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

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

api/tests/integration_tests/model_runtime/localai/test_embedding.py

@@ -1,4 +1,4 @@
 """
-    LocalAI Embedding Interface is temporarily unavailable due to 
-    we could not find a way to test it for now.
-"""
+LocalAI Embedding Interface is temporarily unavailable due to
+we could not find a way to test it for now.
+"""

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

@@ -21,99 +21,78 @@ def test_validate_credentials_for_chat_model():
 
     with pytest.raises(CredentialsValidateFailedError):
         model.validate_credentials(
-            model='chinese-llama-2-7b',
+            model="chinese-llama-2-7b",
             credentials={
-                'server_url': 'hahahaha',
-                'completion_type': 'completion',
-            }
+                "server_url": "hahahaha",
+                "completion_type": "completion",
+            },
         )
 
     model.validate_credentials(
-        model='chinese-llama-2-7b',
+        model="chinese-llama-2-7b",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'completion',
-        }
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "completion",
+        },
     )
 
+
 def test_invoke_completion_model():
     model = LocalAILanguageModel()
 
     response = model.invoke(
-        model='chinese-llama-2-7b',
+        model="chinese-llama-2-7b",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'completion',
-        },
-        prompt_messages=[
-            UserPromptMessage(
-                content='ping'
-            )
-        ],
-        model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
-            'max_tokens': 10
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "completion",
         },
+        prompt_messages=[UserPromptMessage(content="ping")],
+        model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10},
         stop=[],
         user="abc-123",
-        stream=False
+        stream=False,
     )
 
     assert isinstance(response, LLMResult)
     assert len(response.message.content) > 0
     assert response.usage.total_tokens > 0
 
+
 def test_invoke_chat_model():
     model = LocalAILanguageModel()
 
     response = model.invoke(
-        model='chinese-llama-2-7b',
+        model="chinese-llama-2-7b",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'chat_completion',
-        },
-        prompt_messages=[
-            UserPromptMessage(
-                content='ping'
-            )
-        ],
-        model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
-            'max_tokens': 10
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "chat_completion",
         },
+        prompt_messages=[UserPromptMessage(content="ping")],
+        model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10},
         stop=[],
         user="abc-123",
-        stream=False
+        stream=False,
     )
 
     assert isinstance(response, LLMResult)
     assert len(response.message.content) > 0
     assert response.usage.total_tokens > 0
 
+
 def test_invoke_stream_completion_model():
     model = LocalAILanguageModel()
 
     response = model.invoke(
-        model='chinese-llama-2-7b',
+        model="chinese-llama-2-7b",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'completion',
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "completion",
         },
-        prompt_messages=[
-            UserPromptMessage(
-                content='Hello World!'
-            )
-        ],
-        model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
-            'max_tokens': 10
-        },
-        stop=['you'],
+        prompt_messages=[UserPromptMessage(content="Hello World!")],
+        model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10},
+        stop=["you"],
         stream=True,
-        user="abc-123"
+        user="abc-123",
     )
 
     assert isinstance(response, Generator)
@@ -123,28 +102,21 @@ def test_invoke_stream_completion_model():
         assert isinstance(chunk.delta.message, AssistantPromptMessage)
         assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
 
+
 def test_invoke_stream_chat_model():
     model = LocalAILanguageModel()
 
     response = model.invoke(
-        model='chinese-llama-2-7b',
+        model="chinese-llama-2-7b",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'chat_completion',
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "chat_completion",
         },
-        prompt_messages=[
-            UserPromptMessage(
-                content='Hello World!'
-            )
-        ],
-        model_parameters={
-            'temperature': 0.7,
-            'top_p': 1.0,
-            'max_tokens': 10
-        },
-        stop=['you'],
+        prompt_messages=[UserPromptMessage(content="Hello World!")],
+        model_parameters={"temperature": 0.7, "top_p": 1.0, "max_tokens": 10},
+        stop=["you"],
         stream=True,
-        user="abc-123"
+        user="abc-123",
     )
 
     assert isinstance(response, Generator)
@@ -154,64 +126,48 @@ def test_invoke_stream_chat_model():
         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 = LocalAILanguageModel()
 
     num_tokens = model.get_num_tokens(
-        model='????',
+        model="????",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'chat_completion',
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "chat_completion",
         },
         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='????',
+        model="????",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'chat_completion',
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "chat_completion",
         },
-        prompt_messages=[
-            UserPromptMessage(
-                content='Hello World!'
-            )
-        ],
+        prompt_messages=[UserPromptMessage(content="Hello World!")],
     )
 
     assert isinstance(num_tokens, int)

api/tests/integration_tests/model_runtime/localai/test_rerank.py

@@ -12,30 +12,29 @@ def test_validate_credentials_for_chat_model():
 
     with pytest.raises(CredentialsValidateFailedError):
         model.validate_credentials(
-            model='bge-reranker-v2-m3',
+            model="bge-reranker-v2-m3",
             credentials={
-                'server_url': 'hahahaha',
-                'completion_type': 'completion',
-            }
+                "server_url": "hahahaha",
+                "completion_type": "completion",
+            },
         )
 
     model.validate_credentials(
-        model='bge-reranker-base',
+        model="bge-reranker-base",
         credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL'),
-            'completion_type': 'completion',
-        }
+            "server_url": os.environ.get("LOCALAI_SERVER_URL"),
+            "completion_type": "completion",
+        },
     )
 
