test(utils): cover embedding drop params in CI

Signed-off-by: Hasnaat Hussain <hasnaat.hussain.2@gmail.com>

litellm/utils.py

@@ -3430,14 +3430,10 @@ def get_optional_params_embeddings(
     special_params: Final = passed_params.pop("kwargs")
 
     drop_params = passed_params.pop("drop_params", None)
-    if drop_params is None:
-        drop_params = special_params.pop("drop_params", None)
     if drop_params is None:
         drop_params = litellm.drop_params or False
 
     additional_drop_params = passed_params.pop("additional_drop_params", None)
-    if additional_drop_params is None:
-        additional_drop_params = special_params.pop("additional_drop_params", None)
 
     allowed_openai_params = passed_params.pop("allowed_openai_params", None) or []
     # Remove function objects from passed_params to avoid JSON serialization errors

tests/llm_translation/test_optional_params.py

@@ -1120,6 +1120,38 @@ def test_lm_studio_embedding_params():
     assert len(optional_params) == 0
 
 
+@pytest.mark.parametrize("provider", ["azure", "together_ai"])
+def test_embedding_dimensions_drop_params_for_openai_compatible_provider(provider):
+    previous_drop_params = litellm.drop_params
+    try:
+        litellm.drop_params = False
+        dropped = get_optional_params_embeddings(
+            model=f"{provider}/dummy-model",
+            custom_llm_provider=provider,
+            dimensions=512,
+            drop_params=True,
+        )
+        assert "dimensions" not in dropped
+
+        litellm.drop_params = True
+        dropped_globally = get_optional_params_embeddings(
+            model=f"{provider}/dummy-model",
+            custom_llm_provider=provider,
+            dimensions=512,
+        )
+        assert "dimensions" not in dropped_globally
+
+        litellm.drop_params = False
+        preserved = get_optional_params_embeddings(
+            model=f"{provider}/dummy-model",
+            custom_llm_provider=provider,
+            dimensions=512,
+        )
+        assert preserved["dimensions"] == 512
+    finally:
+        litellm.drop_params = previous_drop_params
+
+
 def test_ollama_pydantic_obj():
     from pydantic import BaseModel
 

tests/local_testing/test_get_optional_params_embeddings.py

@@ -160,97 +160,3 @@ def test_openai_non_text_embedding_3_drop_params_global():
         assert "dimensions" not in optional_params
     finally:
         litellm.drop_params = prev_drop_params
-
-
-def test_azure_and_openai_compatible_drop_params():
-    """
-    Verify that dimensions parameter is correctly dropped on Azure and OpenAI compatible calls
-    when drop_params is True (either per-call or globally), while preserving it otherwise.
-    """
-    prev_drop_params = litellm.drop_params
-
-    # 1. Test Azure drop_params=True (per-call)
-    litellm.drop_params = False
-    model, custom_llm_provider, _, _ = get_llm_provider(
-        model="azure/dummy-model"
-    )
-    optional_params = get_optional_params_embeddings(
-        model=model,
-        dimensions=512,
-        custom_llm_provider=custom_llm_provider,
-        drop_params=True,
-    )
-    assert "dimensions" not in optional_params
-
-    # 2. Test Azure drop_params=True (global)
-    litellm.drop_params = True
-    optional_params = get_optional_params_embeddings(
-        model=model,
-        dimensions=512,
-        custom_llm_provider=custom_llm_provider,
-    )
-    assert "dimensions" not in optional_params
-
-    # 3. Test Azure drop_params=False (preserves dimensions parameter)
-    litellm.drop_params = False
-    optional_params = get_optional_params_embeddings(
-        model=model,
-        dimensions=512,
-        custom_llm_provider=custom_llm_provider,
-    )
-    assert "dimensions" in optional_params
-    assert optional_params["dimensions"] == 512
-
-    # 4. Test OpenAI compatible (Together AI) drop_params=True (per-call)
-    model, custom_llm_provider, _, _ = get_llm_provider(
-        model="together_ai/dummy-model"
-    )
-    optional_params = get_optional_params_embeddings(
-        model=model,
-        dimensions=512,
-        custom_llm_provider=custom_llm_provider,
-        drop_params=True,
-    )
-    assert "dimensions" not in optional_params
-
-    # 5. Test OpenAI compatible (Together AI) drop_params=True (global)
-    litellm.drop_params = True
-    optional_params = get_optional_params_embeddings(
-        model=model,
-        dimensions=512,
-        custom_llm_provider=custom_llm_provider,
-    )
-    assert "dimensions" not in optional_params
-
-    # 6. Test OpenAI compatible (Together AI) drop_params=False (preserves dimensions parameter)
-    litellm.drop_params = False
-    optional_params = get_optional_params_embeddings(
-        model=model,
-        dimensions=512,
-        custom_llm_provider=custom_llm_provider,
-    )
-    assert "dimensions" in optional_params
-    assert optional_params["dimensions"] == 512
-
-    # Restore state
-    litellm.drop_params = prev_drop_params
-
-
-@pytest.mark.parametrize("provider", ["nvidia_nim", "lm_studio", "fireworks_ai"])
-def test_dedicated_openai_compatible_providers_drop_dimensions(provider):
-    """Keep dedicated provider mappings reachable when dimensions is dropped."""
-    prev_drop_params = litellm.drop_params
-    litellm.drop_params = False
-    try:
-        model, custom_llm_provider, _, _ = get_llm_provider(
-            model=f"{provider}/dummy-model"
-        )
-        optional_params = get_optional_params_embeddings(
-            model=model,
-            dimensions=512,
-            custom_llm_provider=custom_llm_provider,
-            drop_params=True,
-        )
-        assert "dimensions" not in optional_params
-    finally:
-        litellm.drop_params = prev_drop_params