fix: handle non-string function arguments in tool calls and add corre…

…sponding warnings (#5260)

python/packages/autogen-ext/src/autogen_ext/models/openai/_openai_client.py

@@ -571,14 +571,24 @@ async def create(
                     stacklevel=2,
                 )
             # NOTE: If OAI response type changes, this will need to be updated
-            content = [
-                FunctionCall(
-                    id=x.id,
-                    arguments=x.function.arguments,
-                    name=normalize_name(x.function.name),
+            content = []
+            for tool_call in choice.message.tool_calls:
+                if not isinstance(tool_call.function.arguments, str):
+                    warnings.warn(
+                        f"Tool call function arguments field is not a string: {tool_call.function.arguments}."
+                        "This is unexpected and may due to the API used not returning the correct type. "
+                        "Attempting to convert it to string.",
+                        stacklevel=2,
+                    )
+                    if isinstance(tool_call.function.arguments, dict):
+                        tool_call.function.arguments = json.dumps(tool_call.function.arguments)
+                content.append(
+                    FunctionCall(
+                        id=tool_call.id,
+                        arguments=tool_call.function.arguments,
+                        name=normalize_name(tool_call.function.name),
+                    )
                 )
-                for x in choice.message.tool_calls
-            ]
             finish_reason = "tool_calls"
         else:
             finish_reason = choice.finish_reason

python/packages/autogen-ext/tests/models/test_openai_model_client.py

@@ -619,6 +619,31 @@ async def test_tool_calling(monkeypatch: pytest.MonkeyPatch) -> None:
             object="chat.completion",
             usage=CompletionUsage(prompt_tokens=10, completion_tokens=5, total_tokens=0),
         ),
+        # Should raise warning when function arguments is not a string.
+        ChatCompletion(
+            id="id6",
+            choices=[
+                Choice(
+                    finish_reason="tool_calls",
+                    index=0,
+                    message=ChatCompletionMessage(
+                        content=None,
+                        tool_calls=[
+                            ChatCompletionMessageToolCall(
+                                id="1",
+                                type="function",
+                                function=Function.construct(name="_pass_function", arguments={"input": "task"}),  # type: ignore
+                            )
+                        ],
+                        role="assistant",
+                    ),
+                )
+            ],
+            created=0,
+            model=model,
+            object="chat.completion",
+            usage=CompletionUsage(prompt_tokens=10, completion_tokens=5, total_tokens=0),
+        ),
     ]
     mock = _MockChatCompletion(chat_completions)
     monkeypatch.setattr(AsyncCompletions, "create", mock.mock_create)
@@ -676,8 +701,16 @@ async def test_tool_calling(monkeypatch: pytest.MonkeyPatch) -> None:
     assert create_result.content == "I should make a tool call."
     assert create_result.finish_reason == "stop"
 
+    # Should raise warning when function arguments is not a string.
+    with pytest.warns(UserWarning, match="Tool call function arguments field is not a string"):
+        create_result = await model_client.create(
+            messages=[UserMessage(content="Hello", source="user")], tools=[pass_tool]
+        )
+        assert create_result.content == [FunctionCall(id="1", arguments=r'{"input": "task"}', name="_pass_function")]
+        assert create_result.finish_reason == "function_calls"
+
 
-async def _test_model_client(model_client: OpenAIChatCompletionClient) -> None:
+async def _test_model_client_basic_completion(model_client: OpenAIChatCompletionClient) -> None:
     # Test basic completion
     create_result = await model_client.create(
         messages=[
@@ -688,6 +721,8 @@ async def _test_model_client(model_client: OpenAIChatCompletionClient) -> None:
     assert isinstance(create_result.content, str)
     assert len(create_result.content) > 0
 
+
+async def _test_model_client_with_function_calling(model_client: OpenAIChatCompletionClient) -> None:
     # Test tool calling
     pass_tool = FunctionTool(_pass_function, name="pass_tool", description="pass session.")
     fail_tool = FunctionTool(_fail_function, name="fail_tool", description="fail session.")
@@ -755,7 +790,8 @@ async def test_openai() -> None:
         model="gpt-4o-mini",
         api_key=api_key,
     )
-    await _test_model_client(model_client)
+    await _test_model_client_basic_completion(model_client)
+    await _test_model_client_with_function_calling(model_client)
 
 
 @pytest.mark.asyncio
@@ -775,7 +811,29 @@ async def test_gemini() -> None:
             "family": ModelFamily.UNKNOWN,
         },
     )
-    await _test_model_client(model_client)
+    await _test_model_client_basic_completion(model_client)
+    await _test_model_client_with_function_calling(model_client)
+
+
+@pytest.mark.asyncio
+async def test_hugging_face() -> None:
+    api_key = os.getenv("HF_TOKEN")
+    if not api_key:
+        pytest.skip("HF_TOKEN not found in environment variables")
+
+    model_client = OpenAIChatCompletionClient(
+        model="microsoft/Phi-3.5-mini-instruct",
+        api_key=api_key,
+        base_url="https://api-inference.huggingface.co/v1/",
+        model_info={
+            "function_calling": False,
+            "json_output": False,
+            "vision": False,
+            "family": ModelFamily.UNKNOWN,
+        },
+    )
+
+    await _test_model_client_basic_completion(model_client)
 
 
 # TODO: add integration tests for Azure OpenAI using AAD token.