We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Unpin sqlalchemy
Hi,

Currently mlflow pins sqlalchemy to `<= 1.3.13`. I wanted to use this package on a projects that requires a more updated version of sqlalchemy.
Would it be possible to unpit sqlalchemy or to change the constraint to disallow specific version of it? (like `!=1.3.14` etc?)

Thanks

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `setup.py`
Content:
```
1 import os
2 from importlib.machinery import SourceFileLoader
3 from setuptools import setup, find_packages
4 
5 version = (
6     SourceFileLoader("mlflow.version", os.path.join("mlflow", "version.py")).load_module().VERSION
7 )
8 
9 
10 # Get a list of all files in the JS directory to include in our module
11 def package_files(directory):
12     paths = []
13     for (path, _, filenames) in os.walk(directory):
14         for filename in filenames:
15             paths.append(os.path.join("..", path, filename))
16     return paths
17 
18 
19 # Prints out a set of paths (relative to the mlflow/ directory) of files in mlflow/server/js/build
20 # to include in the wheel, e.g. "../mlflow/server/js/build/index.html"
21 js_files = package_files("mlflow/server/js/build")
22 models_container_server_files = package_files("mlflow/models/container")
23 alembic_files = [
24     "../mlflow/store/db_migrations/alembic.ini",
25     "../mlflow/temporary_db_migrations_for_pre_1_users/alembic.ini",
26 ]
27 
28 setup(
29     name="mlflow",
30     version=version,
31     packages=find_packages(exclude=["tests", "tests.*"]),
32     package_data={"mlflow": js_files + models_container_server_files + alembic_files},
33     install_requires=[
34         "alembic<=1.4.1",
35         # Required
36         "azure-storage-blob",
37         "click>=7.0",
38         "cloudpickle",
39         "databricks-cli>=0.8.7",
40         "requests>=2.17.3",
41         "six>=1.10.0",
42         'waitress; platform_system == "Windows"',
43         'gunicorn; platform_system != "Windows"',
44         "Flask",
45         "numpy",
46         "pandas",
47         "python-dateutil",
48         "protobuf>=3.6.0",
49         "gitpython>=2.1.0",
50         "pyyaml",
51         "querystring_parser",
52         "docker>=4.0.0",
53         "entrypoints",
54         # Pin sqlparse for: https://github.com/mlflow/mlflow/issues/3433
55         "sqlparse>=0.3.1",
56         # Required to run the MLflow server against SQL-backed storage
57         "sqlalchemy<=1.3.13",
58         "gorilla",
59         "prometheus-flask-exporter",
60     ],
61     extras_require={
62         "extras": [
63             "scikit-learn",
64             # Required to log artifacts and models to HDFS artifact locations
65             "pyarrow",
66             # Required to log artifacts and models to AWS S3 artifact locations
67             "boto3",
68             "mleap",
69             # Required to log artifacts and models to GCS artifact locations
70             "google-cloud-storage",
71             "azureml-core>=1.2.0",
72             # Required to log artifacts to SFTP artifact locations
73             "pysftp",
74             # Required by the mlflow.projects module, when running projects against
75             # a remote Kubernetes cluster
76             "kubernetes",
77         ],
78         "sqlserver": ["mlflow-dbstore",],
79         "aliyun-oss": ["aliyunstoreplugin",],
80     },
81     entry_points="""
82         [console_scripts]
83         mlflow=mlflow.cli:cli
84     """,
85     zip_safe=False,
86     author="Databricks",
87     description="MLflow: A Platform for ML Development and Productionization",
88     long_description=open("README.rst").read(),
89     license="Apache License 2.0",
90     classifiers=["Intended Audience :: Developers", "Programming Language :: Python :: 3.6",],
91     keywords="ml ai databricks",
92     url="https://mlflow.org/",
93     python_requires=">=3.5",
94     project_urls={
95         "Bug Tracker": "https://github.com/mlflow/mlflow/issues",
96         "Documentation": "https://mlflow.org/docs/latest/index.html",
97         "Source Code": "https://github.com/mlflow/mlflow",
98     },
99 )
100
```
--- 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()

```

diff --git a/setup.py b/setup.py
