Merge 42ca54b911 into 0b39e5faf3

litellm/llms/ollama/chat/transformation.py

@@ -140,6 +140,7 @@ class OllamaChatConfig(BaseConfig):
             "temperature",
             "seed",
             "frequency_penalty",
+            "presence_penalty",
             "stop",
             "tools",
             "tool_choice",
@@ -172,8 +173,13 @@ class OllamaChatConfig(BaseConfig):
                 optional_params["seed"] = value
             if param == "top_p":
                 optional_params["top_p"] = value
+            # Ollama exposes OpenAI's additive penalties under the same names.
+            # `repeat_penalty` is a different, multiplicative setting (1.0 = off),
+            # so forwarding an OpenAI value of 0 to it would invert the penalty.
             if param == "frequency_penalty":
-                optional_params["repeat_penalty"] = value
+                optional_params["frequency_penalty"] = value
+            if param == "presence_penalty":
+                optional_params["presence_penalty"] = value
             if param == "stop":
                 optional_params["stop"] = value
             if param == "response_format" and isinstance(value, dict) and value.get("type") == "json_object":

litellm/llms/ollama/completion/transformation.py

@@ -221,6 +221,7 @@ class OllamaConfig(BaseConfig):
             "temperature",
             "seed",
             "frequency_penalty",
+            "presence_penalty",
             "stop",
             "response_format",
             "max_completion_tokens",
@@ -247,6 +248,8 @@ class OllamaConfig(BaseConfig):
                 optional_params["top_p"] = value
             elif param == "frequency_penalty":
                 optional_params["frequency_penalty"] = value
+            elif param == "presence_penalty":
+                optional_params["presence_penalty"] = value
             elif param == "stop":
                 optional_params["stop"] = value
             elif param == "reasoning_effort" and value is not None:

tests/unit/llms/ollama/test_ollama_chat_transformation.py

@@ -1309,3 +1309,43 @@ def test_reasoning_effort_with_a_matching_think_value_does_not_warn(
 
     assert result["think"] is think
     assert _warnings_naming(caplog, "reasoning_effort") == ()
+
+
+class TestOllamaChatPenaltyParams:
+    """OpenAI's penalties are additive (0 = off); Ollama's `repeat_penalty` is multiplicative (1.0 = off)."""
+
+    def test_frequency_penalty_is_forwarded_under_its_own_name(self):
+        optional_params = get_optional_params(
+            model="ollama_chat/test-model",
+            frequency_penalty=0,
+            custom_llm_provider="ollama_chat",
+        )
+
+        assert optional_params["frequency_penalty"] == 0
+        assert "repeat_penalty" not in optional_params
+
+    def test_presence_penalty_is_forwarded(self):
+        optional_params = get_optional_params(
+            model="ollama_chat/test-model",
+            presence_penalty=0.5,
+            custom_llm_provider="ollama_chat",
+        )
+
+        assert optional_params["presence_penalty"] == 0.5
+
+    def test_presence_penalty_is_a_supported_param(self):
+        supported = OllamaChatConfig().get_supported_openai_params("test-model")
+
+        assert "presence_penalty" in supported
+        assert "frequency_penalty" in supported
+
+    def test_explicit_repeat_penalty_is_passed_through(self):
+        optional_params = get_optional_params(
+            model="ollama_chat/test-model",
+            frequency_penalty=0.2,
+            repeat_penalty=1.3,
+            custom_llm_provider="ollama_chat",
+        )
+
+        assert optional_params["repeat_penalty"] == 1.3
+        assert optional_params["frequency_penalty"] == 0.2

tests/unit/llms/ollama/test_ollama_completion_transformation.py

@@ -1100,3 +1100,15 @@ def test_reasoning_effort_ollama_honors_does_not_warn(
 
     assert result["think"] == think
     assert _reasoning_effort_warnings(caplog) == ()
+
+
+def test_map_openai_params_forwards_presence_penalty() -> None:
+    config = OllamaConfig()
+
+    assert "presence_penalty" in config.get_supported_openai_params("test-model")
+    assert config.map_openai_params(
+        non_default_params={"presence_penalty": 0.5},
+        optional_params={},
+        model="test-model",
+        drop_params=False,
+    ) == {"presence_penalty": 0.5}