[BUG] Exception During Model Logging with Custom Ollama Class about mlflow HOT 6 OPEN

ValidationError: 1 validation error for Ollama
options
  extra fields not permitted (type=value_error.extra)
File <command-3710765546539638>, line 2
      1 # Load model as a PyFuncModel.
----> 2 loaded_model = mlflow.langchain.load_model(logged_model.model_uri)
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-6fdefbd4-710b-40a8-8764-423b3dffa1a0/lib/python3.10/site-packages/mlflow/langchain/__init__.py:934, in load_model(model_uri, dst_path)
    912 """
    913 Load a LangChain model from a local file or a run.
    914 
   (...)
    931     A LangChain model instance.
    932 """
    933 local_model_path = _download_artifact_from_uri(artifact_uri=model_uri, output_path=dst_path)
--> 934 return _load_model_from_local_fs(local_model_path)
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-6fdefbd4-710b-40a8-8764-423b3dffa1a0/lib/python3.10/site-packages/mlflow/langchain/__init__.py:907, in _load_model_from_local_fs(local_model_path)
    905 _add_code_from_conf_to_system_path(local_model_path, flavor_conf)
    906 with patch_langchain_type_to_cls_dict():
--> 907     return _load_model(local_model_path, flavor_conf)
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-6fdefbd4-710b-40a8-8764-423b3dffa1a0/lib/python3.10/site-packages/mlflow/langchain/__init__.py:616, in _load_model(local_model_path, flavor_conf)
    614     model = _load_runnables(local_model_path, flavor_conf)
    615 elif model_load_fn == _BASE_LOAD_KEY:
--> 616     model = _load_base_lcs(local_model_path, flavor_conf)
    617 else:
    618     raise mlflow.MlflowException(
    619         "Failed to load LangChain model. Unknown model type: "
    620         f"{flavor_conf.get(_MODEL_TYPE_KEY)}"
    621     )
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-6fdefbd4-710b-40a8-8764-423b3dffa1a0/lib/python3.10/site-packages/mlflow/langchain/utils.py:580, in _load_base_lcs(local_model_path, conf)
    578         model = _patch_loader(load_chain)(lc_model_path, **kwargs)
    579 elif agent_path is None and tools_path is None:
--> 580     model = _patch_loader(load_chain)(lc_model_path)
    581 else:
    582     from langchain.agents import initialize_agent
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-6fdefbd4-710b-40a8-8764-423b3dffa1a0/lib/python3.10/site-packages/mlflow/langchain/utils.py:525, in _patch_loader.<locals>.patched_loader(*args, **kwargs)
    524 def patched_loader(*args, **kwargs):
--> 525     return loader_func(*args, **kwargs, allow_dangerous_deserialization=True)
File /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.10/site-packages/langchain/chains/loading.py:631, in load_chain(path, **kwargs)
    625 if isinstance(path, str) and path.startswith("lc://"):
    626     raise RuntimeError(
    627         "Loading from the deprecated github-based Hub is no longer supported. "
    628         "Please use the new LangChain Hub at https://smith.langchain.com/hub "
    629         "instead."
    630     )
--> 631 return _load_chain_from_file(path, **kwargs)
File /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.10/site-packages/langchain/chains/loading.py:658, in _load_chain_from_file(file, **kwargs)
    655     config["memory"] = kwargs.pop("memory")
    657 # Load the chain from the config now.
--> 658 return load_chain_from_config(config, **kwargs)
File /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.10/site-packages/langchain/chains/loading.py:620, in load_chain_from_config(config, **kwargs)
    617     raise ValueError(f"Loading {config_type} chain not supported")
    619 chain_loader = type_to_loader_dict[config_type]
--> 620 return chain_loader(config, **kwargs)
File /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.10/site-packages/langchain/chains/loading.py:40, in _load_llm_chain(config, **kwargs)
     38 if "llm" in config:
     39     llm_config = config.pop("llm")
---> 40     llm = load_llm_from_config(llm_config, **kwargs)
     41 elif "llm_path" in config:
     42     llm = load_llm(config.pop("llm_path"), **kwargs)
File /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.10/site-packages/langchain_community/llms/loading.py:33, in load_llm_from_config(config, **kwargs)
     28 if _ALLOW_DANGEROUS_DESERIALIZATION_ARG in llm_cls.__fields__:
     29     load_kwargs[_ALLOW_DANGEROUS_DESERIALIZATION_ARG] = kwargs.get(
     30         _ALLOW_DANGEROUS_DESERIALIZATION_ARG, False
     31     )
---> 33 return llm_cls(**config, **load_kwargs)
File /local_disk0/.ephemeral_nfs/envs/pythonEnv-6fdefbd4-710b-40a8-8764-423b3dffa1a0/lib/python3.10/site-packages/pydantic/v1/main.py:341, in BaseModel.__init__(__pydantic_self__, **data)
    339 values, fields_set, validation_error = validate_model(__pydantic_self__.__class__, data)
    340 if validation_error:
--> 341     raise validation_error
    342 try:
    343     object_setattr(__pydantic_self__, '__dict__', values)
    

{'_type': 'ollama',
 'format': None,
 'keep_alive': None,
 'model': 'phi3:instruct',
 'options': {'mirostat': None,
  'mirostat_eta': None,
  'mirostat_tau': None,
  'num_ctx': None,
  'num_gpu': None,
  'num_predict': None,
  'num_thread': None,
  'repeat_last_n': None,
  'repeat_penalty': None,
  'stop': None,
  'temperature': 0.0,
  'tfs_z': None,
  'top_k': None,
  'top_p': None},
 'system': None,
 'template': None}

import os
import requests
import json
DATABRICKS_TOKEN=$TOKEN
def create_simplified_json(topic):
    # Simplifying the JSON creation to fit the expected 'dataframe_records' format with 'topic'
    return {'dataframe_records': [{'topic': topic}]}

def score_model(topic):
    url = 'https://<url>/serving-endpoints/LangchainTest1/invocations'
    headers = {'Authorization': f'Bearer {DATABRICKS_TOKEN}',
               'Content-Type': 'application/json'}
    # Generate the payload using the simplified function
    data_json = json.dumps(create_simplified_json(topic))
    
    response = requests.post(url, headers=headers, data=data_json)
    if response.status_code != 200:
        raise Exception(f'Request failed with status {response.status_code}, {response.text}')
    
    return response.json()

# Example usage
try:
    topic = "What is machine learning?"  # Assign the topic here
    result = score_model(topic)
    print("Model response:", result)
except Exception as e:
    print("Error querying the model:", str(e))

Error querying the model: Request failed with status 400, {"error_code": "BAD_REQUEST", "message": "1 tasks failed. Errors: {0: 'error: ConnectionError(MaxRetryError(\"HTTPConnectionPool(host='localhost', port=11434): Max retries exceeded with url: /api/generate (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7fcad9276aa0>: Failed to establish a new connection: [Errno 111] Connection refused'))\"))...