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

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

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

@@ -23,79 +23,64 @@ def test_predefined_models():
     assert len(model_schemas) >= 1
     assert isinstance(model_schemas[0], AIModelEntity)
 
-@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_validate_credentials_for_chat_model(setup_openai_mock):
     model = ChatGLMLargeLanguageModel()
 
     with pytest.raises(CredentialsValidateFailedError):
-        model.validate_credentials(
-            model='chatglm2-6b',
-            credentials={
-                'api_base': 'invalid_key'
-            }
-        )
+        model.validate_credentials(model="chatglm2-6b", credentials={"api_base": "invalid_key"})
 
-    model.validate_credentials(
-        model='chatglm2-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        }
-    )
+    model.validate_credentials(model="chatglm2-6b", credentials={"api_base": os.environ.get("CHATGLM_API_BASE")})
 
-@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_invoke_model(setup_openai_mock):
     model = ChatGLMLargeLanguageModel()
 
     response = model.invoke(
-        model='chatglm2-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        },
+        model="chatglm2-6b",
+        credentials={"api_base": os.environ.get("CHATGLM_API_BASE")},
         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', [['chat']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_invoke_stream_model(setup_openai_mock):
     model = ChatGLMLargeLanguageModel()
 
     response = model.invoke(
-        model='chatglm2-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        },
+        model="chatglm2-6b",
+        credentials={"api_base": os.environ.get("CHATGLM_API_BASE")},
         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)
@@ -105,56 +90,45 @@ def test_invoke_stream_model(setup_openai_mock):
         assert isinstance(chunk.delta.message, AssistantPromptMessage)
         assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
 
-@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_invoke_stream_model_with_functions(setup_openai_mock):
     model = ChatGLMLargeLanguageModel()
 
     response = model.invoke(
-        model='chatglm3-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        },
+        model="chatglm3-6b",
+        credentials={"api_base": os.environ.get("CHATGLM_API_BASE")},
         prompt_messages=[
             SystemPromptMessage(
-                content='你是一个天气机器人，你不知道今天的天气怎么样，你需要通过调用一个函数来获取天气信息。'
+                content="你是一个天气机器人，你不知道今天的天气怎么样，你需要通过调用一个函数来获取天气信息。"
             ),
-            UserPromptMessage(
-                content='波士顿天气如何？'
-            )
+            UserPromptMessage(content="波士顿天气如何？"),
         ],
         model_parameters={
-            'temperature': 0,
-            'top_p': 1.0,
+            "temperature": 0,
+            "top_p": 1.0,
         },
-        stop=['you'],
-        user='abc-123',
+        stop=["you"],
+        user="abc-123",
         stream=True,
         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": ["celsius", "fahrenheit"]
-                        }
+                        "location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
+                        "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
                     },
-                    "required": [
-                        "location"
-                    ]
-                }
+                    "required": ["location"],
+                },
             )
-        ]
+        ],
     )
 
     assert isinstance(response, Generator)
-    
+
     call: LLMResultChunk = None
     chunks = []
 
@@ -170,122 +144,87 @@ def test_invoke_stream_model_with_functions(setup_openai_mock):
             break
 
     assert call is not None
-    assert call.delta.message.tool_calls[0].function.name == 'get_current_weather'
+    assert call.delta.message.tool_calls[0].function.name == "get_current_weather"
 
-@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
+
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_invoke_model_with_functions(setup_openai_mock):
     model = ChatGLMLargeLanguageModel()
 
     response = model.invoke(
-        model='chatglm3-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        },
-        prompt_messages=[
-            UserPromptMessage(
-                content='What is the weather like in San Francisco?'
-            )
-        ],
+        model="chatglm3-6b",
+        credentials={"api_base": os.environ.get("CHATGLM_API_BASE")},
+        prompt_messages=[UserPromptMessage(content="What is the weather like in San Francisco?")],
         model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
+            "temperature": 0.7,
+            "top_p": 1.0,
         },
-        stop=['you'],
-        user='abc-123',
+        stop=["you"],
+        user="abc-123",
         stream=False,
         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(response, LLMResult)
     assert len(response.message.content) > 0
     assert response.usage.total_tokens > 0
-    assert response.message.tool_calls[0].function.name == 'get_current_weather'
+    assert response.message.tool_calls[0].function.name == "get_current_weather"
 
 
 def test_get_num_tokens():
     model = ChatGLMLargeLanguageModel()
 
     num_tokens = model.get_num_tokens(
-        model='chatglm2-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        },
+        model="chatglm2-6b",
+        credentials={"api_base": os.environ.get("CHATGLM_API_BASE")},
         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='chatglm2-6b',
-        credentials={
-            'api_base': os.environ.get('CHATGLM_API_BASE')
-        },
+        model="chatglm2-6b",
+        credentials={"api_base": os.environ.get("CHATGLM_API_BASE")},
         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