Merge 86c9269b42 into a66dc50efb

litellm/llms/ollama/chat/transformation.py

@@ -164,8 +164,8 @@ class OllamaChatConfig(BaseConfig):
                 optional_params["top_p"] = value
             if param == "frequency_penalty":
                 optional_params["repeat_penalty"] = value
-            if param == "stop":
-                optional_params["stop"] = value
+            if param == "stop" and value != "":
+                optional_params["stop"] = [value] if isinstance(value, str) else value
             if param == "response_format" and isinstance(value, dict) and value.get("type") == "json_object":
                 optional_params["format"] = "json"
             if param == "response_format" and isinstance(value, dict) and value.get("type") == "json_schema":

litellm/llms/ollama/completion/transformation.py

@@ -246,8 +246,8 @@ class OllamaConfig(BaseConfig):
                 optional_params["top_p"] = value
             elif param == "frequency_penalty":
                 optional_params["frequency_penalty"] = value
-            elif param == "stop":
-                optional_params["stop"] = value
+            elif param == "stop" and value != "":
+                optional_params["stop"] = [value] if isinstance(value, str) else value
             elif param == "reasoning_effort" and value is not None:
                 if model.startswith("gpt-oss"):
                     optional_params["think"] = value

tests/unit/llms/ollama/test_ollama_chat_transformation.py

@@ -27,6 +27,26 @@ from litellm.types.utils import Choices, EmbeddingResponse, Message, ModelRespon
 from unittest import mock
 
 
+@pytest.mark.parametrize(
+    "stop, expected",
+    [
+        ("END", ["END"]),
+        ("", None),
+        (["END", "STOP"], ["END", "STOP"]),
+        ([""], [""]),
+        ([], []),
+    ],
+)
+def test_stop_is_sent_as_an_array(stop: str | list[str], expected: list[str] | None) -> None:
+    optional_params: Final = get_optional_params(
+        model="test-model", custom_llm_provider="ollama_chat", stop=stop
+    )
+    if expected is None:
+        assert "stop" not in optional_params
+    else:
+        assert optional_params["stop"] == expected
+
+
 class TestEvent(BaseModel):
     name: str
     value: int

tests/unit/llms/ollama/test_ollama_completion_transformation.py

@@ -19,6 +19,26 @@ from litellm.llms.ollama.completion.transformation import (
 from litellm.types.utils import Message, ModelResponse, ModelResponseStream
 
 
+@pytest.mark.parametrize(
+    "stop, expected",
+    [
+        ("END", ["END"]),
+        ("", None),
+        (["END", "STOP"], ["END", "STOP"]),
+        ([""], [""]),
+        ([], []),
+    ],
+)
+def test_stop_is_sent_as_an_array(stop: str | list[str], expected: list[str] | None) -> None:
+    optional_params: Final = litellm.utils.get_optional_params(
+        model="test-model", custom_llm_provider="ollama", stop=stop
+    )
+    if expected is None:
+        assert "stop" not in optional_params
+    else:
+        assert optional_params["stop"] == expected
+
+
 class TestOllamaConfig:
     def test_transform_response_standard(self):
         # Initialize config