chore(api/tests): apply ruff reformat #7590 (#7591)

Co-authored-by: -LAN- <laipz8200@outlook.com>

api/tests/integration_tests/model_runtime/xinference/test_llm.py

@@ -20,92 +20,84 @@ from tests.integration_tests.model_runtime.__mock.openai import setup_openai_moc
 from tests.integration_tests.model_runtime.__mock.xinference import setup_xinference_mock
 
 
-@pytest.mark.parametrize('setup_openai_mock, setup_xinference_mock', [['chat', 'none']], indirect=True)
+@pytest.mark.parametrize("setup_openai_mock, setup_xinference_mock", [["chat", "none"]], indirect=True)
 def test_validate_credentials_for_chat_model(setup_openai_mock, setup_xinference_mock):
     model = XinferenceAILargeLanguageModel()
 
     with pytest.raises(CredentialsValidateFailedError):
         model.validate_credentials(
-            model='ChatGLM3',
+            model="ChatGLM3",
             credentials={
-                'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-                'model_uid': 'www ' + os.environ.get('XINFERENCE_CHAT_MODEL_UID')
-            }
+                "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+                "model_uid": "www " + os.environ.get("XINFERENCE_CHAT_MODEL_UID"),
+            },
         )
 
     with pytest.raises(CredentialsValidateFailedError):
-        model.validate_credentials(
-            model='aaaaa',
-            credentials={
-                'server_url': '',
-                'model_uid': ''
-            }
-        )
+        model.validate_credentials(model="aaaaa", credentials={"server_url": "", "model_uid": ""})
 
     model.validate_credentials(
-        model='ChatGLM3',
+        model="ChatGLM3",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_CHAT_MODEL_UID')
-        }
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_CHAT_MODEL_UID"),
+        },
     )
 
-@pytest.mark.parametrize('setup_openai_mock, setup_xinference_mock', [['chat', 'none']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock, setup_xinference_mock", [["chat", "none"]], indirect=True)
 def test_invoke_chat_model(setup_openai_mock, setup_xinference_mock):
     model = XinferenceAILargeLanguageModel()
 
     response = model.invoke(
-        model='ChatGLM3',
+        model="ChatGLM3",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_CHAT_MODEL_UID')
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_CHAT_MODEL_UID"),
         },
         prompt_messages=[
             SystemPromptMessage(
-                content='You are a helpful AI assistant.',
+                content="You are a helpful AI assistant.",
             ),
-            UserPromptMessage(
-                content='Hello World!'
-            )
+            UserPromptMessage(content="Hello World!"),
         ],
         model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
+            "temperature": 0.7,
+            "top_p": 1.0,
         },
-        stop=['you'],
+        stop=["you"],
         user="abc-123",
-        stream=False
+        stream=False,
     )
 
     assert isinstance(response, LLMResult)
     assert len(response.message.content) > 0
     assert response.usage.total_tokens > 0
 
-@pytest.mark.parametrize('setup_openai_mock, setup_xinference_mock', [['chat', 'none']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock, setup_xinference_mock", [["chat", "none"]], indirect=True)
 def test_invoke_stream_chat_model(setup_openai_mock, setup_xinference_mock):
     model = XinferenceAILargeLanguageModel()
 
     response = model.invoke(
-        model='ChatGLM3',
+        model="ChatGLM3",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_CHAT_MODEL_UID')
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_CHAT_MODEL_UID"),
         },
         prompt_messages=[
             SystemPromptMessage(
-                content='You are a helpful AI assistant.',
+                content="You are a helpful AI assistant.",
             ),
-            UserPromptMessage(
-                content='Hello World!'
-            )
+            UserPromptMessage(content="Hello World!"),
         ],
         model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
+            "temperature": 0.7,
+            "top_p": 1.0,
         },
-        stop=['you'],
+        stop=["you"],
         stream=True,
-        user="abc-123"
+        user="abc-123",
     )
 
     assert isinstance(response, Generator)
@@ -114,6 +106,8 @@ def test_invoke_stream_chat_model(setup_openai_mock, setup_xinference_mock):
         assert isinstance(chunk.delta, LLMResultChunkDelta)
         assert isinstance(chunk.delta.message, AssistantPromptMessage)
         assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
+
+
 """
     Funtion calling of xinference does not support stream mode currently
 """
@@ -168,7 +162,7 @@ def test_invoke_stream_chat_model(setup_openai_mock, setup_xinference_mock):
 #     )
 
 #     assert isinstance(response, Generator)
-    
+
 #     call: LLMResultChunk = None
 #     chunks = []
 
@@ -241,86 +235,75 @@ def test_invoke_stream_chat_model(setup_openai_mock, setup_xinference_mock):
 #     assert response.usage.total_tokens > 0
 #     assert response.message.tool_calls[0].function.name == 'get_current_weather'
 
