Merge pull request #42107 from BerriAI/litellm_migrate_tests_p6

test(llms): migrate phase 6 provider unit tests to tests/unit

tests/test_litellm/llms/fal_ai/test_cost_calculator.py

@@ -1,19 +0,0 @@
-import pytest
-
-import litellm
-from litellm.litellm_core_utils.llm_cost_calc.utils import CostCalculatorUtils
-from litellm.llms.fal_ai.cost_calculator import cost_calculator
-from litellm.types.utils import ImageObject, ImageResponse
-
-
-@pytest.fixture(autouse=True)
-def _use_local_model_cost_map(monkeypatch):
-    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
-    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
-    litellm.get_model_info.cache_clear()
-    yield
-    litellm.get_model_info.cache_clear()
-
-
-def _image_response(num_images: int = 1) -> ImageResponse:
-    return ImageResponse(data=[ImageObject(url="https://example.com/img.png") for _ in range(num_images)])

tests/unit/llms/chatgpt/responses/test_chatgpt_responses_transformation.py

@@ -5,6 +5,7 @@ Source: litellm/llms/chatgpt/responses/transformation.py
 """
 
 import json
+from collections.abc import Generator
 from unittest.mock import MagicMock, patch
 
 import httpx
@@ -19,6 +20,15 @@ from litellm.types.utils import LlmProviders
 from litellm.utils import ProviderConfigManager
 
 
+@pytest.fixture
+def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Generator[None, None, None]:
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    litellm.get_model_info.cache_clear()
+    yield
+    litellm.get_model_info.cache_clear()
+
+
 class TestChatGPTResponsesAPITransformation:
     @pytest.mark.parametrize(
         "model_name",

tests/unit/llms/datarobot/test_datarobot.py

@@ -78,27 +78,3 @@ def test_completion_datarobot_with_deployment():
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
 
-
-def test_completion_datarobot_with_environment_variables():
-    """Allow the test to run with environment variables if they are set for integrations."""
-    # If keys are not set, the test will be skipped
-    if os.environ.get("DATAROBOT_API_TOKEN") is None:
-        return
-
-    messages = [
-        {"role": "user", "content": "What's the weather like in San Francisco?"}
-    ]
-    try:
-        response = completion(
-            model="datarobot/vertex_ai/gemini-1.5-flash-002",
-            messages=messages,
-            max_tokens=5,
-            clientId="custom-model",
-        )
-        print(response)
-        assert response["object"] == "chat.completion"
-        assert response["model"] == "gemini-1.5-flash-002"
-        assert len(response["choices"]) == 1
-        assert len(response["choices"][0]["message"]["content"]) > 0
-    except Exception as e:
-        pytest.fail(f"Error occurred: {e}")

tests/unit/llms/deepseek/test_deepseek_cost_calculator.py

@@ -1,3 +1,4 @@
+from collections.abc import Generator
 from datetime import datetime, timezone
 from typing import Final
 
@@ -7,6 +8,16 @@ import litellm
 from litellm._internal_context import pinned_billing_time
 from litellm.types.utils import ModelResponse, PromptTokensDetailsWrapper, Usage
 
+
+@pytest.fixture
+def local_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Generator[None, None, None]:
+    monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True")
+    monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url=""))
+    litellm.get_model_info.cache_clear()
+    yield
+    litellm.get_model_info.cache_clear()
+
+
 PEAK_MOMENTS: Final = (
     pytest.param(datetime(2026, 9, 22, 8, 0, tzinfo=timezone.utc), id="tuesday-08:00"),
     pytest.param(datetime(2026, 9, 25, 9, 59, tzinfo=timezone.utc), id="friday-09:59"),