prompt: We are currently solving the following issue within our repository. Here is the issue text:
  --- BEGIN ISSUE ---
  Add consistency check for model data object in the CI tests
  We should take a snapshot of a "correct" model data object (as returned by `get_model_data()`) for the CI testing dataset and always compare the json-parsed outputs of `get_model_data` with it.
  
  Might be a bit tedious to alter every time when we run `get_model_data` ,but otherwise there are certain situation where we can get silent failures. Since certain parts of the Model Analyzer have more general exception catching built in (since certain data simply can't be produced in various situations) and `get_model_data` itself is made to work with incomplete data in order to return this data during training.
  
  If we want to be really scrupulous we should check the model data object at each phase of training, but I think that'd be overdoing it.
  
  --- END ISSUE ---
  
  Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
  --- BEGIN FILES ---
  Path: `mindsdb/__about__.py`
  Content:
  ```
  1 __title__ = 'MindsDB'
  2 __package_name__ = 'mindsdb'
  3 __version__ = '1.7.11'
  4 __description__ = "MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects."
  5 __email__ = "jorge@mindsdb.com"
  6 __author__ = 'MindsDB Inc'
  7 __github__ = 'https://github.com/mindsdb/mindsdb'
  8 __pypi__ = 'https://pypi.org/project/mindsdb'
  9 __license__ = 'MIT'
  10 __copyright__ = 'Copyright 2018- mindsdb'
  11
  ```
  --- END FILES ---
  
  Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.
  
  Here is an example:
  
  ```diff
  diff --git a/examples/server_async.py b/examples/server_async.py
  --- a/examples/server_async.py
  +++ b/examples/server_async.py
  @@ -313,4 +313,4 @@
   
   
   if __name__ == "__main__":
  -    asyncio.run(run_async_server("."), debug=True)
  +    asyncio.run(run_async_server(), debug=True)
  diff --git a/examples/server_sync.py b/examples/server_sync.py
  --- a/examples/server_sync.py
  +++ b/examples/server_sync.py
  @@ -313,5 +313,5 @@
   
   
   if __name__ == "__main__":
  -    server = run_sync_server(".")
  +    server = run_sync_server()
       server.shutdown()
  
  ```
  
golden_diff: diff --git a/mindsdb/__about__.py b/mindsdb/__about__.py
  --- a/mindsdb/__about__.py
  +++ b/mindsdb/__about__.py
  @@ -1,6 +1,6 @@
   __title__ = 'MindsDB'
   __package_name__ = 'mindsdb'
  -__version__ = '1.7.11'
  +__version__ = '1.7.12'
   __description__ = "MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects."
   __email__ = "jorge@mindsdb.com"
   __author__ = 'MindsDB Inc'
  
verification_info: {"golden_diff": "diff --git a/mindsdb/__about__.py b/mindsdb/__about__.py\n--- a/mindsdb/__about__.py\n+++ b/mindsdb/__about__.py\n@@ -1,6 +1,6 @@\n __title__ = 'MindsDB'\n __package_name__ = 'mindsdb'\n-__version__ = '1.7.11'\n+__version__ = '1.7.12'\n __description__ = \"MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.\"\n __email__ = \"jorge@mindsdb.com\"\n __author__ = 'MindsDB Inc'\n", "issue": "Add consistency check for model data object in the CI tests\nWe should take a snapshot of a \"correct\" model data object (as returned by `get_model_data()`) for the CI testing dataset and always compare the json-parsed outputs of `get_model_data` with it.\r\n\r\nMight be a bit tedious to alter every time when we run `get_model_data` ,but otherwise there are certain situation where we can get silent failures. Since certain parts of the Model Analyzer have more general exception catching built in (since certain data simply can't be produced in various situations) and `get_model_data` itself is made to work with incomplete data in order to return this data during training.\r\n\r\nIf we want to be really scrupulous we should check the model data object at each phase of training, but I think that'd be overdoing it.\n", "before_files": [{"content": "__title__ = 'MindsDB'\n__package_name__ = 'mindsdb'\n__version__ = '1.7.11'\n__description__ = \"MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.\"\n__email__ = \"jorge@mindsdb.com\"\n__author__ = 'MindsDB Inc'\n__github__ = 'https://github.com/mindsdb/mindsdb'\n__pypi__ = 'https://pypi.org/project/mindsdb'\n__license__ = 'MIT'\n__copyright__ = 'Copyright 2018- mindsdb'\n", "path": "mindsdb/__about__.py"}], "after_files": [{"content": "__title__ = 'MindsDB'\n__package_name__ = 'mindsdb'\n__version__ = '1.7.12'\n__description__ = \"MindsDB's goal is to make it very simple for developers to use the power of artificial neural networks in their projects.\"\n__email__ = \"jorge@mindsdb.com\"\n__author__ = 'MindsDB Inc'\n__github__ = 'https://github.com/mindsdb/mindsdb'\n__pypi__ = 'https://pypi.org/project/mindsdb'\n__license__ = 'MIT'\n__copyright__ = 'Copyright 2018- mindsdb'\n", "path": "mindsdb/__about__.py"}]}