build: merge branch

tests/llm_translation/base_llm_unit_tests.py

@@ -254,7 +254,6 @@ class BaseLLMChatTest(ABC):
         # relevant issue: https://github.com/BerriAI/litellm/issues/6741
         assert response.choices[0].message.content is not None
 
-
     @pytest.mark.parametrize(
         "response_format",
         [
@@ -337,7 +336,6 @@ class BaseLLMChatTest(ABC):
 
         print(f"translated_params={translated_params}")
 
-
     @pytest.mark.flaky(retries=6, delay=1)
     def test_json_response_pydantic_obj(self):
         litellm.set_verbose = True
@@ -613,6 +611,46 @@ class BaseLLMChatTest(ABC):
 
         assert response is not None
 
+    def test_image_url_string(self):
+        litellm.set_verbose = True
+        from litellm.utils import supports_vision
+
+        os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
+        litellm.model_cost = litellm.get_model_cost_map(url="")
+
+        image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
+
+        base_completion_call_args = self.get_base_completion_call_args()
+        if not supports_vision(base_completion_call_args["model"], None):
+            pytest.skip("Model does not support image input")
+        elif "http://" in image_url and "fireworks_ai" in base_completion_call_args.get(
+            "model"
+        ):
+            pytest.skip("Model does not support http:// input")
+
+        image_url_param = image_url
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "What's in this image?"},
+                    {
+                        "type": "image_url",
+                        "image_url": image_url_param,
+                    },
+                ],
+            }
+        ]
+
+        try:
+            response = self.completion_function(
+                **base_completion_call_args, messages=messages
+            )
+        except litellm.InternalServerError:
+            pytest.skip("Model is overloaded")
+
+        assert response is not None
+
     @pytest.mark.flaky(retries=4, delay=1)
     def test_prompt_caching(self):
         litellm.set_verbose = True