diff --git a/.github/workflows/catalog_consistency.yml b/.github/workflows/catalog_consistency.yml
index 4ea4005e1..20de8d87f 100644
--- a/.github/workflows/catalog_consistency.yml
+++ b/.github/workflows/catalog_consistency.yml
@@ -12,7 +12,6 @@ jobs:
      runs-on: ubuntu-latest
      env:
        OS: ubuntu-latest
-       GENAI_KEY: ${{ secrets.GENAI_KEY }}
        UNITXT_DEFAULT_VERBOSITY: error
        DATASETS_VERBOSITY: error
        HF_HUB_VERBOSITY: error
diff --git a/.github/workflows/catalog_preparation.yml b/.github/workflows/catalog_preparation.yml
index a3024f409..468513f30 100644
--- a/.github/workflows/catalog_preparation.yml
+++ b/.github/workflows/catalog_preparation.yml
@@ -12,7 +12,6 @@ jobs:
      runs-on: ubuntu-latest
      env:
        OS: ubuntu-latest
-       GENAI_KEY: ${{ secrets.GENAI_KEY }}
        UNITXT_DEFAULT_VERBOSITY: error
        DATASETS_VERBOSITY: error
        HF_HUB_VERBOSITY: error
diff --git a/src/unitxt/inference.py b/src/unitxt/inference.py
index c6b6b26e0..c35bda5fe 100644
--- a/src/unitxt/inference.py
+++ b/src/unitxt/inference.py
@@ -11,6 +11,9 @@
 from .image_operators import extract_images
 from .logging_utils import get_logger
 from .operator import PackageRequirementsMixin
+from .settings_utils import get_settings
+
+settings = get_settings()
 
 
 class InferenceEngine(abc.ABC, Artifact):
@@ -21,9 +24,20 @@ def _infer(self, dataset):
         """Perform inference on the input dataset."""
         pass
 
+    @abc.abstractmethod
+    def prepare_engine(self):
+        """Perform inference on the input dataset."""
+        pass
+
+    def prepare(self):
+        if not settings.mock_inference_mode:
+            self.prepare_engine()
+
     def infer(self, dataset) -> str:
         """Verifies instances of a dataset and performs inference."""
         [self.verify_instance(instance) for instance in dataset]
+        if settings.mock_inference_mode:
+            return [instance["source"] for instance in dataset]
         return self._infer(dataset)
 
     @deprecation(version="2.0.0")
@@ -122,7 +136,7 @@ def _prepare_pipeline(self):
             model=self.model_name, trust_remote_code=True, **model_args
         )
 
-    def prepare(self):
+    def prepare_engine(self):
         if not self.lazy_load:
             self._prepare_pipeline()
 
@@ -144,13 +158,17 @@ def _infer(self, dataset):
 class MockInferenceEngine(InferenceEngine):
     model_name: str
 
-    def prepare(self):
+    def prepare_engine(self):
         return
 
     def _infer(self, dataset):
         return ["[[10]]" for instance in dataset]
 
 
+class MockModeMixin(Artifact):
+    mock_mode: bool = False
+
+
 class IbmGenAiInferenceEngineParamsMixin(Artifact):
     beam_width: Optional[int] = None
     decoding_method: Optional[Literal["greedy", "sample"]] = None
@@ -201,11 +219,12 @@ class IbmGenAiInferenceEngine(
     data_classification_policy = ["public", "proprietary"]
     parameters: Optional[IbmGenAiInferenceEngineParams] = None
 
-    def prepare(self):
+    def prepare_engine(self):
         from genai import Client, Credentials
 
         api_key_env_var_name = "GENAI_KEY"
         api_key = os.environ.get(api_key_env_var_name)
+
         assert api_key is not None, (
             f"Error while trying to run IbmGenAiInferenceEngine."
             f" Please set the environment param '{api_key_env_var_name}'."
@@ -279,7 +298,7 @@ class OpenAiInferenceEngine(
     data_classification_policy = ["public"]
     parameters: Optional[OpenAiInferenceEngineParams] = None
 
-    def prepare(self):
+    def prepare_engine(self):
         from openai import OpenAI
 
         api_key_env_var_name = "OPENAI_API_KEY"
@@ -490,7 +509,7 @@ def _initialize_wml_client(self):
         client.set.default_project(self.credentials["project_id"])
         return client
 
-    def prepare(self):
+    def prepare_engine(self):
         self._client = self._initialize_wml_client()
 
         self._set_inference_parameters()
@@ -541,7 +560,7 @@ def _prepare_engine(self):
 
         self.processor = AutoProcessor.from_pretrained(self.model_name)
 
-    def prepare(self):
+    def prepare_engine(self):
         if not self.lazy_load:
             self._prepare_engine()
 
diff --git a/src/unitxt/settings_utils.py b/src/unitxt/settings_utils.py
index c6bbd8eac..9018a806c 100644
--- a/src/unitxt/settings_utils.py
+++ b/src/unitxt/settings_utils.py
@@ -146,6 +146,7 @@ def __getattr__(self, key):
     settings.seed = (int, 42)
     settings.skip_artifacts_prepare_and_verify = (bool, False)
     settings.data_classification_policy = None
+    settings.mock_inference_mode = (bool, False)
 
 if Constants.is_uninitilized():
     constants = Constants()
diff --git a/tests/utils.py b/tests/utils.py
index 1c0c1a9c6..36b76fa73 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -33,7 +33,7 @@ def setUpClass(cls):
         enable_explicit_format()
         unitxt.settings.allow_unverified_code = True
         unitxt.settings.use_only_local_catalogs = True
-        # unitxt.settings.global_loader_limit = 300
+        unitxt.settings.mock_inference_mode = True
         unitxt.settings.max_log_message_size = 1000000000000
         if settings.default_verbosity in ["error", "critical"]:
             if not sys.warnoptions: