Merge 7493af5528 into 5337c68dd3

litellm/llms/bedrock/chat/converse_transformation.py

@@ -931,10 +931,12 @@ class AmazonConverseConfig(BaseConfig):
                         litellm.verbose_logger.warning(DROP_UNSUPPORTED_ADAPTIVE_THINKING_WARNING, model)
                 else:
                     optional_params["thinking"] = value
-            elif param == "reasoning_effort" and isinstance(value, str):
-                self._handle_reasoning_effort_parameter(
-                    model=model, reasoning_effort=value, optional_params=optional_params
-                )
+            elif param == "reasoning_effort":
+                effort_value = value.get("effort") if isinstance(value, dict) else value
+                if isinstance(effort_value, str):
+                    self._handle_reasoning_effort_parameter(
+                        model=model, reasoning_effort=effort_value, optional_params=optional_params
+                    )
             elif param == "output_config" and isinstance(value, dict):
                 mapped_output_config = dict(value)
                 normalize_bedrock_opus_output_config_effort(model=model, output_config=mapped_output_config)

litellm/llms/ollama/chat/transformation.py

@@ -170,10 +170,12 @@ class OllamaChatConfig(BaseConfig):
                 if value.get("json_schema") and value["json_schema"].get("schema"):
                     optional_params["format"] = value["json_schema"]["schema"]
             if param == "reasoning_effort" and value is not None:
-                if model.startswith("gpt-oss"):
-                    optional_params["think"] = value
-                else:
-                    optional_params["think"] = value in {"low", "medium", "high"}
+                effort_value = value.get("effort") if isinstance(value, dict) else value
+                if effort_value is not None:
+                    if model.startswith("gpt-oss"):
+                        optional_params["think"] = effort_value
+                    else:
+                        optional_params["think"] = effort_value in {"low", "medium", "high"}
             ### FUNCTION CALLING LOGIC ###
             # Ollama 0.4+ supports native tool calling - pass tools directly
             # and let Ollama handle model capability detection

litellm/llms/ollama/completion/transformation.py

@@ -178,10 +178,12 @@ class OllamaConfig(BaseConfig):
             elif param == "stop":
                 optional_params["stop"] = value
             elif param == "reasoning_effort" and value is not None:
-                if model.startswith("gpt-oss"):
-                    optional_params["think"] = value
-                else:
-                    optional_params["think"] = value in {"low", "medium", "high"}
+                effort_value = value.get("effort") if isinstance(value, dict) else value
+                if effort_value is not None:
+                    if model.startswith("gpt-oss"):
+                        optional_params["think"] = effort_value
+                    else:
+                        optional_params["think"] = effort_value in {"low", "medium", "high"}
             elif param == "response_format" and isinstance(value, dict):
                 if value["type"] == "json_object":
                     optional_params["format"] = "json"

tests/test_litellm/llms/ollama/test_ollama_chat_transformation.py

@@ -904,3 +904,40 @@ class TestOllamaToolCallTransformation:
         assert tool_msg["content"] == "Sunny, 72°F"
         assert "tool_call_id" in tool_msg, "tool_call_id must be forwarded to Ollama"
         assert tool_msg["tool_call_id"] == "call_abc123"
+
+
+class TestOllamaReasoningEffortMapping:
+    """
+    Test reasoning_effort mapping with string and dict formats (Responses API bridge).
+    Regression: https://github.com/BerriAI/litellm/issues/37452
+    """
+
+    def test_map_openai_params_reasoning_effort_string(self):
+        config = OllamaChatConfig()
+        assert config.map_openai_params({"reasoning_effort": "low"}, {}, "qwen3", False) == {"think": True}
+        assert config.map_openai_params({"reasoning_effort": "medium"}, {}, "qwen3", False) == {"think": True}
+        assert config.map_openai_params({"reasoning_effort": "high"}, {}, "qwen3", False) == {"think": True}
+        assert config.map_openai_params({"reasoning_effort": "none"}, {}, "qwen3", False) == {"think": False}
+
+    def test_map_openai_params_reasoning_effort_dict_with_effort(self):
+        config = OllamaChatConfig()
+        result = config.map_openai_params(
+            {"reasoning_effort": {"effort": "medium", "summary": "auto"}}, {}, "qwen3", False
+        )
+        assert result == {"think": True}
+
+        result_low = config.map_openai_params({"reasoning_effort": {"effort": "low"}}, {}, "qwen3", False)
+        assert result_low == {"think": True}
+
+        result_none = config.map_openai_params({"reasoning_effort": {"effort": "none"}}, {}, "qwen3", False)
+        assert result_none == {"think": False}
+
+    def test_map_openai_params_reasoning_effort_dict_summary_only(self):
+        config = OllamaChatConfig()
+        result = config.map_openai_params({"reasoning_effort": {"summary": "auto"}}, {}, "qwen3", False)
+        assert "think" not in result
+
+    def test_map_openai_params_reasoning_effort_gpt_oss(self):
+        config = OllamaChatConfig()
+        result = config.map_openai_params({"reasoning_effort": {"effort": "medium"}}, {}, "gpt-oss-123", False)
+        assert result == {"think": "medium"}

tests/test_litellm/llms/ollama/test_ollama_completion_transformation.py

@@ -502,3 +502,27 @@ class TestOllamaTextCompletionResponseIterator:
         assert result["usage"]["prompt_tokens"] == 10
         assert result["usage"]["completion_tokens"] == 5
         assert result["usage"]["total_tokens"] == 15
+
+
+class TestOllamaCompletionReasoningEffortMapping:
+    @pytest.mark.parametrize(
+        ("reasoning_effort", "model", "expected"),
+        [
+            ("medium", "qwen3", {"think": True}),
+            ("none", "qwen3", {"think": False}),
+            ({"effort": "medium", "summary": "auto"}, "qwen3", {"think": True}),
+            ({"effort": "medium"}, "gpt-oss-123", {"think": "medium"}),
+            ({"summary": "auto"}, "qwen3", {}),
+        ],
+    )
+    def test_map_openai_params_reasoning_effort(self, reasoning_effort, model, expected):
+        config = OllamaConfig()
+
+        result = config.map_openai_params(
+            {"reasoning_effort": reasoning_effort},
+            {},
+            model,
+            False,
+        )
+
+        assert result == expected