text: Title: [BUG] Cannot use self-signed url in OpenAI Model
  Body: ### Issues Policy acknowledgement
  
  - [X] I have read and agree to submit bug reports in accordance with the [issues policy](https://www.github.com/mlflow/mlflow/blob/master/ISSUE_POLICY.md)
  
  ### Where did you encounter this bug?
  
  Databricks
  
  ### MLflow version
  
  - Client: 2.19.0
  - Openai 1.40.2
  
  ### System information
  
  - Databrics Runtime 16.0 ML (includes Apache Spark 3.5.0, Scala 2.12)
  
  
  ### Describe the problem
  
  OpenAI deployment cannot access urls signed by private CA.
  
  The instance of `AzureOpenAI`, as seen bellow, do not allow configuration of custom certificates for http client:
  
  https://github.com/mlflow/mlflow/blob/3c86c188dbd76c614373f96cb3c03871458aba9c/mlflow/openai/__init__.py#L674-L683
  
  The suggested method, [provided by OpenAI](https://github.com/openai/openai-python?tab=readme-ov-file#configuring-the-http-client), is this configuration:
  
  ```python
  import httpx
  from openai import OpenAI, DefaultHttpxClient
  
  client = OpenAI(
      # Or use the `OPENAI_BASE_URL` env var
      base_url="http://my.test.server.example.com:8083/v1",
      http_client=DefaultHttpxClient(
          proxy="http://my.test.proxy.example.com",
          transport=httpx.HTTPTransport(local_address="0.0.0.0"),
      ),
  )
  ```
  
  My suggestion is to add a new configuration, `OPENAI_SSL_VERIFY`. The implementation should be based on this:
  
  ```python
  from openai import AzureOpenAI, DefaultHttpxClient
  
  # Note DefaultHttpxClient is a just a proxy to httpx.Client
  http_client = DefaultHttpxClient(verify=self.api_config.ssl_verify)
    
  return AzureOpenAI( 
       api_key=self.api_token.token, 
       azure_endpoint=self.api_config.api_base, 
       api_version=self.api_config.api_version, 
       azure_deployment=self.api_config.deployment_id, 
       max_retries=max_retries, 
       timeout=timeout, 
       http_client=http_client 
  )
  ```
  
  ### Tracking information
  
  ```
  System information: Linux #84~20.04.1-Ubuntu SMP Mon Nov 4 18:58:41 UTC 2024
  Python version: 3.12.3
  MLflow version: 2.19.0
  MLflow module location: /local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.12/site-packages/mlflow/__init__.py
  Tracking URI: databricks
  Registry URI: databricks
  Databricks runtime version: 16.0
  MLflow environment variables: 
    MLFLOW_CONDA_HOME: /databricks/conda
    MLFLOW_DEPLOYMENTS_TARGET: databricks
    MLFLOW_GATEWAY_URI: databricks
    MLFLOW_PYTHON_EXECUTABLE: /databricks/spark/scripts/mlflow_python.sh
    MLFLOW_TRACKING_URI: databricks
  MLflow dependencies: 
    Flask: 2.2.5
    Jinja2: 3.1.4
    aiohttp: 3.9.5
    alembic: 1.14.0
    azure-storage-file-datalake: 12.17.0
    boto3: 1.34.69
    botocore: 1.34.69
    docker: 7.1.0
    google-cloud-storage: 2.10.0
    graphene: 3.4.3
    gunicorn: 20.1.0
    langchain: 0.2.12
    markdown: 3.4.1
    matplotlib: 3.8.4
    mlflow-skinny: 2.19.0
    numpy: 1.26.4
    pandas: 1.5.3
    pyarrow: 15.0.2
    pydantic: 2.8.2
    scikit-learn: 1.4.2
    scipy: 1.13.1
    sqlalchemy: 2.0.30
    tiktoken: 0.7.0
    virtualenv: 20.26.2
  ```
  
  ### Code to reproduce issue
  
  <!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
  ```python
  import os
  import openai
  import mlflow
  
  os.environ["AZURE_OPENAI_API_KEY"] = "xxxxxxx" # Any value
  os.environ["AZURE_OPENAI_ENDPOINT"] = "https://self-signed.badssl.com/"  # Any self-signed url, like this one
  os.environ["OPENAI_API_VERSION"] = "2024-06-01"
  os.environ["OPENAI_API_TYPE"] = "azure"
  os.environ["OPENAI_DEPLOYMENT_NAME"] = "text-embedding-3-small"
  
  print(mlflow.__version__, openai.__version__) # Yields ('2.19.0', '1.40.2')
  
  with mlflow.start_run():
      model_info = mlflow.openai.log_model(
          model="text-embedding-3-small",
          task=openai.embeddings,
          artifact_path="model"
      )
  
  # Fix error when model has no openai key... but this is another bug
  os.environ["OPENAI_API_KEY"] = os.environ['AZURE_OPENAI_API_KEY']
  
  # Load the model in pyfunc format
  model = mlflow.pyfunc.load_model(model_info.model_uri)
  
  
  # This will rise an Request #0 failed with: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate (_ssl.c:1000)
  results = model.predict([
      "This is a test"
  ])
  
  # We can download self-signed certificate... but how to use it?
  # echo "" | openssl s_client -connect self-signed.badssl.com:443 -prexit 2>/dev/null | sed -n -e '/BEGIN\ CERTIFICATE/,/END\ CERTIFICATE/ p'
  
  ```
  
