diff --git a/kairon/shared/data/model_processor.py b/kairon/shared/data/model_processor.py
index 5a4898e69..3604d9aa3 100644
--- a/kairon/shared/data/model_processor.py
+++ b/kairon/shared/data/model_processor.py
@@ -71,7 +71,7 @@ def handle_current_model_training(bot: Text, user: Text):
             raise AppException("No Enqueued model training present for this bot.")
         model_training_object = model_training.get()
         if model_training_object.status == EVENT_STATUS.INPROGRESS.value:
-            raise AppException("Previous model training in progress. Please wait for sometime.")
+            raise AppException("Previous model training in progress.")
         if model_training_object.status == EVENT_STATUS.ENQUEUED.value:
             ModelProcessor.set_training_status(bot=bot, user=user, status=EVENT_STATUS.FAIL.value)
 
diff --git a/tests/integration_test/services_test.py b/tests/integration_test/services_test.py
index 06a61c29b..413bc0965 100644
--- a/tests/integration_test/services_test.py
+++ b/tests/integration_test/services_test.py
@@ -11900,8 +11900,53 @@ def test_add_training_example_case_insensitivity():
 
 @responses.activate
 @patch("kairon.shared.data.model_processor.ModelProcessor.is_daily_training_limit_exceeded", autospec=True)
-def test_retrain(mock_training_limit):
+def test_retrain_with_no_enqueued_model_training(mock_training_limit):
+    mock_training_limit.return_value = False
+    event_url = urljoin(Utility.environment['events']['server_url'], f"/api/events/execute/{EventClass.model_training}")
+    responses.add(
+        "POST", event_url, json={"success": True, "message": "Event triggered successfully!"}
+    )
+    response = client.post(
+        f"/api/bot/{pytest.bot}/retrain",
+        headers={"Authorization": pytest.token_type + " " + pytest.access_token},
+    )
+    actual = response.json()
+    print(actual)
+    assert not actual["success"]
+    assert actual["error_code"] == 422
+    assert actual["data"] is None
+    assert actual["message"] == "No Enqueued model training present for this bot."
+
+
+@responses.activate
+@patch("kairon.shared.data.model_processor.ModelProcessor.handle_current_model_training", autospec=True)
+@patch("kairon.shared.data.model_processor.ModelProcessor.is_daily_training_limit_exceeded", autospec=True)
+def test_retrain_with_model_training_in_progress(mock_training_limit, mock_handle_current_model_training):
+    mock_handle_current_model_training.side_effect = AppException("Previous model training in progress.")
+    mock_training_limit.return_value = False
+    event_url = urljoin(Utility.environment['events']['server_url'], f"/api/events/execute/{EventClass.model_training}")
+    responses.add(
+        "POST", event_url, json={"success": True, "message": "Event triggered successfully!"}
+    )
+    response = client.post(
+        f"/api/bot/{pytest.bot}/train",
+        headers={"Authorization": pytest.token_type + " " + pytest.access_token},
+    )
+    response = client.post(
+        f"/api/bot/{pytest.bot}/retrain",
+        headers={"Authorization": pytest.token_type + " " + pytest.access_token},
+    )
+    actual = response.json()
+    print(actual)
+    assert not actual["success"]
+    assert actual["error_code"] == 422
+    assert actual["data"] is None
+    assert actual["message"] == "Previous model training in progress."
+
 
+@responses.activate
+@patch("kairon.shared.data.model_processor.ModelProcessor.is_daily_training_limit_exceeded", autospec=True)
+def test_retrain(mock_training_limit):
     mock_training_limit.return_value = False
     event_url = urljoin(Utility.environment['events']['server_url'], f"/api/events/execute/{EventClass.model_training}")
     responses.add(
diff --git a/tests/unit_test/data_processor/data_processor_test.py b/tests/unit_test/data_processor/data_processor_test.py
index 520df81f7..dbff80a82 100644
--- a/tests/unit_test/data_processor/data_processor_test.py
+++ b/tests/unit_test/data_processor/data_processor_test.py
@@ -980,7 +980,7 @@ def test_handle_current_model_training_with_in_progress_model_training(self):
         bot = "test_bot"
         user = "test_user"
         ModelProcessor.set_training_status(bot=bot, user=user, status=EVENT_STATUS.INPROGRESS.value)
-        with pytest.raises(AppException, match="Previous model training in progress. Please wait for sometime."):
+        with pytest.raises(AppException, match="Previous model training in progress."):
             ModelProcessor.handle_current_model_training(bot=bot, user=user)
 
     @pytest.mark.asyncio