updated test cases

Signed-off-by: kalyan <[email protected]>

opensearch_py_ml/ml_commons/model_train.py

@@ -38,7 +38,7 @@ def _train(
 
         return self._client.transport.perform_request(
             method="POST",
-            url=f"{ML_BASE_URI}/{API_ENDPOINT}/{algorithm_name}",
+            url=f"{ML_BASE_URI}/{ModelTrain.API_ENDPOINT}/{algorithm_name}",
             body=input_json,
             params=params,
         )

tests/ml_commons/test_ml_commons_client.py

@@ -515,4 +515,3 @@ def test_integration_model_train_register_full_cycle():
                 assert raised == False, "Raised Exception in deleting model"
 
 
-test_integration_model_train_register_full_cycle()

tests/ml_commons/test_model_train.py

@@ -5,29 +5,79 @@
 # Any modifications Copyright OpenSearch Contributors. See
 # GitHub history for details.
 
+import pytest
+from opensearchpy import OpenSearch, helpers
+from sklearn.datasets import load_iris
+import time
+from opensearch_py_ml.ml_commons import MLCommonClient, ModelTrain
+from tests import OPENSEARCH_TEST_CLIENT
 
-from opensearchpy import OpenSearch
+ml_client = MLCommonClient(OPENSEARCH_TEST_CLIENT)
 
-from opensearch_py_ml.ml_commons import MLCommonClient, ModelTrain
+
+@pytest.fixture
+def iris_index():
+    index_name = "test__index__iris_data"
+    index_mapping = {
+        "mappings": {
+            "properties": {
+                "sepal_length": {"type": "float"},
+                "sepal_width": {"type": "float"},
+                "petal_length": {"type": "float"},
+                "petal_width": {"type": "float"},
+                "species": {"type": "keyword"},
+            }
+        }
+    }
+
+    if ml_client._client.indices.exists(index=index_name):
+        ml_client._client.indices.delete(index=index_name)
+    ml_client._client.indices.create(index=index_name, body=index_mapping)
+
+    iris = load_iris()
+    iris_data = iris.data
+    iris_target = iris.target
+    iris_species = [iris.target_names[i] for i in iris_target]
+
+    actions = [
+        {
+            "_index": index_name,
+            "_source": {
+                "sepal_length": sepal_length,
+                "sepal_width": sepal_width,
+                "petal_length": petal_length,
+                "petal_width": petal_width,
+                "species": species,
+            },
+        }
+        for (sepal_length, sepal_width, petal_length, petal_width), species in zip(
+            iris_data, iris_species
+        )
+    ]
+
+    helpers.bulk(ml_client._client, actions)
+    # without the sleep, test is failing.
+    time.sleep(2)
+
+    yield index_name
+
+    ml_client._client.indices.delete(index=index_name)
 
 
-def test_init(opensearch_client):
-    ml_client = MLCommonClient(opensearch_client)
+def test_init():
     assert isinstance(ml_client._client, OpenSearch)
     assert isinstance(ml_client._model_train, ModelTrain)
 
 
-def test_train(iris_index_client):
-    client, test_index_name = iris_index_client
-    ml_client = MLCommonClient(client)
+def test_train(iris_index):
     algorithm_name = "kmeans"
     input_json_sync = {
         "parameters": {"centroids": 3, "iterations": 10, "distance_type": "COSINE"},
         "input_query": {
             "_source": ["petal_length", "petal_width"],
             "size": 10000,
         },
-        "input_index": [test_index_name],
+        "input_index": [iris_index],
     }
     response = ml_client.train_model(algorithm_name, input_json_sync)
     assert isinstance(response, dict)
@@ -41,7 +91,7 @@ def test_train(iris_index_client):
             "_source": ["petal_length", "petal_width"],
             "size": 10000,
         },
-        "input_index": [test_index_name],
+        "input_index": [iris_index],
     }
     response = ml_client.train_model(algorithm_name, input_json_async, is_async=True)