Fix invalid function schema error for tools with None parameters

Normalize tool function parameters before forwarding to OpenAI API.
When parameters is None or missing, default to a valid empty object
schema {"type": "object", "properties": {}}. This prevents the
BadRequestError reported in #22016.

Fixes https://github.com/galaxyproject/galaxy/issues/22016

lib/galaxy/webapps/galaxy/api/plugins.py

@@ -238,6 +238,9 @@ class FastAPIPlugins:
         if len(original_tools) <= MAX_TOOLS:
             for tool in original_tools:
                 tool_dict = tool.model_dump()
+                func = tool_dict.get("function", {})
+                if func.get("parameters") is None:
+                    func["parameters"] = {"type": "object", "properties": {}}
                 size = len(json.dumps(tool_dict, separators=(",", ":")).encode("utf-8"))
                 if size > MAX_TOOL_BYTES:
                     return self._create_error("Tool schema too large.")

test/integration/test_plugins.py

@@ -216,6 +216,65 @@ class TestVisualizationPluginsApi(IntegrationTestCase):
         forwarded_tools = call_kwargs["tools"]
         assert forwarded_tools[0]["function"]["description"] == "Select a processing step"
 
+    @patch("galaxy.webapps.galaxy.api.plugins.AsyncOpenAI")
+    def test_tool_with_none_parameters_normalized(self, mock_client):
+        mock_response = MagicMock()
+        mock_response.model_dump.return_value = {"id": "test", "choices": []}
+        mock_instance = MagicMock()
+        mock_instance.chat.completions.create = AsyncMock(return_value=mock_response)
+        mock_client.return_value = mock_instance
+        payload = _create_chat_payload(
+            {
+                "tools": [
+                    {
+                        "type": "function",
+                        "function": {
+                            "name": "choose_process",
+                            "description": "Select a processing step",
+                            "parameters": None,
+                        },
+                    }
+                ]
+            }
+        )
+        response = self._post_payload(payload)
+        self._assert_status_code_is(response, 200)
+        call_kwargs = mock_instance.chat.completions.create.call_args.kwargs
+        forwarded_tools = call_kwargs["tools"]
+        assert forwarded_tools[0]["function"]["parameters"] == {
+            "type": "object",
+            "properties": {},
+        }
+
+    @patch("galaxy.webapps.galaxy.api.plugins.AsyncOpenAI")
+    def test_tool_with_missing_parameters_normalized(self, mock_client):
+        mock_response = MagicMock()
+        mock_response.model_dump.return_value = {"id": "test", "choices": []}
+        mock_instance = MagicMock()
+        mock_instance.chat.completions.create = AsyncMock(return_value=mock_response)
+        mock_client.return_value = mock_instance
+        payload = _create_chat_payload(
+            {
+                "tools": [
+                    {
+                        "type": "function",
+                        "function": {
+                            "name": "choose_process",
+                            "description": "Select a processing step",
+                        },
+                    }
+                ]
+            }
+        )
+        response = self._post_payload(payload)
+        self._assert_status_code_is(response, 200)
+        call_kwargs = mock_instance.chat.completions.create.call_args.kwargs
+        forwarded_tools = call_kwargs["tools"]
+        assert forwarded_tools[0]["function"]["parameters"] == {
+            "type": "object",
+            "properties": {},
+        }
+
     @patch("galaxy.webapps.galaxy.api.plugins.AsyncOpenAI")
     def test_provider_error_body_forwarded(self, mock_client):
         class MockOpenAIError(APIError):