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

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

api/tests/integration_tests/workflow/nodes/test_llm.py

@@ -23,90 +23,71 @@ from tests.integration_tests.model_runtime.__mock.openai import setup_openai_moc
 from tests.integration_tests.workflow.nodes.__mock.code_executor import setup_code_executor_mock
 
 
-@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_execute_llm(setup_openai_mock):
     node = LLMNode(
-        tenant_id='1',
-        app_id='1',
-        workflow_id='1',
-        user_id='1',
+        tenant_id="1",
+        app_id="1",
+        workflow_id="1",
+        user_id="1",
         invoke_from=InvokeFrom.WEB_APP,
         user_from=UserFrom.ACCOUNT,
         config={
-            'id': 'llm',
-            'data': {
-                'title': '123',
-                'type': 'llm',
-                'model': {
-                    'provider': 'openai',
-                    'name': 'gpt-3.5-turbo',
-                    'mode': 'chat',
-                    'completion_params': {}
-                },
-                'prompt_template': [
-                    {
-                        'role': 'system',
-                        'text': 'you are a helpful assistant.\ntoday\'s weather is {{#abc.output#}}.'
-                    },
-                    {
-                        'role': 'user',
-                        'text': '{{#sys.query#}}'
-                    }
+            "id": "llm",
+            "data": {
+                "title": "123",
+                "type": "llm",
+                "model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
+                "prompt_template": [
+                    {"role": "system", "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}."},
+                    {"role": "user", "text": "{{#sys.query#}}"},
                 ],
-                'memory': None,
-                'context': {
-                    'enabled': False
-                },
-                'vision': {
-                    'enabled': False
-                }
-            }
-        }
+                "memory": None,
+                "context": {"enabled": False},
+                "vision": {"enabled": False},
+            },
+        },
     )
 
     # construct variable pool
-    pool = VariablePool(system_variables={
-        SystemVariableKey.QUERY: 'what\'s the weather today?',
-        SystemVariableKey.FILES: [],
-        SystemVariableKey.CONVERSATION_ID: 'abababa',
-        SystemVariableKey.USER_ID: 'aaa'
-    }, user_inputs={}, environment_variables=[])
-    pool.add(['abc', 'output'], 'sunny')
+    pool = VariablePool(
+        system_variables={
+            SystemVariableKey.QUERY: "what's the weather today?",
+            SystemVariableKey.FILES: [],
+            SystemVariableKey.CONVERSATION_ID: "abababa",
+            SystemVariableKey.USER_ID: "aaa",
+        },
+        user_inputs={},
+        environment_variables=[],
+    )
+    pool.add(["abc", "output"], "sunny")
 
-    credentials = {
-        'openai_api_key': os.environ.get('OPENAI_API_KEY')
-    }
+    credentials = {"openai_api_key": os.environ.get("OPENAI_API_KEY")}
 
-    provider_instance = ModelProviderFactory().get_provider_instance('openai')
+    provider_instance = ModelProviderFactory().get_provider_instance("openai")
     model_type_instance = provider_instance.get_model_instance(ModelType.LLM)
     provider_model_bundle = ProviderModelBundle(
         configuration=ProviderConfiguration(
-            tenant_id='1',
+            tenant_id="1",
             provider=provider_instance.get_provider_schema(),
             preferred_provider_type=ProviderType.CUSTOM,
             using_provider_type=ProviderType.CUSTOM,
-            system_configuration=SystemConfiguration(
-                enabled=False
-            ),
-            custom_configuration=CustomConfiguration(
-                provider=CustomProviderConfiguration(
-                    credentials=credentials
-                )
-            ),
-            model_settings=[]
+            system_configuration=SystemConfiguration(enabled=False),
+            custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)),
+            model_settings=[],
         ),
         provider_instance=provider_instance,
-        model_type_instance=model_type_instance
+        model_type_instance=model_type_instance,
     )
-    model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model='gpt-3.5-turbo')
+    model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model="gpt-3.5-turbo")
     model_config = ModelConfigWithCredentialsEntity(
-        model='gpt-3.5-turbo',
-        provider='openai',
-        mode='chat',
+        model="gpt-3.5-turbo",
+        provider="openai",
+        mode="chat",
         credentials=credentials,
         parameters={},
-        model_schema=model_type_instance.get_model_schema('gpt-3.5-turbo'),
-        provider_model_bundle=provider_model_bundle
+        model_schema=model_type_instance.get_model_schema("gpt-3.5-turbo"),
+        provider_model_bundle=provider_model_bundle,
     )
 
     # Mock db.session.close()
@@ -118,112 +99,97 @@ def test_execute_llm(setup_openai_mock):
     result = node.run(pool)
 
     assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
-    assert result.outputs['text'] is not None
-    assert result.outputs['usage']['total_tokens'] > 0
+    assert result.outputs["text"] is not None
+    assert result.outputs["usage"]["total_tokens"] > 0
 