  
  ### Stack trace
  
  <!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
  ```
  REPLACE_ME
  ```
  
  
  ### Other info / logs
  
  <!-- PLEASE KEEP BACKTICKS AND CHECK PREVIEW -->
  ```
  APIConnectionError('Connection error.')Traceback (most recent call last):
    File "/databricks/python/lib/python3.12/site-packages/httpx/_transports/default.py", line 72, in map_httpcore_exceptions
      yield
    File "/databricks/python/lib/python3.12/site-packages/httpx/_transports/default.py", line 236, in handle_request
      resp = self._pool.handle_request(req)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_sync/connection_pool.py", line 216, in handle_request
      raise exc from None
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_sync/connection_pool.py", line 196, in handle_request
      response = connection.handle_request(
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_sync/connection.py", line 99, in handle_request
      raise exc
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_sync/connection.py", line 76, in handle_request
      stream = self._connect(request)
               ^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_sync/connection.py", line 154, in _connect
      stream = stream.start_tls(**kwargs)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_backends/sync.py", line 152, in start_tls
      with map_exceptions(exc_map):
    File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
      self.gen.throw(value)
    File "/databricks/python/lib/python3.12/site-packages/httpcore/_exceptions.py", line 14, in map_exceptions
      raise to_exc(exc) from exc
  httpcore.ConnectError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate (_ssl.c:1000)
  
  The above exception was the direct cause of the following exception:
  
  Traceback (most recent call last):
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 972, in _request
      response = self._client.send(
                 ^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpx/_client.py", line 926, in send
      response = self._send_handling_auth(
                 ^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpx/_client.py", line 954, in _send_handling_auth
      response = self._send_handling_redirects(
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpx/_client.py", line 991, in _send_handling_redirects
      response = self._send_single_request(request)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpx/_client.py", line 1027, in _send_single_request
      response = transport.handle_request(request)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/httpx/_transports/default.py", line 235, in handle_request
      with map_httpcore_exceptions():
    File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
      self.gen.throw(value)
    File "/databricks/python/lib/python3.12/site-packages/httpx/_transports/default.py", line 89, in map_httpcore_exceptions
      raise mapped_exc(message) from exc
  httpx.ConnectError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate (_ssl.c:1000)
  
  The above exception was the direct cause of the following exception:
  
  Traceback (most recent call last):
    File "/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.12/site-packages/mlflow/openai/_openai_autolog.py", line 181, in patched_call
      raw_result = original(self, *args, **kwargs)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.12/site-packages/mlflow/utils/autologging_utils/safety.py", line 573, in call_original
      return call_original_fn_with_event_logging(_original_fn, og_args, og_kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.12/site-packages/mlflow/utils/autologging_utils/safety.py", line 508, in call_original_fn_with_event_logging
      original_fn_result = original_fn(*og_args, **og_kwargs)
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/local_disk0/.ephemeral_nfs/cluster_libraries/python/lib/python3.12/site-packages/mlflow/utils/autologging_utils/safety.py", line 570, in _original_fn
      original_result = original(*_og_args, **_og_kwargs)
                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/resources/embeddings.py", line 114, in create
      return self._post(
             ^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1259, in post
      return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 936, in request
      return self._request(
             ^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 996, in _request
      return self._retry_request(
             ^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1074, in _retry_request
      return self._request(
             ^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 996, in _request
      return self._retry_request(
             ^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1074, in _retry_request
      return self._request(
             ^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 996, in _request
      return self._retry_request(
             ^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1074, in _retry_request
      return self._request(
             ^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 996, in _request
      return self._retry_request(
             ^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1074, in _retry_request
      return self._request(
             ^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 996, in _request
      return self._retry_request(
             ^^^^^^^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1074, in _retry_request
      return self._request(
             ^^^^^^^^^^^^^^
    File "/databricks/python/lib/python3.12/site-packages/openai/_base_client.py", line 1006, in _request
      raise APIConnectionError(request=request) from err
  openai.APIConnectionError: Connection error.
  ```
  
  
  ### What component(s) does this bug affect?
  
  - [ ] `area/artifacts`: Artifact stores and artifact logging
  - [ ] `area/build`: Build and test infrastructure for MLflow
  - [X] `area/deployments`: MLflow Deployments client APIs, server, and third-party Deployments integrations
  - [ ] `area/docs`: MLflow documentation pages
  - [ ] `area/examples`: Example code
  - [X] `area/model-registry`: Model Registry service, APIs, and the fluent client calls for Model Registry
  - [X] `area/models`: MLmodel format, model serialization/deserialization, flavors
  - [ ] `area/recipes`: Recipes, Recipe APIs, Recipe configs, Recipe Templates
  - [ ] `area/projects`: MLproject format, project running backends
  - [ ] `area/scoring`: MLflow Model server, model deployment tools, Spark UDFs
  - [ ] `area/server-infra`: MLflow Tracking server backend
  - [ ] `area/tracking`: Tracking Service, tracking client APIs, autologging
  
  ### What interface(s) does this bug affect?
  
  - [ ] `area/uiux`: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  - [ ] `area/docker`: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
  - [ ] `area/sqlalchemy`: Use of SQLAlchemy in the Tracking Service or Model Registry
  - [ ] `area/windows`: Windows support
  
  ### What language(s) does this bug affect?
  
  - [ ] `language/r`: R APIs and clients
  - [ ] `language/java`: Java APIs and clients
  - [ ] `language/new`: Proposals for new client languages
  
  ### What integration(s) does this bug affect?
  
  - [X] `integrations/azure`: Azure and Azure ML integrations
  - [ ] `integrations/sagemaker`: SageMaker integrations
  - [ ] `integrations/databricks`: Databricks integrations