Model returns mutiple tools to call even when `parallel_tool_calls` is set to `False`

I’m experimenting with the OpenAI Agents SDK (Python) and ran into unexpected behavior with parallel_tool_calls.

According to the docs, setting parallel_tool_calls=False should ensure that the model makes at most one tool call per turn. However, I’m still seeing multiple tool calls returned in the assistant response.

My Code:

client = AsyncOpenAI(
    api_key=GEMINI_API_KEY,
    base_url=BASE_URL
)
model = OpenAIChatCompletionsModel(
    openai_client=client,
    model="gemini-2.0-flash" # using openai sdk with gemini model
)

# Emited some code for brevity

async def main():
    agent = Agent[UserInfo](
        name="Assistant",
        model=model,
        tools=[fetch_user_uid, fetch_weather], # Provided two tools
        model_settings=ModelSettings(parallel_tool_calls=False) # Setting `parallel_tool_calls` to false.
    )

    result = await Runner.run(
        starting_agent=agent,
        input="what's user uid and what's the weather in karachi?", # asking question to check if the model is calling both tools
        context=user_info,
    )

if __name__ == "__main__":
    asyncio.run(main())

Logs:

...
LLM resp:
{
  "content": null,
  "refusal": null,
  "role": "assistant",
  "annotations": null,
  "audio": null,
  "function_call": null,
  "tool_calls": [ # Model is asking to call both tools even when `parallel_tool_calls` is set to `False`
    {
      "id": "",
      "function": {
        "arguments": "{}",
        "name": "fetch_user_uid"
      },
      "type": "function"
    },
    {
      "id": "",
      "function": {
        "arguments": "{\"city\":\"karachi\"}",
        "name": "fetch_weather"
      },
      "type": "function"
    }
  ]
}

...

Expected results:

LLM calls at most one tool call per turn.

Actual results:

LLM is calling both tools even when parallel_tool_calls is set to False