Python: Fix single-tool input handling in OpenAIResponsesClient._prepare_tools_for_openai

python/packages/core/agent_framework/openai/_responses_client.py

@@ -43,6 +43,8 @@
     FunctionInvocationConfiguration,
     FunctionInvocationLayer,
     FunctionTool,
+    ToolTypes,
+    normalize_tools,
 )
 from .._types import (
     Annotation,
@@ -425,21 +427,24 @@ def _get_conversation_id(
 
     # region Prep methods
 
-    def _prepare_tools_for_openai(self, tools: Sequence[Any] | None) -> list[Any]:
+    def _prepare_tools_for_openai(
+        self, tools: ToolTypes | Callable[..., Any] | Sequence[ToolTypes | Callable[..., Any]] | None
+    ) -> list[Any]:
         """Prepare tools for the OpenAI Responses API.
 
         Converts FunctionTool to Responses API format. All other tools pass through unchanged.
 
         Args:
-            tools: Sequence of tools to prepare.
+            tools: A single tool or sequence of tools to prepare.
 
         Returns:
             List of tool parameters ready for the OpenAI API.
         """
-        if not tools:
+        tools_list = normalize_tools(tools)
+        if not tools_list:
             return []
         response_tools: list[Any] = []
-        for tool in tools:
+        for tool in tools_list:
             if isinstance(tool, FunctionTool):
                 params = tool.parameters()
                 params["additionalProperties"] = False

python/packages/core/tests/openai/test_openai_responses_client.py

@@ -1193,6 +1193,52 @@ def test_prepare_tools_for_openai_with_mcp() -> None:
     assert "require_approval" in mcp
 
 
+def test_prepare_tools_for_openai_single_function_tool() -> None:
+    """Test that a single FunctionTool (not wrapped in a list) is handled correctly."""
+    client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
+
+    @tool
+    def hello(name: str) -> str:
+        """Say hello."""
+        return name
+
+    resp_tools = client._prepare_tools_for_openai(hello)
+    assert isinstance(resp_tools, list)
+    assert len(resp_tools) == 1
+    tool_def = resp_tools[0]
+    assert tool_def["type"] == "function"
+    assert tool_def["name"] == "hello"
+    assert tool_def["strict"] is False
+    assert "parameters" in tool_def
+    params = tool_def["parameters"]
+    assert isinstance(params, dict)
+    assert params.get("type") == "object"
+    assert "properties" in params
+    assert "name" in params["properties"]
+    assert params["properties"]["name"]["type"] == "string"
+
+
+def test_prepare_tools_for_openai_single_dict_tool() -> None:
+    """Test that a single dict tool (not wrapped in a list) is handled correctly."""
+    client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
+
+    web_tool = OpenAIResponsesClient.get_web_search_tool(search_context_size="low")
+    resp_tools = client._prepare_tools_for_openai(web_tool)
+    assert isinstance(resp_tools, list)
+    assert len(resp_tools) == 1
+    assert "type" in resp_tools[0]
+    assert resp_tools[0]["search_context_size"] == "low"
+
+
+def test_prepare_tools_for_openai_none() -> None:
+    """Test that passing None returns an empty list."""
+    client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
+
+    resp_tools = client._prepare_tools_for_openai(None)
+    assert isinstance(resp_tools, list)
+    assert len(resp_tools) == 0
+
+
 def test_parse_response_from_openai_with_mcp_approval_request() -> None:
     """Test that a non-streaming mcp_approval_request is parsed into FunctionApprovalRequestContent."""
     client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")