+
 def test_invoke_rerank_model():
     model = LocalaiRerankModel()
 
     response = model.invoke(
-        model='bge-reranker-base',
-        credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL')
-        },
-        query='Organic skincare products for sensitive skin',
+        model="bge-reranker-base",
+        credentials={"server_url": os.environ.get("LOCALAI_SERVER_URL")},
+        query="Organic skincare products for sensitive skin",
         docs=[
             "Eco-friendly kitchenware for modern homes",
             "Biodegradable cleaning supplies for eco-conscious consumers",
@@ -45,43 +44,38 @@ def test_invoke_rerank_model():
             "Sustainable gardening tools and compost solutions",
             "Sensitive skin-friendly facial cleansers and toners",
             "Organic food wraps and storage solutions",
-            "Yoga mats made from recycled materials"
+            "Yoga mats made from recycled materials",
         ],
         top_n=3,
         score_threshold=0.75,
-        user="abc-123"
+        user="abc-123",
     )
 
     assert isinstance(response, RerankResult)
     assert len(response.docs) == 3
 
+
 def test__invoke():
     model = LocalaiRerankModel()
 
     # Test case 1: Empty docs
     result = model._invoke(
-        model='bge-reranker-base',
-        credentials={
-            'server_url': 'https://example.com',
-            'api_key': '1234567890'
-        },
-        query='Organic skincare products for sensitive skin',
+        model="bge-reranker-base",
+        credentials={"server_url": "https://example.com", "api_key": "1234567890"},
+        query="Organic skincare products for sensitive skin",
         docs=[],
         top_n=3,
         score_threshold=0.75,
-        user="abc-123"
+        user="abc-123",
     )
     assert isinstance(result, RerankResult)
     assert len(result.docs) == 0
 
     # Test case 2: Valid invocation
     result = model._invoke(
-        model='bge-reranker-base',
-        credentials={
-            'server_url': 'https://example.com',
-            'api_key': '1234567890'
-        },
-        query='Organic skincare products for sensitive skin',
+        model="bge-reranker-base",
+        credentials={"server_url": "https://example.com", "api_key": "1234567890"},
+        query="Organic skincare products for sensitive skin",
         docs=[
             "Eco-friendly kitchenware for modern homes",
             "Biodegradable cleaning supplies for eco-conscious consumers",
@@ -91,12 +85,12 @@ def test__invoke():
             "Sustainable gardening tools and compost solutions",
             "Sensitive skin-friendly facial cleansers and toners",
             "Organic food wraps and storage solutions",
-            "Yoga mats made from recycled materials"
+            "Yoga mats made from recycled materials",
         ],
         top_n=3,
         score_threshold=0.75,
-        user="abc-123"
+        user="abc-123",
     )
     assert isinstance(result, RerankResult)
     assert len(result.docs) == 3
-    assert all(isinstance(doc, RerankDocument) for doc in result.docs)
+    assert all(isinstance(doc, RerankDocument) for doc in result.docs)

api/tests/integration_tests/model_runtime/localai/test_speech2text.py

@@ -10,19 +10,9 @@ def test_validate_credentials():
     model = LocalAISpeech2text()
 
     with pytest.raises(CredentialsValidateFailedError):
-        model.validate_credentials(
-            model='whisper-1',
-            credentials={
-                'server_url': 'invalid_url'
-            }
-        )
+        model.validate_credentials(model="whisper-1", credentials={"server_url": "invalid_url"})
 
-    model.validate_credentials(
-        model='whisper-1',
-        credentials={
-            'server_url': os.environ.get('LOCALAI_SERVER_URL')
-        }
-    )
+    model.validate_credentials(model="whisper-1", credentials={"server_url": os.environ.get("LOCALAI_SERVER_URL")})
 
 
 def test_invoke_model():
@@ -32,23 +22,21 @@ def test_invoke_model():
     current_dir = os.path.dirname(os.path.abspath(__file__))
 
     # Get assets directory
-    assets_dir = os.path.join(os.path.dirname(current_dir), 'assets')
+    assets_dir = os.path.join(os.path.dirname(current_dir), "assets")
 
     # Construct the path to the audio file
-    audio_file_path = os.path.join(assets_dir, 'audio.mp3')
+    audio_file_path = os.path.join(assets_dir, "audio.mp3")
 
     # Open the file and get the file object
-    with open(audio_file_path, 'rb') as audio_file:
+    with open(audio_file_path, "rb") as audio_file:
         file = audio_file
 
         result = model.invoke(
-            model='whisper-1',
-            credentials={
-                'server_url': os.environ.get('LOCALAI_SERVER_URL')
-            },
+            model="whisper-1",
+            credentials={"server_url": os.environ.get("LOCALAI_SERVER_URL")},
             file=file,
-            user="abc-123"
+            user="abc-123",
         )
 
         assert isinstance(result, str)
-        assert result == '1, 2, 3, 4, 5, 6, 7, 8, 9, 10'
+        assert result == "1, 2, 3, 4, 5, 6, 7, 8, 9, 10"