--- a
+++ b/development/testcase/simple_test.py
@@ -0,0 +1,76 @@
+import os
+import sys
+import random
+import string
+import asyncio
+import unittest
+from rasa.model import get_model
+from rasa.nlu.test import run_evaluation
+from rasa.core.test import test as core_test
+
+path = './production/rasa-server/rasa/'
+sys.path.append(path)
+
+
+class TestRasaMethods(unittest.TestCase):
+    model_path = './production/rasa-server/rasa/models/'
+    unpacked_model = get_model(model_path)
+    tmp_name = ''.join(random.choices(
+        string.ascii_uppercase + string.digits, k=10))
+
+    """
+    NLU TEST
+    """
+    nlu_model = os.path.join(unpacked_model, "nlu")
+
+    # Normal NLU tests data
+    test_data = './development/testcase/nlu_test.yml'
+    
+    
+    async_test_result = run_evaluation(test_data,
+                                       nlu_model,
+                                       successes=True,
+                                       errors=True,
+                                       output_directory=f'/tmp/{tmp_name}',
+                                       disable_plotting=True,
+                                       report_as_dict=True,
+                                       )
+    test_result = asyncio.run(async_test_result)
+
+    # Test f1_score of intents
+    def test_f1_intent(self):
+        threshold = 1
+        test_result = self.test_result
+        # Check if intent extractor is in the pipeline
+        if test_result['intent_evaluation'] is not None:
+            # Check if multiple intent extractors are in the pipeline
+            if 'report' not in test_result['intent_evaluation']:
+                for intent in test_result['intent_evaluation']:
+                    f1_score = test_result['intent_evaluation'][intent]['f1_score']
+                    print(f1_score)
+                    self.assertTrue(f1_score >= threshold)
+            else:
+                f1_score = test_result['intent_evaluation']['f1_score']
+                print(f1_score)
+                self.assertTrue(f1_score >= threshold)
+
+    # Test f1_score of entities
+    def test_f1_entity(self):
+        threshold = 1
+        test_result = self.test_result
+        # Check if entity extractor is in the pipeline
+        if test_result['entity_evaluation'] is not None:
+            # Check if multiple entity extractors are in the pipeline
+            if 'report' not in test_result['entity_evaluation']:
+                f1_score = test_result['entity_evaluation']['RegexEntityExtractor']['f1_score']
+                print(f1_score)
+                self.assertTrue(f1_score >= threshold)
+            else:
+                f1_score = test_result['entity_evaluation']['f1_score']
+                print(f1_score)
+                self.assertTrue(f1_score >= threshold)
+
+
+if __name__ == '__main__':
+    # Run tests
+    unittest.main()