-@pytest.mark.parametrize('setup_openai_mock, setup_xinference_mock', [['completion', 'none']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock, setup_xinference_mock", [["completion", "none"]], indirect=True)
 def test_validate_credentials_for_generation_model(setup_openai_mock, setup_xinference_mock):
     model = XinferenceAILargeLanguageModel()
 
     with pytest.raises(CredentialsValidateFailedError):
         model.validate_credentials(
-            model='alapaca',
+            model="alapaca",
             credentials={
-                'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-                'model_uid': 'www ' + os.environ.get('XINFERENCE_GENERATION_MODEL_UID')
-            }
+                "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+                "model_uid": "www " + os.environ.get("XINFERENCE_GENERATION_MODEL_UID"),
+            },
         )
 
     with pytest.raises(CredentialsValidateFailedError):
-        model.validate_credentials(
-            model='alapaca',
-            credentials={
-                'server_url': '',
-                'model_uid': ''
-            }
-        )
+        model.validate_credentials(model="alapaca", credentials={"server_url": "", "model_uid": ""})
 
     model.validate_credentials(
-        model='alapaca',
+        model="alapaca",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_GENERATION_MODEL_UID')
-        }
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"),
+        },
     )
 
-@pytest.mark.parametrize('setup_openai_mock, setup_xinference_mock', [['completion', 'none']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock, setup_xinference_mock", [["completion", "none"]], indirect=True)
 def test_invoke_generation_model(setup_openai_mock, setup_xinference_mock):
     model = XinferenceAILargeLanguageModel()
 
     response = model.invoke(
-        model='alapaca',
+        model="alapaca",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_GENERATION_MODEL_UID')
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"),
         },
-        prompt_messages=[
-            UserPromptMessage(
-                content='the United States is'
-            )
-        ],
+        prompt_messages=[UserPromptMessage(content="the United States is")],
         model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
+            "temperature": 0.7,
+            "top_p": 1.0,
         },
-        stop=['you'],
+        stop=["you"],
         user="abc-123",
-        stream=False
+        stream=False,
     )
 
     assert isinstance(response, LLMResult)
     assert len(response.message.content) > 0
     assert response.usage.total_tokens > 0
 
-@pytest.mark.parametrize('setup_openai_mock, setup_xinference_mock', [['completion', 'none']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock, setup_xinference_mock", [["completion", "none"]], indirect=True)
 def test_invoke_stream_generation_model(setup_openai_mock, setup_xinference_mock):
     model = XinferenceAILargeLanguageModel()
 
     response = model.invoke(
-        model='alapaca',
+        model="alapaca",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_GENERATION_MODEL_UID')
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"),
         },
-        prompt_messages=[
-            UserPromptMessage(
-                content='the United States is'
-            )
-        ],
+        prompt_messages=[UserPromptMessage(content="the United States is")],
         model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
+            "temperature": 0.7,
+            "top_p": 1.0,
         },
-        stop=['you'],
+        stop=["you"],
         stream=True,
-        user="abc-123"
+        user="abc-123",
     )
 
     assert isinstance(response, Generator)
@@ -330,68 +313,54 @@ def test_invoke_stream_generation_model(setup_openai_mock, setup_xinference_mock
         assert isinstance(chunk.delta.message, AssistantPromptMessage)
         assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
 
+
 def test_get_num_tokens():
     model = XinferenceAILargeLanguageModel()
 
     num_tokens = model.get_num_tokens(
-        model='ChatGLM3',
+        model="ChatGLM3",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_GENERATION_MODEL_UID')
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"),
         },
         prompt_messages=[
             SystemPromptMessage(
-                content='You are a helpful AI assistant.',
+                content="You are a helpful AI assistant.",
             ),
-            UserPromptMessage(
-                content='Hello World!'
-            )
+            UserPromptMessage(content="Hello World!"),
         ],
         tools=[
             PromptMessageTool(
-                name='get_current_weather',
-                description='Get the current weather in a given location',
+                name="get_current_weather",
+                description="Get the current weather in a given location",
                 parameters={
                     "type": "object",
                     "properties": {
-                        "location": {
-                        "type": "string",
-                            "description": "The city and state e.g. San Francisco, CA"
-                        },
-                        "unit": {
-                            "type": "string",
-                            "enum": [
-                                "c",
-                                "f"
-                            ]
-                        }
+                        "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
+                        "unit": {"type": "string", "enum": ["c", "f"]},
                     },
-                    "required": [
-                        "location"
-                    ]
-                }
+                    "required": ["location"],
+                },
             )
-        ]
+        ],
     )
 
     assert isinstance(num_tokens, int)
     assert num_tokens == 77
 
     num_tokens = model.get_num_tokens(
-        model='ChatGLM3',
+        model="ChatGLM3",
         credentials={
-            'server_url': os.environ.get('XINFERENCE_SERVER_URL'),
-            'model_uid': os.environ.get('XINFERENCE_GENERATION_MODEL_UID')
+            "server_url": os.environ.get("XINFERENCE_SERVER_URL"),
+            "model_uid": os.environ.get("XINFERENCE_GENERATION_MODEL_UID"),
         },
         prompt_messages=[
             SystemPromptMessage(
-                content='You are a helpful AI assistant.',
+                content="You are a helpful AI assistant.",
             ),
-            UserPromptMessage(
-                content='Hello World!'
-            )
+            UserPromptMessage(content="Hello World!"),
         ],
     )
 
     assert isinstance(num_tokens, int)
-    assert num_tokens == 21
+    assert num_tokens == 21