--- a/setup.py
+++ b/setup.py
@@ -54,7 +54,7 @@
         # Pin sqlparse for: https://github.com/mlflow/mlflow/issues/3433
         "sqlparse>=0.3.1",
         # Required to run the MLflow server against SQL-backed storage
-        "sqlalchemy<=1.3.13",
+        "sqlalchemy",
         "gorilla",
         "prometheus-flask-exporter",
     ],

{"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -54,7 +54,7 @@\n         # Pin sqlparse for: https://github.com/mlflow/mlflow/issues/3433\n         \"sqlparse>=0.3.1\",\n         # Required to run the MLflow server against SQL-backed storage\n-        \"sqlalchemy<=1.3.13\",\n+        \"sqlalchemy\",\n         \"gorilla\",\n         \"prometheus-flask-exporter\",\n     ],\n", "issue": "Unpin sqlalchemy\nHi,\r\n\r\nCurrently mlflow pins sqlalchemy to `<= 1.3.13`. I wanted to use this package on a projects that requires a more updated version of sqlalchemy.\r\nWould it be possible to unpit sqlalchemy or to change the constraint to disallow specific version of it? (like `!=1.3.14` etc?)\r\n\r\nThanks\n", "before_files": [{"content": "import os\nfrom importlib.machinery import SourceFileLoader\nfrom setuptools import setup, find_packages\n\nversion = (\n    SourceFileLoader(\"mlflow.version\", os.path.join(\"mlflow\", \"version.py\")).load_module().VERSION\n)\n\n\n# Get a list of all files in the JS directory to include in our module\ndef package_files(directory):\n    paths = []\n    for (path, _, filenames) in os.walk(directory):\n        for filename in filenames:\n            paths.append(os.path.join(\"..\", path, filename))\n    return paths\n\n\n# Prints out a set of paths (relative to the mlflow/ directory) of files in mlflow/server/js/build\n# to include in the wheel, e.g. \"../mlflow/server/js/build/index.html\"\njs_files = package_files(\"mlflow/server/js/build\")\nmodels_container_server_files = package_files(\"mlflow/models/container\")\nalembic_files = [\n    \"../mlflow/store/db_migrations/alembic.ini\",\n    \"../mlflow/temporary_db_migrations_for_pre_1_users/alembic.ini\",\n]\n\nsetup(\n    name=\"mlflow\",\n    version=version,\n    packages=find_packages(exclude=[\"tests\", \"tests.*\"]),\n    package_data={\"mlflow\": js_files + models_container_server_files + alembic_files},\n    install_requires=[\n        \"alembic<=1.4.1\",\n        # Required\n        \"azure-storage-blob\",\n        \"click>=7.0\",\n        \"cloudpickle\",\n        \"databricks-cli>=0.8.7\",\n        \"requests>=2.17.3\",\n        \"six>=1.10.0\",\n        'waitress; platform_system == \"Windows\"',\n        'gunicorn; platform_system != \"Windows\"',\n        \"Flask\",\n        \"numpy\",\n        \"pandas\",\n        \"python-dateutil\",\n        \"protobuf>=3.6.0\",\n        \"gitpython>=2.1.0\",\n        \"pyyaml\",\n        \"querystring_parser\",\n        \"docker>=4.0.0\",\n        \"entrypoints\",\n        # Pin sqlparse for: https://github.com/mlflow/mlflow/issues/3433\n        \"sqlparse>=0.3.1\",\n        # Required to run the MLflow server against SQL-backed storage\n        \"sqlalchemy<=1.3.13\",\n        \"gorilla\",\n        \"prometheus-flask-exporter\",\n    ],\n    extras_require={\n        \"extras\": [\n            \"scikit-learn\",\n            # Required to log artifacts and models to HDFS artifact locations\n            \"pyarrow\",\n            # Required to log artifacts and models to AWS S3 artifact locations\n            \"boto3\",\n            \"mleap\",\n            # Required to log artifacts and models to GCS artifact locations\n            \"google-cloud-storage\",\n            \"azureml-core>=1.2.0\",\n            # Required to log artifacts to SFTP artifact locations\n            \"pysftp\",\n            # Required by the mlflow.projects module, when running projects against\n            # a remote Kubernetes cluster\n            \"kubernetes\",\n        ],\n        \"sqlserver\": [\"mlflow-dbstore\",],\n        \"aliyun-oss\": [\"aliyunstoreplugin\",],\n    },\n    entry_points=\"\"\"\n        [console_scripts]\n        mlflow=mlflow.cli:cli\n    \"\"\",\n    zip_safe=False,\n    author=\"Databricks\",\n    description=\"MLflow: A Platform for ML Development and Productionization\",\n    