-@pytest.mark.parametrize('setup_code_executor_mock', [['none']], indirect=True)
-@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
+
+@pytest.mark.parametrize("setup_code_executor_mock", [["none"]], indirect=True)
+@pytest.mark.parametrize("setup_openai_mock", [["chat"]], indirect=True)
 def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_openai_mock):
     """
     Test execute LLM node with jinja2
     """
     node = LLMNode(
-        tenant_id='1',
-        app_id='1',
-        workflow_id='1',
-        user_id='1',
+        tenant_id="1",
+        app_id="1",
+        workflow_id="1",
+        user_id="1",
         invoke_from=InvokeFrom.WEB_APP,
         user_from=UserFrom.ACCOUNT,
         config={
-            'id': 'llm',
-            'data': {
-                'title': '123',
-                'type': 'llm',
-                'model': {
-                    'provider': 'openai',
-                    'name': 'gpt-3.5-turbo',
-                    'mode': 'chat',
-                    'completion_params': {}
+            "id": "llm",
+            "data": {
+                "title": "123",
+                "type": "llm",
+                "model": {"provider": "openai", "name": "gpt-3.5-turbo", "mode": "chat", "completion_params": {}},
+                "prompt_config": {
+                    "jinja2_variables": [
+                        {"variable": "sys_query", "value_selector": ["sys", "query"]},
+                        {"variable": "output", "value_selector": ["abc", "output"]},
+                    ]
                 },
-                'prompt_config': {
-                    'jinja2_variables': [{
-                        'variable': 'sys_query',
-                        'value_selector': ['sys', 'query']
-                    }, {
-                        'variable': 'output',
-                        'value_selector': ['abc', 'output']
-                    }]
-                },
-                'prompt_template': [
+                "prompt_template": [
                     {
-                        'role': 'system',
-                        'text': 'you are a helpful assistant.\ntoday\'s weather is {{#abc.output#}}',
-                        'jinja2_text': 'you are a helpful assistant.\ntoday\'s weather is {{output}}.',
-                        'edition_type': 'jinja2'
+                        "role": "system",
+                        "text": "you are a helpful assistant.\ntoday's weather is {{#abc.output#}}",
+                        "jinja2_text": "you are a helpful assistant.\ntoday's weather is {{output}}.",
+                        "edition_type": "jinja2",
                     },
                     {
-                        'role': 'user',
-                        'text': '{{#sys.query#}}',
-                        'jinja2_text': '{{sys_query}}',
-                        'edition_type': 'basic'
-                    }
+                        "role": "user",
+                        "text": "{{#sys.query#}}",
+                        "jinja2_text": "{{sys_query}}",
+                        "edition_type": "basic",
+                    },
                 ],
-                'memory': None,
-                'context': {
-                    'enabled': False
-                },
-                'vision': {
-                    'enabled': False
-                }
-            }
-        }
+                "memory": None,
+                "context": {"enabled": False},
+                "vision": {"enabled": False},
+            },
+        },
     )
 
     # construct variable pool
-    pool = VariablePool(system_variables={
-        SystemVariableKey.QUERY: 'what\'s the weather today?',
-        SystemVariableKey.FILES: [],
-        SystemVariableKey.CONVERSATION_ID: 'abababa',
-        SystemVariableKey.USER_ID: 'aaa'
-    }, user_inputs={}, environment_variables=[])
-    pool.add(['abc', 'output'], 'sunny')
+    pool = VariablePool(
+        system_variables={
+            SystemVariableKey.QUERY: "what's the weather today?",
+            SystemVariableKey.FILES: [],
+            SystemVariableKey.CONVERSATION_ID: "abababa",
+            SystemVariableKey.USER_ID: "aaa",
+        },
+        user_inputs={},
+        environment_variables=[],
+    )
+    pool.add(["abc", "output"], "sunny")
 
-    credentials = {
-        'openai_api_key': os.environ.get('OPENAI_API_KEY')
-    }
+    credentials = {"openai_api_key": os.environ.get("OPENAI_API_KEY")}
 
-    provider_instance = ModelProviderFactory().get_provider_instance('openai')
+    provider_instance = ModelProviderFactory().get_provider_instance("openai")
     model_type_instance = provider_instance.get_model_instance(ModelType.LLM)
     provider_model_bundle = ProviderModelBundle(
         configuration=ProviderConfiguration(
-            tenant_id='1',
+            tenant_id="1",
             provider=provider_instance.get_provider_schema(),
             preferred_provider_type=ProviderType.CUSTOM,
             using_provider_type=ProviderType.CUSTOM,
-            system_configuration=SystemConfiguration(
-                enabled=False
-            ),
-            custom_configuration=CustomConfiguration(
-                provider=CustomProviderConfiguration(
-                    credentials=credentials
-                )
-            ),
-            model_settings=[]
+            system_configuration=SystemConfiguration(enabled=False),
+            custom_configuration=CustomConfiguration(provider=CustomProviderConfiguration(credentials=credentials)),
+            model_settings=[],
         ),
         provider_instance=provider_instance,
         model_type_instance=model_type_instance,
     )
 
-    model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model='gpt-3.5-turbo')
+    model_instance = ModelInstance(provider_model_bundle=provider_model_bundle, model="gpt-3.5-turbo")
 
     model_config = ModelConfigWithCredentialsEntity(
-        model='gpt-3.5-turbo',
-        provider='openai',
-        mode='chat',
+        model="gpt-3.5-turbo",
+        provider="openai",
+        mode="chat",
         credentials=credentials,
         parameters={},
-        model_schema=model_type_instance.get_model_schema('gpt-3.5-turbo'),
-        provider_model_bundle=provider_model_bundle
+        model_schema=model_type_instance.get_model_schema("gpt-3.5-turbo"),
+        provider_model_bundle=provider_model_bundle,
     )
 
     # Mock db.session.close()
@@ -235,5 +201,5 @@ def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_openai_mock):
     result = node.run(pool)
 
     assert result.status == WorkflowNodeExecutionStatus.SUCCEEDED
-    assert 'sunny' in json.dumps(result.process_data)
-    assert 'what\'s the weather today?' in json.dumps(result.process_data)
+    assert "sunny" in json.dumps(result.process_data)
+    assert "what's the weather today?" in json.dumps(result.process_data)