unexpected error format in response (status code: 500) with gpt-oss:20b

Hello there!

Not quite sure if it's relevant to https://github.com/ollama/ollama/issues/11704 or is it a separate thing.

I have updated to the latest version of ollama (which is 0.11.4 as of now). I'm using an official ollama python library (0.5.3) and still constantly getting 500 errors with gpt-oss:20b

unexpected error format in response (status code: 500)
Traceback (most recent call last):
  File "/home/user/test_agent/benchmark.py", line 479, in wrapper
    result = func(*args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^
  File "/home/user/test_agent/agent.py", line 581, in llm_process_question
    response = OllamaClient.chat(model=model_name, messages=messages)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/user/miniconda3/envs/test_ollama/lib/python3.12/site-packages/ollama/_client.py", line 342, in chat
    return self._request(
           ^^^^^^^^^^^^^^
  File "/home/user/miniconda3/envs/test_ollama/lib/python3.12/site-packages/ollama/_client.py", line 180, in _request
    return cls(**self._request_raw(*args, **kwargs).json())
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/user/miniconda3/envs/test_ollama/lib/python3.12/site-packages/ollama/_client.py", line 124, in _request_raw
    raise ResponseError(e.response.text, e.response.status_code) from None
ollama._types.ResponseError: unexpected error format in response (status code: 500)

I'm not using any tools - just plain chat calls like res = OllamaClient.chat(model=model_name, messages=messages) and some custom scaffolding around it. I even tested it with overriding the default three-pages-long TEMPLATE with my much more simpler version of TEMPLATE, inherited from simpler models like qwen2.5. With that template gpt-oss:20b acts much more stable, but still prone to 500 time to time.

Is it ollama or ollama python client here who tries (and fails) to parse the output from a model?

Start in ollama/_client.py at chat, _request, and _request_raw, which appear in the traceback. Reproduce the plain chat call with gpt-oss:20b using the reported Ollama and Python library versions, then inspect the 500 response body to determine whether the server response or client parsing produces the unexpected error format. Done means the source of the error is identified with a minimal reproduction.