long_description=open(\"README.rst\").read(),\n    license=\"Apache License 2.0\",\n    classifiers=[\"Intended Audience :: Developers\", \"Programming Language :: Python :: 3.6\",],\n    keywords=\"ml ai databricks\",\n    url=\"https://mlflow.org/\",\n    python_requires=\">=3.5\",\n    project_urls={\n        \"Bug Tracker\": \"https://github.com/mlflow/mlflow/issues\",\n        \"Documentation\": \"https://mlflow.org/docs/latest/index.html\",\n        \"Source Code\": \"https://github.com/mlflow/mlflow\",\n    },\n)\n", "path": "setup.py"}], "after_files": [{"content": "import os\nfrom importlib.machinery import SourceFileLoader\nfrom setuptools import setup, find_packages\n\nversion = (\n    SourceFileLoader(\"mlflow.version\", os.path.join(\"mlflow\", \"version.py\")).load_module().VERSION\n)\n\n\n# Get a list of all files in the JS directory to include in our module\ndef package_files(directory):\n    paths = []\n    for (path, _, filenames) in os.walk(directory):\n        for filename in filenames:\n            paths.append(os.path.join(\"..\", path, filename))\n    return paths\n\n\n# Prints out a set of paths (relative to the mlflow/ directory) of files in mlflow/server/js/build\n# to include in the wheel, e.g. \"../mlflow/server/js/build/index.html\"\njs_files = package_files(\"mlflow/server/js/build\")\nmodels_container_server_files = package_files(\"mlflow/models/container\")\nalembic_files = [\n    \"../mlflow/store/db_migrations/alembic.ini\",\n    \"../mlflow/temporary_db_migrations_for_pre_1_users/alembic.ini\",\n]\n\nsetup(\n    name=\"mlflow\",\n    version=version,\n    packages=find_packages(exclude=[\"tests\", \"tests.*\"]),\n    package_data={\"mlflow\": js_files + models_container_server_files + alembic_files},\n    install_requires=[\n        \"alembic<=1.4.1\",\n        # Required\n        \"azure-storage-blob\",\n        \"click>=7.0\",\n        \"cloudpickle\",\n        \"databricks-cli>=0.8.7\",\n        \"requests>=2.17.3\",\n        \"six>=1.10.0\",\n        'waitress; platform_system == \"Windows\"',\n        'gunicorn; platform_system != \"Windows\"',\n        \"Flask\",\n        \"numpy\",\n        \"pandas\",\n        \"python-dateutil\",\n        \"protobuf>=3.6.0\",\n        \"gitpython>=2.1.0\",\n        \"pyyaml\",\n        \"querystring_parser\",\n        \"docker>=4.0.0\",\n        \"entrypoints\",\n        # Pin sqlparse for: https://github.com/mlflow/mlflow/issues/3433\n        \"sqlparse>=0.3.1\",\n        # Required to run the MLflow server against SQL-backed storage\n        \"sqlalchemy\",\n        \"gorilla\",\n        \"prometheus-flask-exporter\",\n    ],\n    extras_require={\n        \"extras\": [\n            \"scikit-learn\",\n            # Required to log artifacts and models to HDFS artifact locations\n            \"pyarrow\",\n            # Required to log artifacts and models to AWS S3 artifact locations\n            \"boto3\",\n            \"mleap\",\n            # Required to log artifacts and models to GCS artifact locations\n            \"google-cloud-storage\",\n            \"azureml-core>=1.2.0\",\n            # Required to log artifacts to SFTP artifact locations\n            \"pysftp\",\n            # Required by the mlflow.projects module, when running projects against\n            # a remote Kubernetes cluster\n            \"kubernetes\",\n        ],\n        \"sqlserver\": [\"mlflow-dbstore\",],\n        \"aliyun-oss\": [\"aliyunstoreplugin\",],\n    },\n    entry_points=\"\"\"\n        [console_scripts]\n        mlflow=mlflow.cli:cli\n    \"\"\",\n    zip_safe=False,\n    author=\"Databricks\",\n    description=\"MLflow: A Platform for ML Development and Productionization\",\n    long_description=open(\"README.rst\").read(),\n    license=\"Apache License 2.0\",\n    classifiers=[\"Intended Audience :: Developers\", \"Programming Language :: Python :: 3.6\",],\n    keywords=\"ml ai databricks\",\n    url=\"https://mlflow.org/\",\n    python_requires=\">=3.5\",\n    project_urls={\n        \"Bug Tracker\": \"https://github.com/mlflow/mlflow/issues\",\n        \"Documentation\": \"https://mlflow.org/docs/latest/index.html\",\n        \"Source Code\": \"https://github.com/mlflow/mlflow\",\n    },\n)\n", "path": "setup.py"}]}