata, raw_meta) -> None:
+    for ml_tag in raw_meta.get("tags"):
+
+        #print( ml_tag["tagFQN"])
+        class_tag=ml_tag["tagFQN"].split(".")
+        classificationName=class_tag[0]
+        tagName=class_tag[1]
+        createTagClassification(metadata,classificationName,tagName)
+
+
+
+
+
+
+
+def createTagClassification(metadata, classification_name, tag_name) -> None:
+    from metadata.generated.schema.api.classification.createClassification import (
+        CreateClassificationRequest,
+    )
+    from metadata.generated.schema.api.classification.createTag import CreateTagRequest
+
+    classification_request = CreateClassificationRequest(
+        name=classification_name,
+        description="Sample classification.",
+    )
+
+    metadata.create_or_update(classification_request)
+
+    tag_request = CreateTagRequest(
+        classification=classification_request.name,
+        name=tag_name,
+        description="Sample Tag.",
+    )
+
+    metadata.create_or_update(tag_request)
+
+
+
 if __name__ == "__main__":
 
     run_workflow()
+